double TwoBody::GetPoiUpperSimple(std::string channel, Double_t peak){
//
// Estimate a good value for the upper boundary of the range of POI
// using just data in a window corresponding to the signal region
//
std::string legend = "[TwoBody::GetPoiUpperSimple]: ";
char buf[128];
// special handling needed for single-channel workspaces
bool b_single_channel;
if (channel.size()==0) b_single_channel = true; else b_single_channel = false;
double _range = 1.0;
// get data yield under the signal peak
ws->var("peak")->setVal(peak);
if (b_single_channel) sprintf(buf,"width");
else sprintf(buf,"width_%s",channel.c_str());
double _width = 0;//ws->function(buf)->getVal();
if (b_single_channel) sprintf(buf,"sigma");
else sprintf(buf,"sigma_%s",channel.c_str());
double _sigma = ws->function(buf)->getVal();
double c_min = peak - sqrt(_width*_width + _sigma*_sigma);
double c_max = peak + sqrt(_width*_width + _sigma*_sigma);
sprintf(buf, "mass>=%f && mass<=%f", c_min, c_max);
double n_count = data->sumEntries( buf );
// ad-hoc fix when there are no events in window
if (n_count < 0.3) n_count = 0.3;
std::cout << legend << "event yield in data in the window: "
<< n_count << std::endl;
// compute the corresponding POI range
if (b_single_channel) sprintf(buf,"nsig_scale");
else sprintf(buf,"nsig_scale_%s",channel.c_str());
double _nsig_scale = ws->var(buf)->getVal();
if (b_single_channel) sprintf(buf,"nz");
else sprintf(buf,"nz_%s",channel.c_str());
double _nz = ws->var(buf)->getVal();
if (b_single_channel) sprintf(buf,"eff");
else sprintf(buf,"eff_%s",channel.c_str());
double _eff = ws->function(buf)->getVal();
double n_excess = 3.0 * sqrt(n_count)/0.68; // let signal excess be ~ uncertainty on BG
_range = n_excess / _nsig_scale / _nz / _eff;
return _range;
}
///
/// Make an Asimov toy: set all observables set to truth values.
/// The Asimov point needs to be loaded in the combiner before.
/// \param c - combiner which should be set to an asimov toy
///
void GammaComboEngine::setAsimovObservables(Combiner* c)
{
if ( !c->isCombined() ) {
cout << "GammaComboEngine::setAsimovObservables() : ERROR : Can't set an Asimov toy before "
"the combiner is combined. Call combine() first." << endl;
exit(1);
}
// set observables to asimov values in workspace
RooWorkspace* w = c->getWorkspace();
TIterator* itObs = c->getObservables()->createIterator();
while(RooRealVar* pObs = (RooRealVar*) itObs->Next()) {
// get theory name from the observable name
TString pThName = pObs->GetName();
pThName.ReplaceAll("obs","th");
// get the theory relation
RooAbsReal* th = w->function(pThName);
if ( th==0 ) {
cout << "GammaComboEngine::setAsimovObservables() : ERROR : theory relation not found in workspace: " << pThName << endl;
exit(1);
}
// set the observable to what the theory relation predicts
pObs->setVal(th->getVal());
}
delete itObs;
// write back the asimov values to the PDF object so that when
// the PDF is printed, the asimov values show up
for ( int i=0; i<c->getPdfs().size(); i++ ) {
PDF_Abs* pdf = c->getPdfs()[i];
pdf->setObservableSourceString("Asimov");
TIterator* itObs = pdf->getObservables()->createIterator();
while(RooRealVar* pObs = (RooRealVar*) itObs->Next()) {
RooAbsReal* obs = w->var(pObs->GetName());
if ( obs==0 ) {
cout << "GammaComboEngine::setAsimovObservables() : ERROR : observable not found in workspace: " << pObs->GetName() << endl;
exit(1);
}
pdf->setObservable(pObs->GetName(), obs->getVal());
}
delete itObs;
}
}
// Function that loads
LoadedWS LoadWorkspace(
TString ws_file,
bool dobarrel
){
TFile *ws_rootfp = TFile::Open(ws_file);
RooWorkspace *ws;
if (dobarrel)
ws = (RooWorkspace*)ws_rootfp->Get("wereg_eb");
else
ws = (RooWorkspace*)ws_rootfp->Get("wereg_ee");
//#######################################
// Load relevant variables from the ws
//#######################################
// Read variables from workspace
RooGBRTargetFlex *meantgt;
if (dobarrel)
meantgt = static_cast<RooGBRTargetFlex*>( ws->arg("sigmeantEB") );
else
meantgt = static_cast<RooGBRTargetFlex*>( ws->arg("sigmeantEE") );
RooRealVar *tgtvar = ws->var("targetvar");
RooAbsPdf *sigpdf;
RooAbsReal *sigmeanlim;
RooAbsReal *sigwidthlim;
RooAbsReal *signlim;
RooAbsReal *sign2lim;
if (dobarrel){
sigpdf = ws->pdf("sigpdfEB");
sigmeanlim = ws->function("sigmeanlimEB");
sigwidthlim = ws->function("sigwidthlimEB");
signlim = ws->function("signlimEB");
sign2lim = ws->function("sign2limEB");
}
else {
sigpdf = ws->pdf("sigpdfEE");
sigmeanlim = ws->function("sigmeanlimEE");
sigwidthlim = ws->function("sigwidthlimEE");
signlim = ws->function("signlimEE");
sign2lim = ws->function("sign2limEE");
}
//#######################################
// Register to-be-returned variables in a specific struct
//#######################################
LoadedWS LWS;
LWS.ws = ws;
if (dobarrel)
LWS.name = "wereg_eb";
else
LWS.name = "wereg_ee";
LWS.meantgt = meantgt;
LWS.tgtvar = tgtvar;
LWS.sigpdf = sigpdf;
LWS.sigmeanlim = sigmeanlim;
LWS.sigwidthlim = sigwidthlim;
LWS.signlim = signlim;
LWS.sign2lim = sign2lim;
return LWS;
}
void eregtesting_13TeV_Eta(bool dobarrel=true, bool doele=false,int gammaID=0) {
//output dir
TString EEorEB = "EE";
if(dobarrel)
{
EEorEB = "EB";
}
TString gammaDir = "bothGammas";
if(gammaID==1)
{
gammaDir = "gamma1";
}
else if(gammaID==2)
{
gammaDir = "gamma2";
}
TString dirname = TString::Format("ereg_test_plots_Eta/%s_%s",gammaDir.Data(),EEorEB.Data());
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
TString infile = TString::Format("../../ereg_ws_Eta/%s/%s",gammaDir.Data(),fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *meantgt = static_cast<RooGBRTargetFlex*>(ws->arg("sigmeant"));
RooRealVar *tgtvar = ws->var("tgtvar");
RooArgList vars;
vars.add(meantgt->FuncVars());
vars.add(*tgtvar);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
//TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
//TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiPion_FlatPt-1To15/Gun_FlatPt1to15_MultiPion_withPhotonPtFilter_pythia8/photons_0_half2.root");
//TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiEta_FlatPt-1To15/Gun_FlatPt1to15_MultiEta_withPhotonPtFilter_pythia8/photons_22Aug2017_V3_half2.root");
TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiEta_FlatPt-1To15/Gun_FlatPt1to15_MultiEtaToGG_withPhotonPtFilter_pythia8/photons_20171008_half2.root");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
//selection cuts for testing
//TCut selcut = "(STr2_enG1_true/cosh(STr2_Eta_1)>1.0) && (STr2_S4S9_1>0.75)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_enG_true/STr2_enG_rec)<3.0 && STr2_EOverEOther < 10.0 && STr2_EOverEOther > 0.1";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_mPi0_nocor>0.1)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2)";
TCut selcut = "";
if(dobarrel) selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.2) && (STr2_mPi0_nocor < 1.0) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)<1.479 && (!STr2_fromPi0)";
//if(dobarrel) selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)<1.479";
else selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.2) && (STr2_mPi0_nocor < 1.0) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)>1.479 && (!STr2_fromPi0)";
//else selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)>1.479";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_iEta_on2520==0 || STr2_iPhi_on20==0) ";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)>60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
/*
TCut selcut;
if (dobarrel)
selcut = "ph.genpt>25. && ph.isbarrel && ph.ispromptgen";
else
selcut = "ph.genpt>25. && !ph.isbarrel && ph.ispromptgen";
*/
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(Entry$%10==0)";
TCut prescale10alt = "(Entry$%10==1)";
TCut prescale25 = "(Entry$%25==0)";
TCut prescale100 = "(Entry$%100==0)";
TCut prescale1000 = "(Entry$%1000==0)";
TCut evenevents = "(Entry$%2==0)";
TCut oddevents = "(Entry$%2==1)";
TCut prescale100alt = "(Entry$%100==1)";
TCut prescale1000alt = "(Entry$%1000==1)";
TCut prescale50alt = "(Entry$%50==1)";
TCut Events3_4 = "(Entry$%4==3)";
TCut Events1_4 = "(Entry$%4==1)";
TCut Events2_4 = "(Entry$%4==2)";
TCut Events0_4 = "(Entry$%4==0)";
TCut Events01_4 = "(Entry$%4<2)";
TCut Events23_4 = "(Entry$%4>1)";
TCut EventsTest = "(Entry$%2==1)";
//weightvar.SetTitle(EventsTest*selcut);
weightvar.SetTitle(selcut);
/*
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
*/
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
if (doele)
weightvar.SetTitle(prescale1000alt*selcut);
else
weightvar.SetTitle(prescale10alt*selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
//input variable corresponding to sceta
RooRealVar *scEraw = ws->var("var_0");
scEraw->setRange(1.,2.);
scEraw->setBins(100);
// RooRealVar *scetavar = ws->var("var_1");
// RooRealVar *scphivar = ws->var("var_2");
//regressed output functions
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
// RooAbsReal *sigalphalim = ws->function("sigalphalim");
//RooAbsReal *sigalpha2lim = ws->function("sigalpha2lim");
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
// RooRealVar *alphavar = (RooRealVar*)hdataclone->addColumn(*sigalphalim);
// RooRealVar *alpha2var = (RooRealVar*)hdataclone->addColumn(*sigalpha2lim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.6,2.0,100);
hdata->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
craw->SaveAs("RawE.pdf");
craw->SaveAs("RawE.png");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.pdf");
craw->SaveAs("RawElog.png");
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.pdf");
cmean->SaveAs("mean.png");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.pdf");
cwidth->SaveAs("width.png");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.pdf");
cn->SaveAs("n.png");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.pdf");
cn2->SaveAs("n2.png");
/*
TCanvas *calpha = new TCanvas;
RooPlot *plotalpha = alphavar->frame(0.,5.,200);
hdataclone->plotOn(plotalpha);
plotalpha->Draw();
calpha->SaveAs("alpha.pdf");
calpha->SaveAs("alpha.png");
TCanvas *calpha2 = new TCanvas;
RooPlot *plotalpha2 = alpha2var->frame(0.,5.,200);
hdataclone->plotOn(plotalpha2);
plotalpha2->Draw();
calpha2->SaveAs("alpha2.pdf");
calpha2->SaveAs("alpha2.png");
*/
/*
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.pdf");
ceta->SaveAs("eta.png");
*/
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw;// = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor;// = hdata->createHistogram("hecor",*ecorvar);
if (EEorEB == "EB")
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.0));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(800,0.,2.0));
}
else
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(200,0.,2.));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(200,0.,2.));
}
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
heraw->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
hecor->GetXaxis()->SetRangeUser(0.0,1.5);
heraw->GetXaxis()->SetRangeUser(0.0,1.5);
/*if(EEorEB == "EE")
{
heraw->GetYaxis()->SetRangeUser(10.0,200.0);
hecor->GetYaxis()->SetRangeUser(10.0,200.0);
}
*/
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
double effsigma_cor, effsigma_raw, fwhm_cor, fwhm_raw;
if(EEorEB == "EB")
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(800,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(800,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
else
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
TCanvas *cresponse = new TCanvas;
gStyle->SetOptStat(0);
gStyle->SetPalette(107);
hecor->SetTitle("");
heraw->SetTitle("");
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
//show errSigma in the plot
TLegend *leg = new TLegend(0.1, 0.75, 0.7, 0.9);
leg->AddEntry(hecor,Form("E_{cor}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_cor, fwhm_cor),"l");
leg->AddEntry(heraw,Form("E_{raw}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_raw, fwhm_raw),"l");
leg->SetFillStyle(0);
leg->SetBorderSize(0);
// leg->SetTextColor(kRed);
leg->Draw();
cresponse->SaveAs("response.pdf");
cresponse->SaveAs("response.png");
cresponse->SetLogy();
cresponse->SaveAs("responselog.pdf");
cresponse->SaveAs("responselog.png");
// draw CCs vs eta and phi
/*
TCanvas *c_eta = new TCanvas;
TH1 *h_eta = hdata->createHistogram("h_eta",*scetavar,Binning(100,-3.2,3.2));
h_eta->Draw("HIST");
c_eta->SaveAs("heta.pdf");
c_eta->SaveAs("heta.png");
TCanvas *c_phi = new TCanvas;
TH1 *h_phi = hdata->createHistogram("h_phi",*scphivar,Binning(100,-3.2,3.2));
h_phi->Draw("HIST");
c_phi->SaveAs("hphi.pdf");
c_phi->SaveAs("hphi.png");
*/
RooRealVar *scetaiXvar = ws->var("var_4");
RooRealVar *scphiiYvar = ws->var("var_5");
if(EEorEB=="EB")
{
scetaiXvar->setRange(-90,90);
scetaiXvar->setBins(180);
scphiiYvar->setRange(0,360);
scphiiYvar->setBins(360);
}
else
{
scetaiXvar->setRange(0,50);
scetaiXvar->setBins(50);
scphiiYvar->setRange(0,50);
scphiiYvar->setBins(50);
}
ecorvar->setRange(0.5,1.5);
ecorvar->setBins(800);
rawvar->setRange(0.5,1.5);
rawvar->setBins(800);
TCanvas *c_cor_eta = new TCanvas;
TH3F *h3_CC_eta_phi = (TH3F*) hdata->createHistogram("var_5,var_4,ecor",(EEorEB=="EB") ? 170 : 100, (EEorEB=="EB") ? 360 : 100,25);
TProfile2D *h_CC_eta_phi = h3_CC_eta_phi->Project3DProfile();
h_CC_eta_phi->SetTitle("E_{cor}/E_{true}");
if(EEorEB=="EB")
{
h_CC_eta_phi->GetXaxis()->SetTitle("i#eta");
h_CC_eta_phi->GetYaxis()->SetTitle("i#phi");
h_CC_eta_phi->GetXaxis()->SetRangeUser(-85,85);
h_CC_eta_phi->GetYaxis()->SetRangeUser(0,360);
}
else
{
h_CC_eta_phi->GetXaxis()->SetTitle("iX");
h_CC_eta_phi->GetYaxis()->SetTitle("iY");
}
h_CC_eta_phi->SetMinimum(0.5);
h_CC_eta_phi->SetMaximum(1.5);
h_CC_eta_phi->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta_phi.pdf");
c_cor_eta->SaveAs("cor_vs_eta_phi.png");
TH2F *h_CC_eta = hdata->createHistogram(*scetaiXvar, *ecorvar, "","cor_vs_eta");
if(EEorEB=="EB")
{
h_CC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetXaxis()->SetTitle("iX");
}
h_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_eta->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta.pdf");
c_cor_eta->SaveAs("cor_vs_eta.png");
TCanvas *c_cor_scEraw = new TCanvas;
TH2F *h_CC_scEraw = hdata->createHistogram(*scEraw, *ecorvar, "","cor_vs_scEraw");
h_CC_scEraw->GetXaxis()->SetTitle("E_{raw}");
h_CC_scEraw->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_scEraw->Draw("COLZ");
c_cor_scEraw->SaveAs("cor_vs_scEraw.pdf");
c_cor_scEraw->SaveAs("cor_vs_scEraw.png");
TCanvas *c_raw_scEraw = new TCanvas;
TH2F *h_RC_scEraw = hdata->createHistogram(*scEraw, *rawvar, "","raw_vs_scEraw");
h_RC_scEraw->GetXaxis()->SetTitle("E_{raw}");
h_RC_scEraw->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_scEraw->Draw("COLZ");
c_raw_scEraw->SaveAs("raw_vs_scEraw.pdf");
c_raw_scEraw->SaveAs("raw_vs_scEraw.png");
TCanvas *c_cor_phi = new TCanvas;
TH2F *h_CC_phi = hdata->createHistogram(*scphiiYvar, *ecorvar, "","cor_vs_phi");
if(EEorEB=="EB")
{
h_CC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetXaxis()->SetTitle("iY");
}
h_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_phi->Draw("COLZ");
c_cor_phi->SaveAs("cor_vs_phi.pdf");
c_cor_phi->SaveAs("cor_vs_phi.png");
TCanvas *c_raw_eta = new TCanvas;
TH3F *h3_RC_eta_phi = (TH3F*) hdata->createHistogram("var_5,var_4,raw",(EEorEB=="EB") ? 170 : 100, (EEorEB=="EB") ? 360 : 100,25);
TProfile2D *h_RC_eta_phi = h3_RC_eta_phi->Project3DProfile();
h_RC_eta_phi->SetTitle("E_{raw}/E_{true}");
if(EEorEB=="EB")
{
h_RC_eta_phi->GetXaxis()->SetTitle("i#eta");
h_RC_eta_phi->GetYaxis()->SetTitle("i#phi");
h_RC_eta_phi->GetXaxis()->SetRangeUser(-85,85);
h_RC_eta_phi->GetYaxis()->SetRangeUser(0,360);
}
else
{
h_RC_eta_phi->GetXaxis()->SetTitle("iX");
h_RC_eta_phi->GetYaxis()->SetTitle("iY");
}
h_RC_eta_phi->SetMinimum(0.5);
h_RC_eta_phi->SetMaximum(1.5);
h_RC_eta_phi->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta_phi.pdf");
c_raw_eta->SaveAs("raw_vs_eta_phi.png");
TH2F *h_RC_eta = hdata->createHistogram(*scetaiXvar, *rawvar, "","raw_vs_eta");
if(EEorEB=="EB")
{
h_RC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_RC_eta->GetXaxis()->SetTitle("iX");
}
h_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_eta->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta.pdf");
c_raw_eta->SaveAs("raw_vs_eta.png");
TCanvas *c_raw_phi = new TCanvas;
TH2F *h_RC_phi = hdata->createHistogram(*scphiiYvar, *rawvar, "","raw_vs_phi");
if(EEorEB=="EB")
{
h_RC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_RC_phi->GetXaxis()->SetTitle("iY");
}
h_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_phi->Draw("COLZ");
c_raw_phi->SaveAs("raw_vs_phi.pdf");
c_raw_phi->SaveAs("raw_vs_phi.png");
//on2,5,20, etc
if(EEorEB == "EB")
{
TCanvas *myC_iCrystal_mod = new TCanvas;
RooRealVar *SM_distvar = ws->var("var_6");
SM_distvar->setRange(0,10);
SM_distvar->setBins(10);
TH2F *h_CC_SM_dist = hdata->createHistogram(*SM_distvar, *ecorvar, "","cor_vs_SM_dist");
h_CC_SM_dist->GetXaxis()->SetTitle("SM_dist");
h_CC_SM_dist->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_SM_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_SM_dist.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_SM_dist.png");
TH2F *h_RC_SM_dist = hdata->createHistogram(*SM_distvar, *rawvar, "","raw_vs_SM_dist");
h_RC_SM_dist->GetXaxis()->SetTitle("distance to SM gap");
h_RC_SM_dist->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_SM_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_SM_dist.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_SM_dist.png");
RooRealVar *M_distvar = ws->var("var_7");
M_distvar->setRange(0,13);
M_distvar->setBins(10);
TH2F *h_CC_M_dist = hdata->createHistogram(*M_distvar, *ecorvar, "","cor_vs_M_dist");
h_CC_M_dist->GetXaxis()->SetTitle("M_dist");
h_CC_M_dist->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_M_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_M_dist.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_M_dist.png");
TH2F *h_RC_M_dist = hdata->createHistogram(*M_distvar, *rawvar, "","raw_vs_M_dist");
h_RC_M_dist->GetXaxis()->SetTitle("distance to module gap");
h_RC_M_dist->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_M_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_M_dist.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_M_dist.png");
/*
RooRealVar *DeltaRG1G2var = ws->var("var_8");
DeltaRG1G2var->setRange(0,0.2);
DeltaRG1G2var->setBins(100);
TH2F *h_CC_DeltaRG1G2 = hdata->createHistogram(*DeltaRG1G2var, *ecorvar, "","cor_vs_DeltaRG1G2");
h_CC_DeltaRG1G2->GetXaxis()->SetTitle("DeltaRG1G2");
h_CC_DeltaRG1G2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_DeltaRG1G2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_DeltaRG1G2.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_DeltaRG1G2.png");
TH2F *h_RC_DeltaRG1G2 = hdata->createHistogram(*DeltaRG1G2var, *rawvar, "","raw_vs_DeltaRG1G2");
h_RC_DeltaRG1G2->GetXaxis()->SetTitle("distance to module gap");
h_RC_DeltaRG1G2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_DeltaRG1G2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_DeltaRG1G2.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_DeltaRG1G2.png");
*/
}
// other variables
TCanvas *myC_variables = new TCanvas;
RooRealVar *Nxtalvar = ws->var("var_1");
Nxtalvar->setRange(0,10);
Nxtalvar->setBins(10);
TH2F *h_CC_Nxtal = hdata->createHistogram(*Nxtalvar, *ecorvar, "","cor_vs_Nxtal");
h_CC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_CC_Nxtal->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Nxtal.pdf");
myC_variables->SaveAs("cor_vs_Nxtal.png");
TH2F *h_RC_Nxtal = hdata->createHistogram(*Nxtalvar, *rawvar, "","raw_vs_Nxtal");
h_RC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_RC_Nxtal->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Nxtal.pdf");
myC_variables->SaveAs("raw_vs_Nxtal.png");
RooRealVar *S4S9var = ws->var("var_2");
int Nbins_S4S9 = 100;
double Low_S4S9 = 0.6;
double High_S4S9 = 1.0;
S4S9var->setRange(Low_S4S9,High_S4S9);
S4S9var->setBins(Nbins_S4S9);
TH2F *h_CC_S4S9 = hdata->createHistogram(*S4S9var, *ecorvar, "","cor_vs_S4S9");
h_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h_CC_S4S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S4S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S4S9.pdf");
myC_variables->SaveAs("cor_vs_S4S9.png");
TH2F *h_RC_S4S9 = hdata->createHistogram(*S4S9var, *rawvar, "","raw_vs_S4S9");
h_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h_RC_S4S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S4S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S4S9.pdf");
myC_variables->SaveAs("raw_vs_S4S9.png");
RooRealVar *S2S9var = ws->var("var_3");
int Nbins_S2S9 = 100;
double Low_S2S9 = 0.5;
double High_S2S9 = 1.0;
S2S9var->setRange(Low_S2S9,High_S2S9);
S2S9var->setBins(Nbins_S2S9);
TH2F *h_CC_S2S9 = hdata->createHistogram(*S2S9var, *ecorvar, "","cor_vs_S2S9");
h_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h_CC_S2S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S2S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S2S9.pdf");
myC_variables->SaveAs("cor_vs_S2S9.png");
TH2F *h_RC_S2S9 = hdata->createHistogram(*S2S9var, *rawvar, "","raw_vs_S2S9");
h_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h_RC_S2S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S2S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S2S9.pdf");
myC_variables->SaveAs("raw_vs_S2S9.png");
TH2F *h_S2S9_eta = hdata->createHistogram(*scetaiXvar, *S2S9var, "","S2S9_vs_eta");
h_S2S9_eta->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S2S9_eta->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_eta.pdf");
myC_variables->SaveAs("S2S9_vs_eta.png");
TH2F *h_S4S9_eta = hdata->createHistogram(*scetaiXvar, *S4S9var, "","S4S9_vs_eta");
h_S4S9_eta->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S4S9_eta->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_eta.pdf");
myC_variables->SaveAs("S4S9_vs_eta.png");
TH2F *h_S2S9_phi = hdata->createHistogram(*scphiiYvar, *S2S9var, "","S2S9_vs_phi");
h_S2S9_phi->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S2S9_phi->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_phi.pdf");
myC_variables->SaveAs("S2S9_vs_phi.png");
TH2F *h_S4S9_phi = hdata->createHistogram(*scphiiYvar, *S4S9var, "","S4S9_vs_phi");
h_S4S9_phi->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S4S9_phi->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_phi.pdf");
myC_variables->SaveAs("S4S9_vs_phi.png");
if(EEorEB=="EE")
{
}
TProfile *p_CC_eta = h_CC_eta->ProfileX("p_CC_eta");//,1,-1,"s");
p_CC_eta->GetYaxis()->SetRangeUser(0.8,1.05);
if(EEorEB == "EB")
{
// p_CC_eta->GetYaxis()->SetRangeUser(0.85,1.0);
// p_CC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_eta->SetTitle("");
p_CC_eta->Draw();
myC_variables->SaveAs("profile_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_cor_vs_eta.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_CC_eta = new TH1F("h1_fit_CC_eta","h1_fit_CC_eta",(EEorEB=="EB") ? 180 : 50,(EEorEB=="EB") ? -90 : 0, (EEorEB=="EB") ? 90 : 50);
for(int ix = 1;ix <= h_CC_eta->GetNbinsX(); ix++)
{
stringstream os_iEta;
os_iEta << ((EEorEB=="EB") ? (-90 + ix -1) : (0 + ix -1));
string ss_iEta = os_iEta.str();
TH1D * h_temp = h_CC_eta->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.95,1.07);
h_temp->Fit("f_temp","R");
h1_fit_CC_eta->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_CC_eta->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{cor}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".pdf").c_str());
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".png").c_str());
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_CC_eta->GetYaxis()->SetRangeUser(0.95,1.05);
h1_fit_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h1_fit_CC_eta->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#eta" : "iX");
h1_fit_CC_eta->SetTitle("");
h1_fit_CC_eta->Draw();
myC_variables->SaveAs("profile_fit_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_fit_cor_vs_eta.png");
myC_variables->SaveAs("profile_fit_cor_vs_eta.C");
TProfile *p_RC_eta = h_RC_eta->ProfileX("p_RC_eta");//,1,-1,"s");
p_RC_eta->GetYaxis()->SetRangeUser(0.8,1.05);
if(EEorEB=="EB")
{
// p_RC_eta->GetYaxis()->SetRangeUser(0.80,0.95);
// p_RC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_eta->SetTitle("");
p_RC_eta->Draw();
myC_variables->SaveAs("profile_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_raw_vs_eta.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_RC_eta = new TH1F("h1_fit_RC_eta","h1_fit_RC_eta",(EEorEB=="EB") ? 180 : 50,(EEorEB=="EB") ? -90 : 0, (EEorEB=="EB") ? 90 : 50);
for(int ix = 1;ix <= h_RC_eta->GetNbinsX(); ix++)
{
stringstream os_iEta;
os_iEta << ((EEorEB=="EB") ? (-90 + ix -1) : (0 + ix -1));
string ss_iEta = os_iEta.str();
TH1D * h_temp = h_RC_eta->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.87,1.05);
h_temp->Fit("f_temp","R");
h1_fit_RC_eta->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_RC_eta->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{raw}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".pdf").c_str());
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".png").c_str());
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_RC_eta->GetYaxis()->SetRangeUser(0.9,1.0);
h1_fit_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h1_fit_RC_eta->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#eta" : "iX");
h1_fit_RC_eta->SetTitle("");
h1_fit_RC_eta->Draw();
myC_variables->SaveAs("profile_fit_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_fit_raw_vs_eta.png");
myC_variables->SaveAs("profile_fit_raw_vs_eta.C");
int Nbins_iEta = EEorEB=="EB" ? 180 : 50;
int nLow_iEta = EEorEB=="EB" ? -90 : 0;
int nHigh_iEta = EEorEB=="EB" ? 90 : 50;
TH1F *h1_RC_eta = new TH1F("h1_RC_eta","h1_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_RC_eta->SetBinContent(i,p_RC_eta->GetBinError(i));
}
h1_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_RC_eta->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_eta->SetTitle("");
h1_RC_eta->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.png");
TH1F *h1_CC_eta = new TH1F("h1_CC_eta","h1_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_CC_eta->SetBinContent(i,p_CC_eta->GetBinError(i));
}
h1_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_CC_eta->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_eta->SetTitle("");
h1_CC_eta->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.png");
TProfile *p_CC_phi = h_CC_phi->ProfileX("p_CC_phi");//,1,-1,"s");
p_CC_phi->GetYaxis()->SetRangeUser(0.9,1.0);
if(EEorEB == "EB")
{
// p_CC_phi->GetYaxis()->SetRangeUser(0.94,1.00);
}
p_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_phi->SetTitle("");
p_CC_phi->Draw();
myC_variables->SaveAs("profile_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_cor_vs_phi.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_CC_phi = new TH1F("h1_fit_CC_phi","h1_fit_CC_phi",(EEorEB=="EB") ? 360 : 50,(EEorEB=="EB") ? 0 : 0, (EEorEB=="EB") ? 360 : 50);
for(int ix = 1;ix <= h_CC_phi->GetNbinsX(); ix++)
{
stringstream os_iPhi;
os_iPhi << ((EEorEB=="EB") ? (0 + ix -1) : (0 + ix -1));
string ss_iPhi = os_iPhi.str();
TH1D * h_temp = h_CC_phi->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.95,1.07);
h_temp->Fit("f_temp","R");
h1_fit_CC_phi->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_CC_phi->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{cor}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".pdf").c_str());
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".png").c_str());
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_CC_phi->GetYaxis()->SetRangeUser(0.95,1.05);
h1_fit_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h1_fit_CC_phi->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#phi" : "iX");
h1_fit_CC_phi->SetTitle("");
h1_fit_CC_phi->Draw();
myC_variables->SaveAs("profile_fit_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_fit_cor_vs_phi.png");
myC_variables->SaveAs("profile_fit_cor_vs_phi.C");
TProfile *p_RC_phi = h_RC_phi->ProfileX("p_RC_phi");//,1,-1,"s");
p_RC_phi->GetYaxis()->SetRangeUser(0.8,0.9);
if(EEorEB=="EB")
{
// p_RC_phi->GetYaxis()->SetRangeUser(0.89,0.95);
}
p_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_phi->SetTitle("");
p_RC_phi->Draw();
myC_variables->SaveAs("profile_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_raw_vs_phi.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_RC_phi = new TH1F("h1_fit_RC_phi","h1_fit_RC_phi",(EEorEB=="EB") ? 360 : 50,(EEorEB=="EB") ? 0 : 0, (EEorEB=="EB") ? 360 : 50);
for(int ix = 1;ix <= h_RC_phi->GetNbinsX(); ix++)
{
stringstream os_iPhi;
os_iPhi << ((EEorEB=="EB") ? (0 + ix -1) : (0 + ix -1));
string ss_iPhi = os_iPhi.str();
TH1D * h_temp = h_RC_phi->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.87,1.05);
h_temp->Fit("f_temp","R");
h1_fit_RC_phi->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_RC_phi->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{raw}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".pdf").c_str());
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".png").c_str());
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_RC_phi->GetYaxis()->SetRangeUser(0.9,1.0);
h1_fit_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h1_fit_RC_phi->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#phi" : "iX");
h1_fit_RC_phi->SetTitle("");
h1_fit_RC_phi->Draw();
myC_variables->SaveAs("profile_fit_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_fit_raw_vs_phi.png");
myC_variables->SaveAs("profile_fit_raw_vs_phi.C");
int Nbins_iPhi = EEorEB=="EB" ? 360 : 50;
int nLow_iPhi = EEorEB=="EB" ? 0 : 0;
int nHigh_iPhi = EEorEB=="EB" ? 360 : 50;
TH1F *h1_RC_phi = new TH1F("h1_RC_phi","h1_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_RC_phi->SetBinContent(i,p_RC_phi->GetBinError(i));
}
h1_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_RC_phi->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_phi->SetTitle("");
h1_RC_phi->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.png");
TH1F *h1_CC_phi = new TH1F("h1_CC_phi","h1_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_CC_phi->SetBinContent(i,p_CC_phi->GetBinError(i));
}
h1_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_CC_phi->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_phi->SetTitle("");
h1_CC_phi->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.png");
// FWHM over sigma_eff vs. eta/phi
TH1F *h1_FoverS_RC_phi = new TH1F("h1_FoverS_RC_phi","h1_FoverS_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_CC_phi = new TH1F("h1_FoverS_CC_phi","h1_FoverS_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_RC_eta = new TH1F("h1_FoverS_RC_eta","h1_FoverS_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_eta = new TH1F("h1_FoverS_CC_eta","h1_FoverS_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_S2S9 = new TH1F("h1_FoverS_CC_S2S9","h1_FoverS_CC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_RC_S2S9 = new TH1F("h1_FoverS_RC_S2S9","h1_FoverS_RC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_CC_S4S9 = new TH1F("h1_FoverS_CC_S4S9","h1_FoverS_CC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
TH1F *h1_FoverS_RC_S4S9 = new TH1F("h1_FoverS_RC_S4S9","h1_FoverS_RC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
float FWHMoverSigmaEff = 0.0;
TH1F *h_tmp_rawvar = new TH1F("tmp_rawvar","tmp_rawvar",800,0.5,1.5);
TH1F *h_tmp_corvar = new TH1F("tmp_corvar","tmp_corvar",800,0.5,1.5);
for(int i=1;i<=Nbins_iPhi;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_phi->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_phi->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_phi->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_phi->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_CC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_phi->SetTitle("");
h1_FoverS_CC_phi->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.png");
h1_FoverS_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_RC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_phi->SetTitle("");
h1_FoverS_RC_phi->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.png");
for(int i=1;i<=Nbins_iEta;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_eta->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_eta->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_eta->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_eta->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_CC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_eta->SetTitle("");
h1_FoverS_CC_eta->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.png");
h1_FoverS_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_RC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_eta->SetTitle("");
h1_FoverS_RC_eta->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.png");
for(int i=1;i<=Nbins_S2S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S2S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S2S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_CC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S2S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S2S9->SetTitle("");
h1_FoverS_CC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.png");
h1_FoverS_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_RC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S2S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S2S9->SetTitle("");
h1_FoverS_RC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.png");
for(int i=1;i<=Nbins_S4S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S4S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S4S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_CC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S4S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S4S9->SetTitle("");
h1_FoverS_CC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.png");
h1_FoverS_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_RC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S4S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S4S9->SetTitle("");
h1_FoverS_RC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.png");
printf("calc effsigma\n");
std::cout<<"_"<<EEorEB<<std::endl;
printf("corrected curve effSigma= %5f, FWHM=%5f \n",effsigma_cor, fwhm_cor);
printf("raw curve effSigma= %5f FWHM=%5f \n",effsigma_raw, fwhm_raw);
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
}
void plot_pll(TString fname="monoh_withsm_SRCR_bg11.7_bgslop-0.0_nsig0.0.root")
{
SetAtlasStyle();
TFile* file = TFile::Open(fname);
RooWorkspace* wspace = (RooWorkspace*) file->Get("wspace");
cout << "\n\ncheck that eff and reco terms included in BSM component to make fiducial cross-section" <<endl;
wspace->function("nsig")->Print();
RooRealVar* reco = wspace->var("reco");
if( wspace->function("nsig")->dependsOn(*reco) ) {
cout << "all good." <<endl;
} else {
cout << "need to rerun fit_withsm using DO_FIDUCIAL_LIMIT true" <<endl;
return;
}
/*
// DANGER
// TEST WITH EXAGGERATED UNCERTAINTY
wspace->var("unc_theory")->setMax(1);
wspace->var("unc_theory")->setVal(1);
wspace->var("unc_theory")->Print();
*/
// this was for making plot about decoupling/recoupling approach
TCanvas* tc = new TCanvas("tc","",400,400);
RooPlot *frame = wspace->var("xsec_bsm")->frame();
RooAbsPdf* pdfc = wspace->pdf("jointModeld");
RooAbsData* data = wspace->data("data");
RooAbsReal *nllJoint = pdfc->createNLL(*data, RooFit::Constrained()); // slice with fixed xsec_bsm
RooAbsReal *profileJoint = nllJoint->createProfile(*wspace->var("xsec_bsm"));
wspace->allVars().Print("v");
pdfc->fitTo(*data);
wspace->allVars().Print("v");
wspace->var("xsec_bsm")->Print();
double nllmin = 2*nllJoint->getVal();
wspace->var("xsec_bsm")->setVal(0);
double nll0 = 2*nllJoint->getVal();
cout << Form("nllmin = %f, nll0 = %f, Z=%f", nllmin, nll0, sqrt(nll0-nllmin)) << endl;
nllJoint->plotOn(frame, RooFit::LineColor(kGreen), RooFit::LineStyle(kDotted), RooFit::ShiftToZero(), RooFit::Name("nll_statonly")); // no error
profileJoint->plotOn(frame,RooFit::Name("pll") );
wspace->var("xsec_sm")->Print();
wspace->var("theory")->Print();
wspace->var("theory")->setConstant();
profileJoint->plotOn(frame, RooFit::LineColor(kRed), RooFit::LineStyle(kDashed), RooFit::Name("pll_smfixed") );
frame->GetXaxis()->SetTitle("#sigma_{BSM, fid} [fb]");
frame->GetYaxis()->SetTitle("-log #lambda ( #sigma_{BSM, fid} )");
double temp = frame->GetYaxis()->GetTitleOffset();
frame->GetYaxis()->SetTitleOffset( 1.1* temp );
frame->SetMinimum(1e-7);
frame->SetMaximum(4);
// Legend
double x1,y1,x2,y2;
GetX1Y1X2Y2(tc,x1,y1,x2,y2);
TLegend *legend_sr=FastLegend(x2-0.75,y2-0.3,x2-0.25,y2-0.5,0.045);
legend_sr->AddEntry(frame->findObject("pll"),"with #sigma_{SM} uncertainty","L");
legend_sr->AddEntry(frame->findObject("pll_smfixed"),"with #sigma_{SM} constant","L");
legend_sr->AddEntry(frame->findObject("nll_statonly"),"no systematics","L");
frame->Draw();
legend_sr->Draw("SAME");
// descriptive text
vector<TString> pavetext11;
pavetext11.push_back("#bf{#it{ATLAS Internal}}");
pavetext11.push_back("#sqrt{#it{s}} = 8 TeV #scale[0.6]{#int}Ldt = 20.3 fb^{-1}");
pavetext11.push_back("#it{H}+#it{E}_{T}^{miss} , #it{H #rightarrow #gamma#gamma}, #it{m}_{#it{H}} = 125.4 GeV");
TPaveText* text11=CreatePaveText(x2-0.75,y2-0.25,x2-0.25,y2-0.05,pavetext11,0.045);
text11->Draw();
tc->SaveAs("pll.pdf");
/*
wspace->var("xsec_bsm")->setConstant(true);
wspace->var("eff" )->setConstant(true);
wspace->var("mh" )->setConstant(true);
wspace->var("sigma_h" )->setConstant(true);
wspace->var("lumi" )->setConstant(true);
wspace->var("xsec_sm" )->setVal(v_xsec_sm);
wspace->var("eff" )->setVal(1.0);
wspace->var("lumi" )->setVal(v_lumi);
TH1* nllHist = profileJoint->createHistogram("xsec_bsm",100);
TFile* out = new TFile("nllHist.root","REPLACE");
nllHist->Write()
out->Write();
out->Close();
*/
}
void eregtesting_13TeV_Pi0(bool dobarrel=true, bool doele=false,int gammaID=0) {
//output dir
TString EEorEB = "EE";
if(dobarrel)
{
EEorEB = "EB";
}
TString gammaDir = "bothGammas";
if(gammaID==1)
{
gammaDir = "gamma1";
}
else if(gammaID==2)
{
gammaDir = "gamma2";
}
TString dirname = TString::Format("ereg_test_plots/%s_%s",gammaDir.Data(),EEorEB.Data());
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
TString infile = TString::Format("../../ereg_ws/%s/%s",gammaDir.Data(),fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *meantgt = static_cast<RooGBRTargetFlex*>(ws->arg("sigmeant"));
RooRealVar *tgtvar = ws->var("tgtvar");
RooArgList vars;
vars.add(meantgt->FuncVars());
vars.add(*tgtvar);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
//TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
if(dobarrel)
{
TFile *fdin = TFile::Open("/afs/cern.ch/work/z/zhicaiz/public/ECALpro_MC_TreeForRegression/Gun_Pi0_Pt1To15_FlatPU0to50RAW_withHLT_80X_mcRun2_GEN-SIM-RAW_ALL_EcalNtp_ALL_EB_combine_test.root");//("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
else
{
TFile *fdin = TFile::Open("/afs/cern.ch/work/z/zhicaiz/public/ECALpro_MC_TreeForRegression/Gun_Pi0_Pt1To15_FlatPU0to50RAW_withHLT_80X_mcRun2_GEN-SIM-RAW_ALL_EcalNtp_ALL_EE_combine_test.root");//("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
}
//selection cuts for testing
//TCut selcut = "(STr2_enG1_true/cosh(STr2_Eta_1)>1.0) && (STr2_S4S9_1>0.75)";
TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)>60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
/*
TCut selcut;
if (dobarrel)
selcut = "ph.genpt>25. && ph.isbarrel && ph.ispromptgen";
else
selcut = "ph.genpt>25. && !ph.isbarrel && ph.ispromptgen";
*/
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(Entry$%10==0)";
TCut prescale10alt = "(Entry$%10==1)";
TCut prescale25 = "(Entry$%25==0)";
TCut prescale100 = "(Entry$%100==0)";
TCut prescale1000 = "(Entry$%1000==0)";
TCut evenevents = "(Entry$%2==0)";
TCut oddevents = "(Entry$%2==1)";
TCut prescale100alt = "(Entry$%100==1)";
TCut prescale1000alt = "(Entry$%1000==1)";
TCut prescale50alt = "(Entry$%50==1)";
TCut Events3_4 = "(Entry$%4==3)";
TCut Events1_4 = "(Entry$%4==1)";
TCut Events2_4 = "(Entry$%4==2)";
TCut Events0_4 = "(Entry$%4==0)";
TCut Events01_4 = "(Entry$%4<2)";
TCut Events23_4 = "(Entry$%4>1)";
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
if (doele)
weightvar.SetTitle(prescale1000alt*selcut);
else
weightvar.SetTitle(prescale10alt*selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
//input variable corresponding to sceta
RooRealVar *scetavar = ws->var("var_1");
RooRealVar *scphivar = ws->var("var_2");
//regressed output functions
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
RooAbsReal *sigalphalim = ws->function("sigalphalim");
RooAbsReal *sigalpha2lim = ws->function("sigalpha2lim");
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
RooRealVar *alphavar = (RooRealVar*)hdataclone->addColumn(*sigalphalim);
RooRealVar *alpha2var = (RooRealVar*)hdataclone->addColumn(*sigalpha2lim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.6,2.0,100);
hdata->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
craw->SaveAs("RawE.pdf");
craw->SaveAs("RawE.png");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.pdf");
craw->SaveAs("RawElog.png");
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.pdf");
cmean->SaveAs("mean.png");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.pdf");
cwidth->SaveAs("width.png");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.pdf");
cn->SaveAs("n.png");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.pdf");
cn2->SaveAs("n2.png");
TCanvas *calpha = new TCanvas;
RooPlot *plotalpha = alphavar->frame(0.,5.,200);
hdataclone->plotOn(plotalpha);
plotalpha->Draw();
calpha->SaveAs("alpha.pdf");
calpha->SaveAs("alpha.png");
TCanvas *calpha2 = new TCanvas;
RooPlot *plotalpha2 = alpha2var->frame(0.,5.,200);
hdataclone->plotOn(plotalpha2);
plotalpha2->Draw();
calpha2->SaveAs("alpha2.pdf");
calpha2->SaveAs("alpha2.png");
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.pdf");
ceta->SaveAs("eta.png");
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw;// = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor;// = hdata->createHistogram("hecor",*ecorvar);
if (EEorEB == "EB")
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.8,1.1));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(800,0.8,1.1));
}
else
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(200,0.,2.));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(200,0.,2.));
}
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
heraw->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
hecor->GetXaxis()->SetRangeUser(0.0,1.5);
heraw->GetXaxis()->SetRangeUser(0.0,1.5);
/*if(EEorEB == "EE")
{
heraw->GetYaxis()->SetRangeUser(10.0,200.0);
hecor->GetYaxis()->SetRangeUser(10.0,200.0);
}
*/
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
double effsigma_cor, effsigma_raw, fwhm_cor, fwhm_raw;
if(EEorEB == "EB")
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
else
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
TCanvas *cresponse = new TCanvas;
gStyle->SetOptStat(0);
gStyle->SetPalette(107);
hecor->SetTitle("");
heraw->SetTitle("");
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
//show errSigma in the plot
TLegend *leg = new TLegend(0.1, 0.75, 0.7, 0.9);
leg->AddEntry(hecor,Form("E_{cor}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_cor, fwhm_cor),"l");
leg->AddEntry(heraw,Form("E_{raw}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_raw, fwhm_raw),"l");
leg->SetFillStyle(0);
leg->SetBorderSize(0);
// leg->SetTextColor(kRed);
leg->Draw();
cresponse->SaveAs("response.pdf");
cresponse->SaveAs("response.png");
cresponse->SetLogy();
cresponse->SaveAs("responselog.pdf");
cresponse->SaveAs("responselog.png");
// draw CCs vs eta and phi
TCanvas *c_eta = new TCanvas;
TH1 *h_eta = hdata->createHistogram("h_eta",*scetavar,Binning(100,-3.2,3.2));
h_eta->Draw("HIST");
c_eta->SaveAs("heta.pdf");
c_eta->SaveAs("heta.png");
TCanvas *c_phi = new TCanvas;
TH1 *h_phi = hdata->createHistogram("h_phi",*scphivar,Binning(100,-3.2,3.2));
h_phi->Draw("HIST");
c_phi->SaveAs("hphi.pdf");
c_phi->SaveAs("hphi.png");
RooRealVar *scetaiXvar = ws->var("var_6");
RooRealVar *scphiiYvar = ws->var("var_7");
if(EEorEB=="EB")
{
scetaiXvar->setRange(-90,90);
scetaiXvar->setBins(180);
scphiiYvar->setRange(0,360);
scphiiYvar->setBins(360);
}
else
{
scetaiXvar->setRange(0,50);
scetaiXvar->setBins(50);
scphiiYvar->setRange(0,50);
scphiiYvar->setBins(50);
}
ecorvar->setRange(0.5,1.5);
ecorvar->setBins(800);
rawvar->setRange(0.5,1.5);
rawvar->setBins(800);
TCanvas *c_cor_eta = new TCanvas;
TH2F *h_CC_eta = hdata->createHistogram(*scetaiXvar, *ecorvar, "","cor_vs_eta");
if(EEorEB=="EB")
{
h_CC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetXaxis()->SetTitle("iX");
}
h_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_eta->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta.pdf");
c_cor_eta->SaveAs("cor_vs_eta.png");
TCanvas *c_cor_phi = new TCanvas;
TH2F *h_CC_phi = hdata->createHistogram(*scphiiYvar, *ecorvar, "","cor_vs_phi");
if(EEorEB=="EB")
{
h_CC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetXaxis()->SetTitle("iY");
}
h_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_phi->Draw("COLZ");
c_cor_phi->SaveAs("cor_vs_phi.pdf");
c_cor_phi->SaveAs("cor_vs_phi.png");
TCanvas *c_raw_eta = new TCanvas;
TH2F *h_RC_eta = hdata->createHistogram(*scetaiXvar, *rawvar, "","raw_vs_eta");
if(EEorEB=="EB")
{
h_RC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_RC_eta->GetXaxis()->SetTitle("iX");
}
h_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_eta->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta.pdf");
c_raw_eta->SaveAs("raw_vs_eta.png");
TCanvas *c_raw_phi = new TCanvas;
TH2F *h_RC_phi = hdata->createHistogram(*scphiiYvar, *rawvar, "","raw_vs_phi");
if(EEorEB=="EB")
{
h_RC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_RC_phi->GetXaxis()->SetTitle("iY");
}
h_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_phi->Draw("COLZ");
c_raw_phi->SaveAs("raw_vs_phi.pdf");
c_raw_phi->SaveAs("raw_vs_phi.png");
//on2,5,20, etc
if(EEorEB == "EB")
{
TCanvas *myC_iCrystal_mod = new TCanvas;
RooRealVar *iEtaOn5var = ws->var("var_8");
iEtaOn5var->setRange(0,5);
iEtaOn5var->setBins(5);
TH2F *h_CC_iEtaOn5 = hdata->createHistogram(*iEtaOn5var, *ecorvar, "","cor_vs_iEtaOn5");
h_CC_iEtaOn5->GetXaxis()->SetTitle("iEtaOn5");
h_CC_iEtaOn5->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iEtaOn5->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn5.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn5.png");
TH2F *h_RC_iEtaOn5 = hdata->createHistogram(*iEtaOn5var, *rawvar, "","raw_vs_iEtaOn5");
h_RC_iEtaOn5->GetXaxis()->SetTitle("iEtaOn5");
h_RC_iEtaOn5->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iEtaOn5->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn5.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn5.png");
RooRealVar *iPhiOn2var = ws->var("var_9");
iPhiOn2var->setRange(0,2);
iPhiOn2var->setBins(2);
TH2F *h_CC_iPhiOn2 = hdata->createHistogram(*iPhiOn2var, *ecorvar, "","cor_vs_iPhiOn2");
h_CC_iPhiOn2->GetXaxis()->SetTitle("iPhiOn2");
h_CC_iPhiOn2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iPhiOn2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn2.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn2.png");
TH2F *h_RC_iPhiOn2 = hdata->createHistogram(*iPhiOn2var, *rawvar, "","raw_vs_iPhiOn2");
h_RC_iPhiOn2->GetXaxis()->SetTitle("iPhiOn2");
h_RC_iPhiOn2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iPhiOn2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn2.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn2.png");
RooRealVar *iPhiOn20var = ws->var("var_10");
iPhiOn20var->setRange(0,20);
iPhiOn20var->setBins(20);
TH2F *h_CC_iPhiOn20 = hdata->createHistogram(*iPhiOn20var, *ecorvar, "","cor_vs_iPhiOn20");
h_CC_iPhiOn20->GetXaxis()->SetTitle("iPhiOn20");
h_CC_iPhiOn20->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iPhiOn20->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn20.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn20.png");
TH2F *h_RC_iPhiOn20 = hdata->createHistogram(*iPhiOn20var, *rawvar, "","raw_vs_iPhiOn20");
h_RC_iPhiOn20->GetXaxis()->SetTitle("iPhiOn20");
h_RC_iPhiOn20->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iPhiOn20->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn20.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn20.png");
RooRealVar *iEtaOn2520var = ws->var("var_11");
iEtaOn2520var->setRange(-25,25);
iEtaOn2520var->setBins(50);
TH2F *h_CC_iEtaOn2520 = hdata->createHistogram(*iEtaOn2520var, *ecorvar, "","cor_vs_iEtaOn2520");
h_CC_iEtaOn2520->GetXaxis()->SetTitle("iEtaOn2520");
h_CC_iEtaOn2520->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iEtaOn2520->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn2520.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn2520.png");
TH2F *h_RC_iEtaOn2520 = hdata->createHistogram(*iEtaOn2520var, *rawvar, "","raw_vs_iEtaOn2520");
h_RC_iEtaOn2520->GetXaxis()->SetTitle("iEtaOn2520");
h_RC_iEtaOn2520->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iEtaOn2520->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn2520.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn2520.png");
}
// other variables
TCanvas *myC_variables = new TCanvas;
RooRealVar *Nxtalvar = ws->var("var_3");
Nxtalvar->setRange(0,10);
Nxtalvar->setBins(10);
TH2F *h_CC_Nxtal = hdata->createHistogram(*Nxtalvar, *ecorvar, "","cor_vs_Nxtal");
h_CC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_CC_Nxtal->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Nxtal.pdf");
myC_variables->SaveAs("cor_vs_Nxtal.png");
TH2F *h_RC_Nxtal = hdata->createHistogram(*Nxtalvar, *rawvar, "","raw_vs_Nxtal");
h_RC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_RC_Nxtal->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Nxtal.pdf");
myC_variables->SaveAs("raw_vs_Nxtal.png");
RooRealVar *S4S9var = ws->var("var_4");
int Nbins_S4S9 = 100;
double Low_S4S9 = 0.6;
double High_S4S9 = 1.0;
S4S9var->setRange(Low_S4S9,High_S4S9);
S4S9var->setBins(Nbins_S4S9);
TH2F *h_CC_S4S9 = hdata->createHistogram(*S4S9var, *ecorvar, "","cor_vs_S4S9");
h_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h_CC_S4S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S4S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S4S9.pdf");
myC_variables->SaveAs("cor_vs_S4S9.png");
TH2F *h_RC_S4S9 = hdata->createHistogram(*S4S9var, *rawvar, "","raw_vs_S4S9");
h_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h_RC_S4S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S4S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S4S9.pdf");
myC_variables->SaveAs("raw_vs_S4S9.png");
/*
RooRealVar *S1S9var = ws->var("var_5");
S1S9var->setRange(0.3,1.0);
S1S9var->setBins(100);
TH2F *h_CC_S1S9 = hdata->createHistogram(*S1S9var, *ecorvar, "","cor_vs_S1S9");
h_CC_S1S9->GetXaxis()->SetTitle("S1S9");
h_CC_S1S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S1S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S1S9.pdf");
TH2F *h_RC_S1S9 = hdata->createHistogram(*S1S9var, *rawvar, "","raw_vs_S1S9");
h_RC_S1S9->GetXaxis()->SetTitle("S1S9");
h_RC_S1S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S1S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S1S9.pdf");
*/
RooRealVar *S2S9var = ws->var("var_5");
int Nbins_S2S9 = 100;
double Low_S2S9 = 0.5;
double High_S2S9 = 1.0;
S2S9var->setRange(Low_S2S9,High_S2S9);
S2S9var->setBins(Nbins_S2S9);
TH2F *h_CC_S2S9 = hdata->createHistogram(*S2S9var, *ecorvar, "","cor_vs_S2S9");
h_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h_CC_S2S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S2S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S2S9.pdf");
myC_variables->SaveAs("cor_vs_S2S9.png");
TH2F *h_RC_S2S9 = hdata->createHistogram(*S2S9var, *rawvar, "","raw_vs_S2S9");
h_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h_RC_S2S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S2S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S2S9.pdf");
myC_variables->SaveAs("raw_vs_S2S9.png");
TH2F *h_S2S9_eta = hdata->createHistogram(*scetaiXvar, *S2S9var, "","S2S9_vs_eta");
h_S2S9_eta->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S2S9_eta->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_eta.pdf");
myC_variables->SaveAs("S2S9_vs_eta.png");
TH2F *h_S4S9_eta = hdata->createHistogram(*scetaiXvar, *S4S9var, "","S4S9_vs_eta");
h_S4S9_eta->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S4S9_eta->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_eta.pdf");
myC_variables->SaveAs("S4S9_vs_eta.png");
TH2F *h_S2S9_phi = hdata->createHistogram(*scphiiYvar, *S2S9var, "","S2S9_vs_phi");
h_S2S9_phi->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S2S9_phi->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_phi.pdf");
myC_variables->SaveAs("S2S9_vs_phi.png");
TH2F *h_S4S9_phi = hdata->createHistogram(*scphiiYvar, *S4S9var, "","S4S9_vs_phi");
h_S4S9_phi->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S4S9_phi->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_phi.pdf");
myC_variables->SaveAs("S4S9_vs_phi.png");
/*
RooRealVar *DeltaRvar = ws->var("var_6");
DeltaRvar->setRange(0.0,0.1);
DeltaRvar->setBins(100);
TH2F *h_CC_DeltaR = hdata->createHistogram(*DeltaRvar, *ecorvar, "","cor_vs_DeltaR");
h_CC_DeltaR->GetXaxis()->SetTitle("#Delta R");
h_CC_DeltaR->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_DeltaR->Draw("COLZ");
myC_variables->SaveAs("cor_vs_DeltaR.pdf");
myC_variables->SaveAs("cor_vs_DeltaR.png");
TH2F *h_RC_DeltaR = hdata->createHistogram(*DeltaRvar, *rawvar, "","raw_vs_DeltaR");
h_RC_DeltaR->GetXaxis()->SetTitle("#Delta R");
h_RC_DeltaR->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_DeltaR->Draw("COLZ");
myC_variables->SaveAs("raw_vs_DeltaR.pdf");
myC_variables->SaveAs("raw_vs_DeltaR.png");
*/
if(EEorEB=="EE")
{
/* RooRealVar *Es_e1var = ws->var("var_9");
Es_e1var->setRange(0.0,200.0);
Es_e1var->setBins(1000);
TH2F *h_CC_Es_e1 = hdata->createHistogram(*Es_e1var, *ecorvar, "","cor_vs_Es_e1");
h_CC_Es_e1->GetXaxis()->SetTitle("Es_e1");
h_CC_Es_e1->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Es_e1->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Es_e1.pdf");
myC_variables->SaveAs("cor_vs_Es_e1.png");
TH2F *h_RC_Es_e1 = hdata->createHistogram(*Es_e1var, *rawvar, "","raw_vs_Es_e1");
h_RC_Es_e1->GetXaxis()->SetTitle("Es_e1");
h_RC_Es_e1->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Es_e1->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Es_e1.pdf");
myC_variables->SaveAs("raw_vs_Es_e1.png");
RooRealVar *Es_e2var = ws->var("var_10");
Es_e2var->setRange(0.0,200.0);
Es_e2var->setBins(1000);
TH2F *h_CC_Es_e2 = hdata->createHistogram(*Es_e2var, *ecorvar, "","cor_vs_Es_e2");
h_CC_Es_e2->GetXaxis()->SetTitle("Es_e2");
h_CC_Es_e2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Es_e2->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Es_e2.pdf");
myC_variables->SaveAs("cor_vs_Es_e2.png");
TH2F *h_RC_Es_e2 = hdata->createHistogram(*Es_e2var, *rawvar, "","raw_vs_Es_e2");
h_RC_Es_e2->GetXaxis()->SetTitle("Es_e2");
h_RC_Es_e2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Es_e2->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Es_e2.pdf");
myC_variables->SaveAs("raw_vs_Es_e2.png");
*/
}
TProfile *p_CC_eta = h_CC_eta->ProfileX("p_CC_eta",1,-1,"s");
p_CC_eta->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB == "EB")
{
// p_CC_eta->GetYaxis()->SetRangeUser(0.85,1.0);
// p_CC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_eta->SetTitle("");
p_CC_eta->Draw();
myC_variables->SaveAs("profile_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_cor_vs_eta.png");
TProfile *p_RC_eta = h_RC_eta->ProfileX("p_RC_eta",1,-1,"s");
p_RC_eta->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB=="EB")
{
// p_RC_eta->GetYaxis()->SetRangeUser(0.80,0.95);
// p_RC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_eta->SetTitle("");
p_RC_eta->Draw();
myC_variables->SaveAs("profile_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_raw_vs_eta.png");
int Nbins_iEta = EEorEB=="EB" ? 180 : 50;
int nLow_iEta = EEorEB=="EB" ? -90 : 0;
int nHigh_iEta = EEorEB=="EB" ? 90 : 50;
TH1F *h1_RC_eta = new TH1F("h1_RC_eta","h1_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_RC_eta->SetBinContent(i,p_RC_eta->GetBinError(i));
}
h1_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_RC_eta->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_eta->SetTitle("");
h1_RC_eta->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.png");
TH1F *h1_CC_eta = new TH1F("h1_CC_eta","h1_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_CC_eta->SetBinContent(i,p_CC_eta->GetBinError(i));
}
h1_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_CC_eta->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_eta->SetTitle("");
h1_CC_eta->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.png");
TProfile *p_CC_phi = h_CC_phi->ProfileX("p_CC_phi",1,-1,"s");
p_CC_phi->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB == "EB")
{
// p_CC_phi->GetYaxis()->SetRangeUser(0.94,1.00);
}
p_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_phi->SetTitle("");
p_CC_phi->Draw();
myC_variables->SaveAs("profile_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_cor_vs_phi.png");
TProfile *p_RC_phi = h_RC_phi->ProfileX("p_RC_phi",1,-1,"s");
p_RC_phi->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB=="EB")
{
// p_RC_phi->GetYaxis()->SetRangeUser(0.89,0.95);
}
p_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_phi->SetTitle("");
p_RC_phi->Draw();
myC_variables->SaveAs("profile_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_raw_vs_phi.png");
int Nbins_iPhi = EEorEB=="EB" ? 360 : 50;
int nLow_iPhi = EEorEB=="EB" ? 0 : 0;
int nHigh_iPhi = EEorEB=="EB" ? 360 : 50;
TH1F *h1_RC_phi = new TH1F("h1_RC_phi","h1_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_RC_phi->SetBinContent(i,p_RC_phi->GetBinError(i));
}
h1_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_RC_phi->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_phi->SetTitle("");
h1_RC_phi->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.png");
TH1F *h1_CC_phi = new TH1F("h1_CC_phi","h1_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_CC_phi->SetBinContent(i,p_CC_phi->GetBinError(i));
}
h1_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_CC_phi->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_phi->SetTitle("");
h1_CC_phi->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.png");
// FWHM over sigma_eff vs. eta/phi
TH1F *h1_FoverS_RC_phi = new TH1F("h1_FoverS_RC_phi","h1_FoverS_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_CC_phi = new TH1F("h1_FoverS_CC_phi","h1_FoverS_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_RC_eta = new TH1F("h1_FoverS_RC_eta","h1_FoverS_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_eta = new TH1F("h1_FoverS_CC_eta","h1_FoverS_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_S2S9 = new TH1F("h1_FoverS_CC_S2S9","h1_FoverS_CC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_RC_S2S9 = new TH1F("h1_FoverS_RC_S2S9","h1_FoverS_RC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_CC_S4S9 = new TH1F("h1_FoverS_CC_S4S9","h1_FoverS_CC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
TH1F *h1_FoverS_RC_S4S9 = new TH1F("h1_FoverS_RC_S4S9","h1_FoverS_RC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
float FWHMoverSigmaEff = 0.0;
TH1F *h_tmp_rawvar = new TH1F("tmp_rawvar","tmp_rawvar",800,0.5,1.5);
TH1F *h_tmp_corvar = new TH1F("tmp_corvar","tmp_corvar",800,0.5,1.5);
for(int i=1;i<=Nbins_iPhi;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_phi->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_phi->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_phi->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_phi->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_CC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_phi->SetTitle("");
h1_FoverS_CC_phi->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.png");
h1_FoverS_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_RC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_phi->SetTitle("");
h1_FoverS_RC_phi->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.png");
for(int i=1;i<=Nbins_iEta;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_eta->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_eta->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_eta->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_eta->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_CC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_eta->SetTitle("");
h1_FoverS_CC_eta->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.png");
h1_FoverS_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_RC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_eta->SetTitle("");
h1_FoverS_RC_eta->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.png");
for(int i=1;i<=Nbins_S2S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S2S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S2S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_CC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S2S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S2S9->SetTitle("");
h1_FoverS_CC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.png");
h1_FoverS_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_RC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S2S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S2S9->SetTitle("");
h1_FoverS_RC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.png");
for(int i=1;i<=Nbins_S4S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S4S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S4S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_CC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S4S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S4S9->SetTitle("");
h1_FoverS_CC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.png");
h1_FoverS_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_RC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S4S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S4S9->SetTitle("");
h1_FoverS_RC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.png");
printf("calc effsigma\n");
std::cout<<"_"<<EEorEB<<std::endl;
printf("corrected curve effSigma= %5f, FWHM=%5f \n",effsigma_cor, fwhm_cor);
printf("raw curve effSigma= %5f FWHM=%5f \n",effsigma_raw, fwhm_raw);
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
}
void constrained_scan( const char* wsfile = "outputfiles/ws.root",
const char* new_poi_name="mu_bg_4b_msig_met1",
double constraintWidth=1.5,
int npoiPoints = 20,
double poiMinVal = 0.,
double poiMaxVal = 10.0,
double ymax = 9.,
int verbLevel=1 ) {
TString outputdir("outputfiles") ;
gStyle->SetOptStat(0) ;
TFile* wstf = new TFile( wsfile ) ;
RooWorkspace* ws = dynamic_cast<RooWorkspace*>( wstf->Get("ws") );
ws->Print() ;
RooDataSet* rds = (RooDataSet*) ws->obj( "hbb_observed_rds" ) ;
cout << "\n\n\n ===== RooDataSet ====================\n\n" << endl ;
rds->Print() ;
rds->printMultiline(cout, 1, kTRUE, "") ;
RooRealVar* rv_sig_strength = ws->var("sig_strength") ;
if ( rv_sig_strength == 0x0 ) { printf("\n\n *** can't find sig_strength in workspace.\n\n" ) ; return ; }
RooAbsPdf* likelihood = ws->pdf("likelihood") ;
if ( likelihood == 0x0 ) { printf("\n\n *** can't find likelihood in workspace.\n\n" ) ; return ; }
printf("\n\n Likelihood:\n") ;
likelihood -> Print() ;
/////rv_sig_strength -> setConstant( kFALSE ) ;
rv_sig_strength -> setVal(0.) ;
rv_sig_strength -> setConstant( kTRUE ) ;
likelihood->fitTo( *rds, Save(false), PrintLevel(0), Hesse(true), Strategy(1) ) ;
//RooFitResult* fitResult = likelihood->fitTo( *rds, Save(true), PrintLevel(0), Hesse(true), Strategy(1) ) ;
//double minNllSusyFloat = fitResult->minNll() ;
//double susy_ss_atMinNll = rv_sig_strength -> getVal() ;
RooMsgService::instance().getStream(1).removeTopic(Minimization) ;
RooMsgService::instance().getStream(1).removeTopic(Fitting) ;
//-- Construct the new POI parameter.
RooAbsReal* new_poi_rar(0x0) ;
new_poi_rar = ws->var( new_poi_name ) ;
if ( new_poi_rar == 0x0 ) {
printf("\n\n New POI %s is not a variable. Trying function.\n\n", new_poi_name ) ;
new_poi_rar = ws->function( new_poi_name ) ;
if ( new_poi_rar == 0x0 ) {
printf("\n\n New POI %s is not a function. I quit.\n\n", new_poi_name ) ;
return ;
} else {
printf("\n Found it.\n\n") ;
}
} else {
printf("\n\n New POI %s is a variable with current value %.1f.\n\n", new_poi_name, new_poi_rar->getVal() ) ;
}
double startPoiVal = new_poi_rar->getVal() ;
RooAbsReal* nll = likelihood -> createNLL( *rds, Verbose(true) ) ;
RooRealVar* rrv_poiValue = new RooRealVar( "poiValue", "poiValue", 0., -10000., 10000. ) ;
RooRealVar* rrv_constraintWidth = new RooRealVar("constraintWidth","constraintWidth", 0.1, 0.1, 1000. ) ;
rrv_constraintWidth -> setVal( constraintWidth ) ;
rrv_constraintWidth -> setConstant(kTRUE) ;
RooMinuit* rminuit( 0x0 ) ;
RooMinuit* rminuit_uc = new RooMinuit( *nll ) ;
rminuit_uc->setPrintLevel(verbLevel-1) ;
rminuit_uc->setNoWarn() ;
rminuit_uc->migrad() ;
rminuit_uc->hesse() ;
RooFitResult* rfr_uc = rminuit_uc->fit("mr") ;
double floatParInitVal[10000] ;
char floatParName[10000][100] ;
int nFloatParInitVal(0) ;
RooArgList ral_floats = rfr_uc->floatParsFinal() ;
TIterator* floatParIter = ral_floats.createIterator() ;
{
RooRealVar* par ;
while ( (par = (RooRealVar*) floatParIter->Next()) ) {
sprintf( floatParName[nFloatParInitVal], "%s", par->GetName() ) ;
floatParInitVal[nFloatParInitVal] = par->getVal() ;
nFloatParInitVal++ ;
}
}
printf("\n\n Unbiased best value for new POI %s is : %7.1f\n\n", new_poi_rar->GetName(), new_poi_rar->getVal() ) ;
double best_poi_val = new_poi_rar->getVal() ;
char minuit_formula[10000] ;
sprintf( minuit_formula, "%s+%s*(%s-%s)*(%s-%s)",
nll->GetName(),
rrv_constraintWidth->GetName(),
new_poi_rar->GetName(), rrv_poiValue->GetName(),
new_poi_rar->GetName(), rrv_poiValue->GetName()
) ;
printf("\n\n Creating new minuit variable with formula: %s\n\n", minuit_formula ) ;
RooFormulaVar* new_minuit_var = new RooFormulaVar("new_minuit_var", minuit_formula,
RooArgList( *nll,
*rrv_constraintWidth,
*new_poi_rar, *rrv_poiValue,
*new_poi_rar, *rrv_poiValue
) ) ;
printf("\n\n Current value is %.2f\n\n",
new_minuit_var->getVal() ) ;
rminuit = new RooMinuit( *new_minuit_var ) ;
RooAbsReal* plot_var = nll ;
printf("\n\n Current value is %.2f\n\n",
plot_var->getVal() ) ;
rminuit->setPrintLevel(verbLevel-1) ;
if ( verbLevel <=0 ) { rminuit->setNoWarn() ; }
if ( poiMinVal < 0. && poiMaxVal < 0. ) {
printf("\n\n Automatic determination of scan range.\n\n") ;
if ( startPoiVal <= 0. ) {
printf("\n\n *** POI starting value zero or negative %g. Quit.\n\n\n", startPoiVal ) ;
return ;
}
poiMinVal = startPoiVal - 3.5 * sqrt(startPoiVal) ;
poiMaxVal = startPoiVal + 6.0 * sqrt(startPoiVal) ;
if ( poiMinVal < 0. ) { poiMinVal = 0. ; }
printf(" Start val = %g. Scan range: %g to %g\n\n", startPoiVal, poiMinVal, poiMaxVal ) ;
}
//----------------------------------------------------------------------------------------------
double poiVals_scanDown[1000] ;
double nllVals_scanDown[1000] ;
//-- Do scan down from best value.
printf("\n\n +++++ Starting scan down from best value.\n\n") ;
double minNllVal(1.e9) ;
for ( int poivi=0; poivi < npoiPoints/2 ; poivi++ ) {
////double poiValue = poiMinVal + poivi*(poiMaxVal-poiMinVal)/(1.*(npoiPoints-1)) ;
double poiValue = best_poi_val - poivi*(best_poi_val-poiMinVal)/(1.*(npoiPoints/2-1)) ;
rrv_poiValue -> setVal( poiValue ) ;
rrv_poiValue -> setConstant( kTRUE ) ;
//+++++++++++++++++++++++++++++++++++
rminuit->migrad() ;
rminuit->hesse() ;
RooFitResult* rfr = rminuit->save() ;
//+++++++++++++++++++++++++++++++++++
if ( verbLevel > 0 ) { rfr->Print("v") ; }
float fit_minuit_var_val = rfr->minNll() ;
printf(" %02d : poi constraint = %.2f : allvars : MinuitVar, createNLL, PV, POI : %.5f %.5f %.5f %.5f\n",
poivi, rrv_poiValue->getVal(), fit_minuit_var_val, nll->getVal(), plot_var->getVal(), new_poi_rar->getVal() ) ;
cout << flush ;
poiVals_scanDown[poivi] = new_poi_rar->getVal() ;
nllVals_scanDown[poivi] = plot_var->getVal() ;
if ( nllVals_scanDown[poivi] < minNllVal ) { minNllVal = nllVals_scanDown[poivi] ; }
delete rfr ;
} // poivi
printf("\n\n +++++ Resetting floats to best fit values.\n\n") ;
for ( int pi=0; pi<nFloatParInitVal; pi++ ) {
RooRealVar* par = ws->var( floatParName[pi] ) ;
par->setVal( floatParInitVal[pi] ) ;
} // pi.
printf("\n\n +++++ Starting scan up from best value.\n\n") ;
//-- Now do scan up.
double poiVals_scanUp[1000] ;
double nllVals_scanUp[1000] ;
for ( int poivi=0; poivi < npoiPoints/2 ; poivi++ ) {
double poiValue = best_poi_val + poivi*(poiMaxVal-best_poi_val)/(1.*(npoiPoints/2-1)) ;
rrv_poiValue -> setVal( poiValue ) ;
rrv_poiValue -> setConstant( kTRUE ) ;
//+++++++++++++++++++++++++++++++++++
rminuit->migrad() ;
rminuit->hesse() ;
RooFitResult* rfr = rminuit->save() ;
//+++++++++++++++++++++++++++++++++++
if ( verbLevel > 0 ) { rfr->Print("v") ; }
float fit_minuit_var_val = rfr->minNll() ;
printf(" %02d : poi constraint = %.2f : allvars : MinuitVar, createNLL, PV, POI : %.5f %.5f %.5f %.5f\n",
poivi, rrv_poiValue->getVal(), fit_minuit_var_val, nll->getVal(), plot_var->getVal(), new_poi_rar->getVal() ) ;
cout << flush ;
poiVals_scanUp[poivi] = new_poi_rar->getVal() ;
nllVals_scanUp[poivi] = plot_var->getVal() ;
if ( nllVals_scanUp[poivi] < minNllVal ) { minNllVal = nllVals_scanUp[poivi] ; }
delete rfr ;
} // poivi
double poiVals[1000] ;
double nllVals[1000] ;
int pointCount(0) ;
for ( int pi=0; pi<npoiPoints/2; pi++ ) {
poiVals[pi] = poiVals_scanDown[(npoiPoints/2-1)-pi] ;
nllVals[pi] = nllVals_scanDown[(npoiPoints/2-1)-pi] ;
pointCount++ ;
}
for ( int pi=1; pi<npoiPoints/2; pi++ ) {
poiVals[pointCount] = poiVals_scanUp[pi] ;
nllVals[pointCount] = nllVals_scanUp[pi] ;
pointCount++ ;
}
npoiPoints = pointCount ;
printf("\n\n --- TGraph arrays:\n") ;
for ( int i=0; i<npoiPoints; i++ ) {
printf(" %2d : poi = %6.1f, nll = %g\n", i, poiVals[i], nllVals[i] ) ;
}
printf("\n\n") ;
double nllDiffVals[1000] ;
double poiAtMinlnL(-1.) ;
double poiAtMinusDelta2(-1.) ;
double poiAtPlusDelta2(-1.) ;
for ( int poivi=0; poivi < npoiPoints ; poivi++ ) {
nllDiffVals[poivi] = 2.*(nllVals[poivi] - minNllVal) ;
double poiValue = poiMinVal + poivi*(poiMaxVal-poiMinVal)/(1.*npoiPoints) ;
if ( nllDiffVals[poivi] < 0.01 ) { poiAtMinlnL = poiValue ; }
if ( poiAtMinusDelta2 < 0. && nllDiffVals[poivi] < 2.5 ) { poiAtMinusDelta2 = poiValue ; }
if ( poiAtMinlnL > 0. && poiAtPlusDelta2 < 0. && nllDiffVals[poivi] > 2.0 ) { poiAtPlusDelta2 = poiValue ; }
} // poivi
printf("\n\n Estimates for poi at delta ln L = -2, 0, +2: %g , %g , %g\n\n", poiAtMinusDelta2, poiAtMinlnL, poiAtPlusDelta2 ) ;
//--- Main canvas
TCanvas* cscan = (TCanvas*) gDirectory->FindObject("cscan") ;
if ( cscan == 0x0 ) {
printf("\n Creating canvas.\n\n") ;
cscan = new TCanvas("cscan","Delta nll") ;
}
char gname[1000] ;
TGraph* graph = new TGraph( npoiPoints, poiVals, nllDiffVals ) ;
sprintf( gname, "scan_%s", new_poi_name ) ;
graph->SetName( gname ) ;
double poiBest(-1.) ;
double poiMinus1stdv(-1.) ;
double poiPlus1stdv(-1.) ;
double poiMinus2stdv(-1.) ;
double poiPlus2stdv(-1.) ;
double twoDeltalnLMin(1e9) ;
int nscan(1000) ;
for ( int xi=0; xi<nscan; xi++ ) {
double x = poiVals[0] + xi*(poiVals[npoiPoints-1]-poiVals[0])/(nscan-1) ;
double twoDeltalnL = graph -> Eval( x, 0, "S" ) ;
if ( poiMinus1stdv < 0. && twoDeltalnL < 1.0 ) { poiMinus1stdv = x ; printf(" set m1 : %d, x=%g, 2dnll=%g\n", xi, x, twoDeltalnL) ;}
if ( poiMinus2stdv < 0. && twoDeltalnL < 4.0 ) { poiMinus2stdv = x ; printf(" set m2 : %d, x=%g, 2dnll=%g\n", xi, x, twoDeltalnL) ;}
if ( twoDeltalnL < twoDeltalnLMin ) { poiBest = x ; twoDeltalnLMin = twoDeltalnL ; }
if ( twoDeltalnLMin < 0.3 && poiPlus1stdv < 0. && twoDeltalnL > 1.0 ) { poiPlus1stdv = x ; printf(" set p1 : %d, x=%g, 2dnll=%g\n", xi, x, twoDeltalnL) ;}
if ( twoDeltalnLMin < 0.3 && poiPlus2stdv < 0. && twoDeltalnL > 4.0 ) { poiPlus2stdv = x ; printf(" set p2 : %d, x=%g, 2dnll=%g\n", xi, x, twoDeltalnL) ;}
if ( xi%100 == 0 ) { printf( " %4d : poi=%6.2f, 2DeltalnL = %6.2f\n", xi, x, twoDeltalnL ) ; }
}
printf("\n\n POI estimate : %g +%g -%g [%g,%g], two sigma errors: +%g -%g [%g,%g]\n\n",
poiBest,
(poiPlus1stdv-poiBest), (poiBest-poiMinus1stdv), poiMinus1stdv, poiPlus1stdv,
(poiPlus2stdv-poiBest), (poiBest-poiMinus2stdv), poiMinus2stdv, poiPlus2stdv
) ;
printf(" %s val,pm1sig,pm2sig: %7.2f %7.2f %7.2f %7.2f %7.2f\n",
new_poi_name, poiBest, (poiPlus1stdv-poiBest), (poiBest-poiMinus1stdv), (poiPlus2stdv-poiBest), (poiBest-poiMinus2stdv) ) ;
char htitle[1000] ;
sprintf(htitle, "%s profile likelihood scan: -2ln(L/Lm)", new_poi_name ) ;
TH1F* hscan = new TH1F("hscan", htitle, 10, poiMinVal, poiMaxVal ) ;
hscan->SetMinimum(0.) ;
hscan->SetMaximum(ymax) ;
hscan->DrawCopy() ;
graph->SetLineColor(4) ;
graph->SetLineWidth(3) ;
graph->Draw("CP") ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cscan->Update() ;
TLine* line = new TLine() ;
line->SetLineColor(2) ;
line->DrawLine(poiMinVal, 1., poiPlus1stdv, 1.) ;
line->DrawLine(poiMinus1stdv,0., poiMinus1stdv, 1.) ;
line->DrawLine(poiPlus1stdv ,0., poiPlus1stdv , 1.) ;
TText* text = new TText() ;
text->SetTextSize(0.04) ;
char tstring[1000] ;
sprintf( tstring, "%s = %.1f +%.1f -%.1f", new_poi_name, poiBest, (poiPlus1stdv-poiBest), (poiBest-poiMinus1stdv) ) ;
text -> DrawTextNDC( 0.15, 0.85, tstring ) ;
sprintf( tstring, "68%% interval [%.1f, %.1f]", poiMinus1stdv, poiPlus1stdv ) ;
text -> DrawTextNDC( 0.15, 0.78, tstring ) ;
char hname[1000] ;
sprintf( hname, "hscanout_%s", new_poi_name ) ;
TH1F* hsout = new TH1F( hname,"scan results",4,0.,4.) ;
double obsVal(-1.) ;
hsout->SetBinContent(1, obsVal ) ;
hsout->SetBinContent(2, poiPlus1stdv ) ;
hsout->SetBinContent(3, poiBest ) ;
hsout->SetBinContent(4, poiMinus1stdv ) ;
TAxis* xaxis = hsout->GetXaxis() ;
xaxis->SetBinLabel(1,"Observed val.") ;
xaxis->SetBinLabel(2,"Model+1sd") ;
xaxis->SetBinLabel(3,"Model") ;
xaxis->SetBinLabel(4,"Model-1sd") ;
char outrootfile[10000] ;
sprintf( outrootfile, "%s/scan-ff-%s.root", outputdir.Data(), new_poi_name ) ;
char outpdffile[10000] ;
sprintf( outpdffile, "%s/scan-ff-%s.pdf", outputdir.Data(), new_poi_name ) ;
cscan->Update() ; cscan->Draw() ;
printf("\n Saving %s\n", outpdffile ) ;
cscan->SaveAs( outpdffile ) ;
//--- save in root file
printf("\n Saving %s\n", outrootfile ) ;
TFile fout(outrootfile,"recreate") ;
graph->Write() ;
hsout->Write() ;
fout.Close() ;
delete ws ;
wstf->Close() ;
} // constrained_scan.
void ws_cls_hybrid1_ag( const char* wsfile = "output-files/expected-ws-lm9-2BL.root", bool isBgonlyStudy=false, double poiVal = 150.0, int nToys=100, bool makeTtree=true, int verbLevel=0 ) {
TTree* toytt(0x0) ;
TFile* ttfile(0x0) ;
int tt_gen_Nsig ;
int tt_gen_Nsb ;
int tt_gen_Nsig_sl ;
int tt_gen_Nsb_sl ;
int tt_gen_Nsig_ldp ;
int tt_gen_Nsb_ldp ;
int tt_gen_Nsig_ee ;
int tt_gen_Nsb_ee ;
int tt_gen_Nsig_mm ;
int tt_gen_Nsb_mm ;
double tt_testStat ;
double tt_dataTestStat ;
double tt_hypo_mu_susy_sig ;
char ttname[1000] ;
char tttitle[1000] ;
if ( makeTtree ) {
ttfile = gDirectory->GetFile() ;
if ( ttfile == 0x0 ) { printf("\n\n\n *** asked for a ttree but no open file???\n\n") ; return ; }
if ( isBgonlyStudy ) {
sprintf( ttname, "toytt_%.0f_bgo", poiVal ) ;
sprintf( tttitle, "Toy study for background only, mu_susy_sig = %.0f", poiVal ) ;
} else {
sprintf( ttname, "toytt_%.0f_spb", poiVal ) ;
sprintf( tttitle, "Toy study for signal+background, mu_susy_sig = %.0f", poiVal ) ;
}
printf("\n\n Creating TTree : %s : %s\n\n", ttname, tttitle ) ;
gDirectory->pwd() ;
gDirectory->ls() ;
toytt = new TTree( ttname, tttitle ) ;
gDirectory->ls() ;
toytt -> Branch( "gen_Nsig" , &tt_gen_Nsig , "gen_Nsig/I" ) ;
toytt -> Branch( "gen_Nsb" , &tt_gen_Nsb , "gen_Nsb/I" ) ;
toytt -> Branch( "gen_Nsig_sl" , &tt_gen_Nsig_sl , "gen_Nsig_sl/I" ) ;
toytt -> Branch( "gen_Nsb_sl" , &tt_gen_Nsb_sl , "gen_Nsb_sl/I" ) ;
toytt -> Branch( "gen_Nsig_ldp" , &tt_gen_Nsig_ldp , "gen_Nsig_ldp/I" ) ;
toytt -> Branch( "gen_Nsb_ldp" , &tt_gen_Nsb_ldp , "gen_Nsb_ldp/I" ) ;
toytt -> Branch( "gen_Nsig_ee" , &tt_gen_Nsig_ee , "gen_Nsig_ee/I" ) ;
toytt -> Branch( "gen_Nsb_ee" , &tt_gen_Nsb_ee , "gen_Nsb_ee/I" ) ;
toytt -> Branch( "gen_Nsig_mm" , &tt_gen_Nsig_mm , "gen_Nsig_mm/I" ) ;
toytt -> Branch( "gen_Nsb_mm" , &tt_gen_Nsb_mm , "gen_Nsb_mm/I" ) ;
toytt -> Branch( "testStat" , &tt_testStat , "testStat/D" ) ;
toytt -> Branch( "dataTestStat" , &tt_dataTestStat , "dataTestStat/D" ) ;
toytt -> Branch( "hypo_mu_susy_sig" , &tt_hypo_mu_susy_sig , "hypo_mu_susy_sig/D" ) ;
}
//--- Tell RooFit to shut up about anything less important than an ERROR.
RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR) ;
random_ng = new TRandom2(12345) ;
/// char sel[100] ;
/// if ( strstr( wsfile, "1BL" ) != 0 ) {
/// sprintf( sel, "1BL" ) ;
/// } else if ( strstr( wsfile, "2BL" ) != 0 ) {
/// sprintf( sel, "2BL" ) ;
/// } else if ( strstr( wsfile, "3B" ) != 0 ) {
/// sprintf( sel, "3B" ) ;
/// } else if ( strstr( wsfile, "1BT" ) != 0 ) {
/// sprintf( sel, "1BT" ) ;
/// } else if ( strstr( wsfile, "2BT" ) != 0 ) {
/// sprintf( sel, "2BT" ) ;
/// } else {
/// printf("\n\n\n *** can't figure out which selection this is. I quit.\n\n" ) ;
/// return ;
/// }
/// printf("\n\n selection is %s\n\n", sel ) ;
TFile* wstf = new TFile( wsfile ) ;
RooWorkspace* ws = dynamic_cast<RooWorkspace*>( wstf->Get("ws") );
ws->Print() ;
RooDataSet* rds = (RooDataSet*) ws->obj( "ra2b_observed_rds" ) ;
printf("\n\n\n ===== RooDataSet ====================\n\n") ;
rds->Print() ;
rds->printMultiline(cout, 1, kTRUE, "") ;
ModelConfig* modelConfig = (ModelConfig*) ws->obj( "SbModel" ) ;
RooAbsPdf* likelihood = modelConfig->GetPdf() ;
const RooArgSet* nuisanceParameters = modelConfig->GetNuisanceParameters() ;
RooRealVar* rrv_mu_susy_sig = ws->var("mu_susy_sig") ;
if ( rrv_mu_susy_sig == 0x0 ) {
printf("\n\n\n *** can't find mu_susy_sig in workspace. Quitting.\n\n\n") ;
return ;
}
//// printf("\n\n\n ===== Doing a fit ====================\n\n") ;
//// RooFitResult* preFitResult = likelihood->fitTo( *rds, Save(true) ) ;
//// const RooArgList preFitFloatVals = preFitResult->floatParsFinal() ;
//// {
//// TIterator* parIter = preFitFloatVals.createIterator() ;
//// while ( RooRealVar* par = (RooRealVar*) parIter->Next() ) {
//// printf(" %20s : %8.2f\n", par->GetName(), par->getVal() ) ;
//// }
//// }
//--- Get pointers to the model predictions of the observables.
rfv_n_sig = ws->function("n_sig") ;
rfv_n_sb = ws->function("n_sb") ;
rfv_n_sig_sl = ws->function("n_sig_sl") ;
rfv_n_sb_sl = ws->function("n_sb_sl") ;
rfv_n_sig_ldp = ws->function("n_sig_ldp") ;
rfv_n_sb_ldp = ws->function("n_sb_ldp") ;
rfv_n_sig_ee = ws->function("n_sig_ee") ;
rfv_n_sb_ee = ws->function("n_sb_ee") ;
rfv_n_sig_mm = ws->function("n_sig_mm") ;
rfv_n_sb_mm = ws->function("n_sb_mm") ;
if ( rfv_n_sig == 0x0 ) { printf("\n\n\n *** can't find n_sig in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sb == 0x0 ) { printf("\n\n\n *** can't find n_sb in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sig_sl == 0x0 ) { printf("\n\n\n *** can't find n_sig_sl in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sb_sl == 0x0 ) { printf("\n\n\n *** can't find n_sb_sl in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sig_ldp == 0x0 ) { printf("\n\n\n *** can't find n_sig_ldp in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sb_ldp == 0x0 ) { printf("\n\n\n *** can't find n_sb_ldp in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sig_ee == 0x0 ) { printf("\n\n\n *** can't find n_sig_ee in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sb_ee == 0x0 ) { printf("\n\n\n *** can't find n_sb_ee in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sig_mm == 0x0 ) { printf("\n\n\n *** can't find n_sig_mm in workspace. Quitting.\n\n\n") ; return ; }
if ( rfv_n_sb_mm == 0x0 ) { printf("\n\n\n *** can't find n_sb_mm in workspace. Quitting.\n\n\n") ; return ; }
//--- Get pointers to the observables.
const RooArgSet* dsras = rds->get() ;
TIterator* obsIter = dsras->createIterator() ;
while ( RooRealVar* obs = (RooRealVar*) obsIter->Next() ) {
if ( strcmp( obs->GetName(), "Nsig" ) == 0 ) { rrv_Nsig = obs ; }
if ( strcmp( obs->GetName(), "Nsb" ) == 0 ) { rrv_Nsb = obs ; }
if ( strcmp( obs->GetName(), "Nsig_sl" ) == 0 ) { rrv_Nsig_sl = obs ; }
if ( strcmp( obs->GetName(), "Nsb_sl" ) == 0 ) { rrv_Nsb_sl = obs ; }
if ( strcmp( obs->GetName(), "Nsig_ldp" ) == 0 ) { rrv_Nsig_ldp = obs ; }
if ( strcmp( obs->GetName(), "Nsb_ldp" ) == 0 ) { rrv_Nsb_ldp = obs ; }
if ( strcmp( obs->GetName(), "Nsig_ee" ) == 0 ) { rrv_Nsig_ee = obs ; }
if ( strcmp( obs->GetName(), "Nsb_ee" ) == 0 ) { rrv_Nsb_ee = obs ; }
if ( strcmp( obs->GetName(), "Nsig_mm" ) == 0 ) { rrv_Nsig_mm = obs ; }
if ( strcmp( obs->GetName(), "Nsb_mm" ) == 0 ) { rrv_Nsb_mm = obs ; }
}
if ( rrv_Nsig == 0x0 ) { printf("\n\n\n *** can't find Nsig in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsb == 0x0 ) { printf("\n\n\n *** can't find Nsb in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsig_sl == 0x0 ) { printf("\n\n\n *** can't find Nsig_sl in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsb_sl == 0x0 ) { printf("\n\n\n *** can't find Nsb_sl in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsig_ldp == 0x0 ) { printf("\n\n\n *** can't find Nsig_ldp in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsb_ldp == 0x0 ) { printf("\n\n\n *** can't find Nsb_ldp in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsig_ee == 0x0 ) { printf("\n\n\n *** can't find Nsig_ee in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsb_ee == 0x0 ) { printf("\n\n\n *** can't find Nsb_ee in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsig_mm == 0x0 ) { printf("\n\n\n *** can't find Nsig_mm in dataset. Quitting.\n\n\n") ; return ; }
if ( rrv_Nsb_mm == 0x0 ) { printf("\n\n\n *** can't find Nsb_mm in dataset. Quitting.\n\n\n") ; return ; }
printf("\n\n\n === Model values for observables\n\n") ;
printObservables() ;
//--- save the actual values of the observables.
saveObservables() ;
//--- evaluate the test stat on the data: fit with susy floating.
rrv_mu_susy_sig->setVal( poiVal ) ;
rrv_mu_susy_sig->setConstant( kTRUE ) ;
printf("\n\n\n ====== Fitting the data with susy fixed.\n\n") ;
RooFitResult* dataFitResultSusyFixed = likelihood->fitTo(*rds, Save(true));
int dataSusyFixedFitCovQual = dataFitResultSusyFixed->covQual() ;
if ( dataSusyFixedFitCovQual != 3 ) { printf("\n\n\n *** Failed fit! Cov qual %d. Quitting.\n\n", dataSusyFixedFitCovQual ) ; return ; }
double dataFitSusyFixedNll = dataFitResultSusyFixed->minNll() ;
rrv_mu_susy_sig->setVal( 0.0 ) ;
rrv_mu_susy_sig->setConstant( kFALSE ) ;
printf("\n\n\n ====== Fitting the data with susy floating.\n\n") ;
RooFitResult* dataFitResultSusyFloat = likelihood->fitTo(*rds, Save(true));
int dataSusyFloatFitCovQual = dataFitResultSusyFloat->covQual() ;
if ( dataSusyFloatFitCovQual != 3 ) { printf("\n\n\n *** Failed fit! Cov qual %d. Quitting.\n\n", dataSusyFloatFitCovQual ) ; return ; }
double dataFitSusyFloatNll = dataFitResultSusyFloat->minNll() ;
double dataTestStat = 2.*( dataFitSusyFixedNll - dataFitSusyFloatNll) ;
printf("\n\n\n Data value of test stat : %8.2f\n", dataTestStat ) ;
printf("\n\n\n === Nuisance parameters\n\n") ;
{
int npi(0) ;
TIterator* npIter = nuisanceParameters->createIterator() ;
while ( RooRealVar* np_rrv = (RooRealVar*) npIter->Next() ) {
np_initial_val[npi] = np_rrv->getVal() ; //--- I am assuming that the order of the NPs in the iterator does not change.
TString npname( np_rrv->GetName() ) ;
npname.ReplaceAll("_prim","") ;
RooAbsReal* np_rfv = ws->function( npname ) ;
TString pdfname( np_rrv->GetName() ) ;
pdfname.ReplaceAll("_prim","") ;
pdfname.Prepend("pdf_") ;
RooAbsPdf* np_pdf = ws->pdf( pdfname ) ;
if ( np_pdf == 0x0 ) { printf("\n\n *** Can't find nuisance parameter pdf with name %s.\n\n", pdfname.Data() ) ; }
if ( np_rfv != 0x0 ) {
printf(" %20s : %8.2f , %20s, %8.2f\n", np_rrv->GetName(), np_rrv->getVal(), np_rfv->GetName(), np_rfv->getVal() ) ;
} else {
printf(" %20s : %8.2f\n", np_rrv->GetName(), np_rrv->getVal() ) ;
}
npi++ ;
} // np_rrv iterator.
np_count = npi ;
}
tt_dataTestStat = dataTestStat ;
tt_hypo_mu_susy_sig = poiVal ;
printf("\n\n\n === Doing the toys\n\n") ;
int nToyOK(0) ;
int nToyWorseThanData(0) ;
for ( int ti=0; ti<nToys; ti++ ) {
printf("\n\n\n ======= Toy %4d\n\n\n", ti ) ;
//--- 1) pick values for the nuisance parameters from the PDFs and fix them.
{
TIterator* npIter = nuisanceParameters->createIterator() ;
while ( RooRealVar* np_rrv = (RooRealVar*) npIter->Next() ) {
TString pdfname( np_rrv->GetName() ) ;
pdfname.ReplaceAll("_prim","") ;
pdfname.Prepend("pdf_") ;
RooAbsPdf* np_pdf = ws->pdf( pdfname ) ;
if ( np_pdf == 0x0 ) { printf("\n\n *** Can't find nuisance parameter pdf with name %s.\n\n", pdfname.Data() ) ; return ; }
RooDataSet* nprds = np_pdf->generate( RooArgSet(*np_rrv) ,1) ;
const RooArgSet* npdsras = nprds->get() ;
TIterator* valIter = npdsras->createIterator() ;
RooRealVar* val = (RooRealVar*) valIter->Next() ;
//--- reset the value of the nuisance parameter and fix it for the toy model definition fit.
np_rrv->setVal( val->getVal() ) ;
np_rrv->setConstant( kTRUE ) ;
TString npname( np_rrv->GetName() ) ;
npname.ReplaceAll("_prim","") ;
RooAbsReal* np_rfv = ws->function( npname ) ;
if ( verbLevel > 0 ) {
if ( np_rfv != 0x0 ) {
printf(" %20s : %8.2f , %15s, %8.3f\n", val->GetName(), val->getVal(), np_rfv->GetName(), np_rfv->getVal() ) ;
} else if ( strstr( npname.Data(), "eff_sf" ) != 0 ) {
np_rfv = ws->function( "eff_sf_sig" ) ;
RooAbsReal* np_rfv2 = ws->function( "eff_sf_sb" ) ;
printf(" %20s : %8.2f , %15s, %8.3f , %15s, %8.3f\n", val->GetName(), val->getVal(), np_rfv->GetName(), np_rfv->getVal(), np_rfv2->GetName(), np_rfv2->getVal() ) ;
} else if ( strstr( npname.Data(), "sf_ll" ) != 0 ) {
np_rfv = ws->function( "sf_ee" ) ;
RooAbsReal* np_rfv2 = ws->function( "sf_mm" ) ;
printf(" %20s : %8.2f , %15s, %8.3f , %15s, %8.3f\n", val->GetName(), val->getVal(), np_rfv->GetName(), np_rfv->getVal(), np_rfv2->GetName(), np_rfv2->getVal() ) ;
} else {
printf(" %20s : %8.2f\n", val->GetName(), val->getVal() ) ;
}
}
delete nprds ;
} // np_rrv iterator
}
//--- 2) Fit the dataset with these values for the nuisance parameters.
if ( isBgonlyStudy ) {
//-- fit with susy yield fixed to zero.
rrv_mu_susy_sig -> setVal( 0. ) ;
if ( verbLevel > 0 ) { printf("\n Setting mu_susy_sig to zero.\n\n") ; }
} else {
//-- fit with susy yield fixed to predicted value.
rrv_mu_susy_sig -> setVal( poiVal ) ;
if ( verbLevel > 0 ) { printf("\n Setting mu_susy_sig to %8.1f.\n\n", poiVal) ; }
}
rrv_mu_susy_sig->setConstant( kTRUE ) ;
if ( verbLevel > 0 ) {
printf("\n\n") ;
printf(" Fitting with these values for the observables to define the model for toy generation.\n") ;
rds->printMultiline(cout, 1, kTRUE, "") ;
printf("\n\n") ;
}
RooFitResult* toyModelDefinitionFitResult(0x0) ;
if ( verbLevel < 2 ) {
toyModelDefinitionFitResult = likelihood->fitTo(*rds, Save(true), PrintLevel(-1));
} else {
toyModelDefinitionFitResult = likelihood->fitTo(*rds, Save(true));
}
int toyModelDefFitCovQual = toyModelDefinitionFitResult->covQual() ;
if ( verbLevel > 0 ) { printf("\n fit covariance matrix quality: %d\n\n", toyModelDefFitCovQual ) ; }
if ( toyModelDefFitCovQual != 3 ) {
printf("\n\n\n *** Bad toy model definition fit. Cov qual %d. Aborting this toy.\n\n\n", toyModelDefFitCovQual ) ;
continue ;
}
delete toyModelDefinitionFitResult ;
if ( verbLevel > 0 ) {
printf("\n\n\n === Model values for observables. These will be used to generate the toy dataset.\n\n") ;
printObservables() ;
}
//--- 3) Generate a new set of observables based on this model.
generateObservables() ;
printf("\n\n\n Generated dataset\n") ;
rds->Print() ;
rds->printMultiline(cout, 1, kTRUE, "") ;
//--- Apparently, I need to make a new RooDataSet... Resetting the
// values in the old one doesn't stick. If you do likelihood->fitTo(*rds), it
// uses the original values, not the reset ones, in the fit.
RooArgSet toyFitobservedParametersList ;
toyFitobservedParametersList.add( *rrv_Nsig ) ;
toyFitobservedParametersList.add( *rrv_Nsb ) ;
toyFitobservedParametersList.add( *rrv_Nsig_sl ) ;
toyFitobservedParametersList.add( *rrv_Nsb_sl ) ;
toyFitobservedParametersList.add( *rrv_Nsig_ldp ) ;
toyFitobservedParametersList.add( *rrv_Nsb_ldp ) ;
toyFitobservedParametersList.add( *rrv_Nsig_ee ) ;
toyFitobservedParametersList.add( *rrv_Nsb_ee ) ;
toyFitobservedParametersList.add( *rrv_Nsig_mm ) ;
toyFitobservedParametersList.add( *rrv_Nsb_mm ) ;
RooDataSet* toyFitdsObserved = new RooDataSet("toyfit_ra2b_observed_rds", "RA2b toy observed data values",
toyFitobservedParametersList ) ;
toyFitdsObserved->add( toyFitobservedParametersList ) ;
//--- 4) Reset and free the nuisance parameters.
{
if ( verbLevel > 0 ) { printf("\n\n") ; }
int npi(0) ;
TIterator* npIter = nuisanceParameters->createIterator() ;
while ( RooRealVar* np_rrv = (RooRealVar*) npIter->Next() ) {
np_rrv -> setVal( np_initial_val[npi] ) ; // assuming that the order in the iterator does not change.
np_rrv -> setConstant( kFALSE ) ;
npi++ ;
if ( verbLevel > 0 ) { printf(" reset %20s to %8.2f and freed it.\n", np_rrv->GetName() , np_rrv->getVal() ) ; }
} // np_rrv iterator.
if ( verbLevel > 0 ) { printf("\n\n") ; }
}
//--- 5a) Evaluate the test statistic: Fit with susy yield floating to get the absolute maximum log likelihood.
if ( verbLevel > 0 ) { printf("\n\n Evaluating the test statistic for this toy. Fitting with susy floating.\n\n") ; }
rrv_mu_susy_sig->setVal( 0.0 ) ;
rrv_mu_susy_sig->setConstant( kFALSE ) ;
if ( verbLevel > 0 ) {
printf("\n toy dataset\n\n") ;
toyFitdsObserved->printMultiline(cout, 1, kTRUE, "") ;
}
/////---- nfg. Need to create a new dataset ----------
/////RooFitResult* maxLikelihoodFitResult = likelihood->fitTo(*rds, Save(true), PrintLevel(-1));
/////RooFitResult* maxLikelihoodFitResult = likelihood->fitTo(*rds, Save(true));
/////--------------
RooFitResult* maxLikelihoodFitResult(0x0) ;
if ( verbLevel < 2 ) {
maxLikelihoodFitResult = likelihood->fitTo(*toyFitdsObserved, Save(true), PrintLevel(-1));
} else {
maxLikelihoodFitResult = likelihood->fitTo(*toyFitdsObserved, Save(true));
}
if ( verbLevel > 0 ) { printObservables() ; }
int mlFitCovQual = maxLikelihoodFitResult->covQual() ;
if ( verbLevel > 0 ) { printf("\n fit covariance matrix quality: %d , -log likelihood %f\n\n", mlFitCovQual, maxLikelihoodFitResult->minNll() ) ; }
if ( mlFitCovQual != 3 ) {
printf("\n\n\n *** Bad maximum likelihood fit (susy floating). Cov qual %d. Aborting this toy.\n\n\n", mlFitCovQual ) ;
continue ;
}
double maxL_susyFloat = maxLikelihoodFitResult->minNll() ;
double maxL_mu_susy_sig = rrv_mu_susy_sig->getVal() ;
delete maxLikelihoodFitResult ;
//--- 5b) Evaluate the test statistic: Fit with susy yield fixed to hypothesis value.
// This is only necessary if the maximum likelihood fit value of the susy yield
// is less than the hypothesis value (to get a one-sided limit).
double testStat(0.0) ;
double maxL_susyFixed(0.0) ;
if ( maxL_mu_susy_sig < poiVal ) {
if ( verbLevel > 0 ) { printf("\n\n Evaluating the test statistic for this toy. Fitting with susy fixed to %8.2f.\n\n", poiVal ) ; }
rrv_mu_susy_sig->setVal( poiVal ) ;
rrv_mu_susy_sig->setConstant( kTRUE ) ;
if ( verbLevel > 0 ) {
printf("\n toy dataset\n\n") ;
rds->printMultiline(cout, 1, kTRUE, "") ;
}
////--------- nfg. need to make a new dataset ---------------
////RooFitResult* susyFixedFitResult = likelihood->fitTo(*rds, Save(true), PrintLevel(-1));
////RooFitResult* susyFixedFitResult = likelihood->fitTo(*rds, Save(true));
////-----------------------------
RooFitResult* susyFixedFitResult(0x0) ;
if ( verbLevel < 2 ) {
susyFixedFitResult = likelihood->fitTo(*toyFitdsObserved, Save(true), PrintLevel(-1));
} else {
susyFixedFitResult = likelihood->fitTo(*toyFitdsObserved, Save(true));
}
if ( verbLevel > 0 ) { printObservables() ; }
int susyFixedFitCovQual = susyFixedFitResult->covQual() ;
if ( verbLevel > 0 ) { printf("\n fit covariance matrix quality: %d , -log likelihood %f\n\n", susyFixedFitCovQual, susyFixedFitResult->minNll() ) ; }
if ( susyFixedFitCovQual != 3 ) {
printf("\n\n\n *** Bad maximum likelihood fit (susy fixed). Cov qual %d. Aborting this toy.\n\n\n", susyFixedFitCovQual ) ;
continue ;
}
maxL_susyFixed = susyFixedFitResult->minNll() ;
testStat = 2. * (maxL_susyFixed - maxL_susyFloat) ;
delete susyFixedFitResult ;
} else {
if ( verbLevel > 0 ) { printf("\n\n Floating value of susy yield greater than hypo value (%8.2f > %8.2f). Setting test stat to zero.\n\n", maxL_mu_susy_sig, poiVal ) ; }
testStat = 0.0 ;
}
printf(" --- test stat for toy %4d : %8.2f\n", ti, testStat ) ;
nToyOK++ ;
if ( testStat > dataTestStat ) { nToyWorseThanData++ ; }
if ( makeTtree ) {
tt_testStat = testStat ;
tt_gen_Nsig = rrv_Nsig->getVal() ;
tt_gen_Nsb = rrv_Nsb->getVal() ;
tt_gen_Nsig_sl = rrv_Nsig_sl->getVal() ;
tt_gen_Nsb_sl = rrv_Nsb_sl->getVal() ;
tt_gen_Nsig_ldp = rrv_Nsig_ldp->getVal() ;
tt_gen_Nsb_ldp = rrv_Nsb_ldp->getVal() ;
tt_gen_Nsig_ee = rrv_Nsig_ee->getVal() ;
tt_gen_Nsb_ee = rrv_Nsb_ee->getVal() ;
tt_gen_Nsig_mm = rrv_Nsig_mm->getVal() ;
tt_gen_Nsb_mm = rrv_Nsb_mm->getVal() ;
toytt->Fill() ;
}
//--- *) reset things for the next toy.
resetObservables() ;
delete toyFitdsObserved ;
} // ti.
wstf->Close() ;
printf("\n\n\n") ;
if ( nToyOK == 0 ) { printf("\n\n\n *** All toys bad !?!?!\n\n\n") ; return ; }
double pValue = (1.0*nToyWorseThanData) / (1.0*nToyOK) ;
if ( isBgonlyStudy ) {
printf("\n\n\n p-value result, BG-only , poi=%3.0f : %4d / %4d = %6.3f\n\n\n\n", poiVal, nToyWorseThanData, nToyOK, pValue ) ;
} else {
printf("\n\n\n p-value result, S-plus-B, poi=%3.0f : %4d / %4d = %6.3f\n\n\n\n", poiVal, nToyWorseThanData, nToyOK, pValue ) ;
}
if ( makeTtree ) {
printf("\n\n Writing TTree : %s : %s\n\n", ttname, tttitle ) ;
ttfile->cd() ;
toytt->Write() ;
}
} // ws_cls_hybrid1
void check_fit_bias_sim(const int N=1, string infname="20140409_SimFits_M1850_DblMu0_AllCent/fracLogCBG_PbPbpol3_HI020_pol2_HI2040_pol2_HI40100_pppol2_rap16-24_pT3-30_centMult_Workspace.root")
{
RooMsgService::instance().setGlobalKillBelow(RooFit::WARNING);
TFile *inf = new TFile(infname.c_str(),"READ");
RooWorkspace *ws = (RooWorkspace*) inf->Get("workspace");
// ws->var("doubleRatio_HI020")->setConstant(true);
// ws->var("doubleRatio_HI2040")->setConstant(true);
// ws->var("doubleRatio_HI40100")->setConstant(true);
RooRealVar *Jpsi_Mass = ws->var("Jpsi_Mass");
RooCategory *sample = ws->cat("sample");
// TIter types(ws->cat("sample")->typeIterator());
// RooCatType * type;
// types.Reset();
RooDataSet * protoData = (RooDataSet*) ws->data("redDataSim");
RooDataSet * protoData_pp = (RooDataSet*) ws->data("data4");
RooDataSet * protoData_HI020 = (RooDataSet*) ws->data("data1");
RooDataSet * protoData_HI2040 = (RooDataSet*) ws->data("data2");
RooDataSet * protoData_HI40100 = (RooDataSet*) ws->data("data3");
// RooSimultaneous *model = (RooSimultaneous*) ws->pdf("sigMassPDFSim");
RooAbsPdf *model_pp = (RooAbsPdf*) ws->pdf("sigMassPDF_pp");
RooAbsPdf *model_HI020 = (RooAbsPdf*) ws->pdf("pdf_HI020");
RooAbsPdf *model_HI2040 = (RooAbsPdf*) ws->pdf("pdf_HI2040");
RooAbsPdf *model_HI40100 = (RooAbsPdf*) ws->pdf("pdf_HI40100");
// ws->var("sigma_pol")->setVal(0.0);
// ws->var("sigma_b")->setVal(0.0);
// ws->var("sigma_pol")->setConstant(true);
// ws->var("sigma_b")->setConstant(true);
// ws->var("sigma_fit_HI020")->setVal(0.0);
// ws->var("sigma_eff_HI020")->setVal(0.0);
// ws->var("sigma_fit_HI020")->setConstant(true);
// ws->var("sigma_eff_HI020")->setConstant(true);
// ws->var("sigma_fit_HI2040")->setVal(0.0);
// ws->var("sigma_eff_HI2040")->setVal(0.0);
// ws->var("sigma_fit_HI2040")->setConstant(true);
// ws->var("sigma_eff_HI2040")->setConstant(true);
// ws->var("sigma_fit_HI40100")->setVal(0.0);
// ws->var("sigma_eff_HI40100")->setVal(0.0);
// ws->var("sigma_fit_HI40100")->setConstant(true);
// ws->var("sigma_eff_HI40100")->setConstant(true);
RooPlot *frame = Jpsi_Mass->frame(Range("M2242"));
protoData->plotOn(frame, Cut("sample==sample::pp"));
protoData->plotOn(frame, Cut("sample==sample::HI020"), MarkerColor(kRed));
protoData->plotOn(frame, Cut("sample==sample::HI2040"), MarkerStyle(25), MarkerColor(kBlue));
protoData->plotOn(frame, Cut("sample==sample::HI40100"), MarkerStyle(24), MarkerColor(kGreen+2));
// model->plotOn(frame, Slice(*sample,"pp"), ProjWData(*sample,*protoData));
TCanvas *c0 = new TCanvas("c0","c0");
c0->cd();
frame->Draw();
// return;
// ws->pdf("sigMassPDF_M2242")->plotOn(frame,Range("M2242"));
// redData->plotOn(frame,MarkerStyle(24),MarkerColor(kRed),Range("M2242"));
// while ((type=(RooCatType*)types.Next())) {
// protoData =
// (RooDataSet*)ws->data(TString::Format("data_%s", type->GetName()));
// bkg = ws.pdf(TString::Format("expFunct_%s", type->GetName()));
// if ((*type) == "HI")
// N = Nhi;
// else
// N = Npp;
// RooDataSet * tmpData = bkg->generate(RooArgSet(*Jpsi_mass), N,
// RooFit::ProtoData(*protoData));
// osBkgData->append(*tmpData);
// delete tmpData;
// }
// double Nevents = ws->var("NJpsi_pp")->getVal()+ws->function("NPsiP_pp")->getVal()+ws->var("NBkg_pp")->getVal();
TH1F *h0_pp = new TH1F("h0_pp","h0_pp;R_{#psi}^{pp};Events",1200,-0.3,0.3);
TH1F *h1_pp = new TH1F("h1_pp","h1_pp;R_{#psi}^{pp};Events",1200,-0.3,0.3);
TH2F *h2_pp = new TH2F("h2_pp","h2_pp;R_{#psi}^{pp} (M1850);R_{#psi}^{pp} (M2242)",600,-0.3,0.3,600,-0.3,0.3);
h0_pp->Sumw2();
h1_pp->Sumw2();
h2_pp->Sumw2();
h1_pp->SetMarkerColor(2);
h1_pp->SetLineColor(2);
h0_pp->GetXaxis()->CenterTitle(true);
h1_pp->GetXaxis()->CenterTitle(true);
h2_pp->GetXaxis()->CenterTitle(true);
TH1F *h0_HI020 = new TH1F("h0_HI020","h0_HI020;#chi_{#psi}^{HI020};Events",5000,-1.0,4.0);
TH1F *h1_HI020 = new TH1F("h1_HI020","h1_HI020;#chi_{#psi}^{HI020};Events",5000,-1.0,4.0);
TH2F *h2_HI020 = new TH2F("h2_HI020","h2_HI020;#chi_{#psi}^{HI020} (M1850);#chi_{#psi}^{HI020} (M2242)",500,-1,4,500,-1,4);
h0_HI020->Sumw2();
h1_HI020->Sumw2();
h2_HI020->Sumw2();
h1_HI020->SetMarkerColor(2);
h1_HI020->SetLineColor(2);
h0_HI020->GetXaxis()->CenterTitle(true);
h1_HI020->GetXaxis()->CenterTitle(true);
h2_HI020->GetXaxis()->CenterTitle(true);
TH1F *h0_HI2040 = new TH1F("h0_HI2040","h0_HI2040;#chi_{#psi}^{HI2040};Events",5000,-1.0,4.0);
TH1F *h1_HI2040 = new TH1F("h1_HI2040","h1_HI2040;#chi_{#psi}^{HI2040};Events",5000,-1.0,4.0);
TH2F *h2_HI2040 = new TH2F("h2_HI2040","h2_HI2040;#chi_{#psi}^{HI2040} (M1850);#chi_{#psi}^{HI2040} (M2242)",500,-1,4,500,-1,4);
h0_HI2040->Sumw2();
h1_HI2040->Sumw2();
h2_HI2040->Sumw2();
h1_HI2040->SetMarkerColor(2);
h1_HI2040->SetLineColor(2);
h0_HI2040->GetXaxis()->CenterTitle(true);
h1_HI2040->GetXaxis()->CenterTitle(true);
h2_HI2040->GetXaxis()->CenterTitle(true);
TH1F *h0_HI40100 = new TH1F("h0_HI40100","h0_HI40100;#chi_{#psi}^{HI40100};Events",5000,-1.0,4.0);
TH1F *h1_HI40100 = new TH1F("h1_HI40100","h1_HI40100;#chi_{#psi}^{HI40100};Events",5000,-1.0,4.0);
TH2F *h2_HI40100 = new TH2F("h2_HI40100","h2_HI40100;#chi_{#psi}^{HI40100} (M1850);#chi_{#psi}^{HI40100} (M2242)",500,-1,4,500,-1,4);
h0_HI40100->Sumw2();
h1_HI40100->Sumw2();
h2_HI40100->Sumw2();
h1_HI40100->SetMarkerColor(2);
h1_HI40100->SetLineColor(2);
h0_HI40100->GetXaxis()->CenterTitle(true);
h1_HI40100->GetXaxis()->CenterTitle(true);
h2_HI40100->GetXaxis()->CenterTitle(true);
TH1F *h0_HI0100 = new TH1F("h0_HI0100","h0_HI0100;#chi_{#psi}^{HI0100};Events",5000,-1.0,4.0);
TH1F *h1_HI0100 = new TH1F("h1_HI0100","h1_HI0100;#chi_{#psi}^{HI0100};Events",5000,-1.0,4.0);
TH2F *h2_HI0100 = new TH2F("h2_HI0100","h2_HI0100;#chi_{#psi}^{HI0100} (M1850);#chi_{#psi}^{HI0100} (M2242)",500,-1,4,500,-1,4);
h0_HI0100->Sumw2();
h1_HI0100->Sumw2();
h2_HI0100->Sumw2();
h1_HI0100->SetMarkerColor(2);
h1_HI0100->SetLineColor(2);
h0_HI0100->GetXaxis()->CenterTitle(true);
h1_HI0100->GetXaxis()->CenterTitle(true);
h2_HI0100->GetXaxis()->CenterTitle(true);
Jpsi_Mass->setRange("signal",3.6,3.76);
Jpsi_Mass->setRange("M2045",2.0,4.5);
Jpsi_Mass->setRange("M2242",2.2,4.2);
RooFitResult *fitMall;
RooFitResult *fitM;
// RooFit cannot normalize Chebychev polynomials to a subrange (no analytic integral?)
// using normal polynomials instead
RooRealVar a("a","a",0.0);a.setConstant(false);
RooRealVar b("b","b",0.01);b.setConstant(false);
RooRealVar c("c","c",-0.005);c.setConstant(false);
// mid
// RooPolynomial bkg_pp("bkg_pp","bkg_pp",*Jpsi_Mass,RooArgSet(a,b,c));
// fwd
RooPolynomial bkg_pp("bkg_pp","bkg_pp",*Jpsi_Mass,RooArgSet(a));//,b,c));
RooRealVar a_HI020("a_HI020","a_HI020",0.0);a_HI020.setConstant(false);
RooRealVar b_HI020("b_HI020","b_HI020",0.01);b_HI020.setConstant(false);
RooRealVar c_HI020("c_HI020","c_HI020",-0.005);c_HI020.setConstant(false);
// mid
// RooPolynomial bkg_HI020("bkg_HI020","bkg_HI020",*Jpsi_Mass,RooArgSet(a_HI020));//,b_HI020,c_HI020));
// fwd
RooPolynomial bkg_HI020("bkg_HI020","bkg_HI020",*Jpsi_Mass,RooArgSet(a_HI020,b_HI020,c_HI020));
RooRealVar a_HI2040("a_HI2040","a_HI2040",0.0);a_HI2040.setConstant(false);
RooRealVar b_HI2040("b_HI2040","b_HI2040",0.01);b_HI2040.setConstant(false);
RooRealVar c_HI2040("c_HI2040","c_HI2040",-0.005);c_HI2040.setConstant(false);
// mid
// RooPolynomial bkg_HI2040("bkg_HI2040","bkg_HI2040",*Jpsi_Mass,RooArgSet(a_HI2040));//,b_HI2040,c_HI2040));
// fwd
RooPolynomial bkg_HI2040("bkg_HI2040","bkg_HI2040",*Jpsi_Mass,RooArgSet(a_HI2040,b_HI2040));//,c_HI2040));
RooRealVar a_HI40100("a_HI40100","a_HI40100",0.0);a_HI40100.setConstant(false);
RooRealVar b_HI40100("b_HI40100","b_HI40100",0.01);b_HI40100.setConstant(false);
RooRealVar c_HI40100("c_HI40100","c_HI40100",-0.005);c_HI40100.setConstant(false);
// mid
// a_HI40100.setConstant(true);
// RooPolynomial bkg_HI40100("bkg_HI40100","bkg_HI40100",*Jpsi_Mass,RooArgSet(a_HI40100));//,b_HI40100,c_HI40100));
// fwd
RooPolynomial bkg_HI40100("bkg_HI40100","bkg_HI40100",*Jpsi_Mass,RooArgSet(a_HI40100));//,b_HI40100,c_HI40100));
ws->import(bkg_pp);
ws->import(bkg_HI020);
ws->import(bkg_HI2040);
ws->import(bkg_HI40100);
ws->factory("SUM::sigMassPDF_pp_M2242(NJpsi_pp*sigCB1G2_HI,NPsiP_pp*sigCB1G2P_HI,NBkg_pp*bkg_pp)");
ws->factory("SUM::sigMassPDF_HI020_M2242(NJpsi_HI020*sigCB1G2_HI,NPsiP_HI020*sigCB1G2P_HI,NBkg_HI020*bkg_HI020)");
ws->factory("SUM::sigMassPDF_HI2040_M2242(NJpsi_HI2040*sigCB1G2_HI,NPsiP_HI2040*sigCB1G2P_HI,NBkg_HI2040*bkg_HI2040)");
ws->factory("SUM::sigMassPDF_HI40100_M2242(NJpsi_HI40100*sigCB1G2_HI,NPsiP_HI40100*sigCB1G2P_HI,NBkg_HI40100*bkg_HI40100)");
ws->factory("SIMUL::sigMassPDFSim_M2242(sample,HI020=sigMassPDF_HI020_M2242,HI2040=sigMassPDF_HI2040_M2242,HI40100=sigMassPDF_HI40100_M2242,pp=sigMassPDF_pp_M2242)");
RooDataSet *data[N];
RooDataSet *data_pp[N];
RooDataSet *data_HI020[N];
RooDataSet *data_HI2040[N];
RooDataSet *data_HI40100[N];
RooDataSet *redData;
for (int i=0;i<N;++i) {
cout << "Generating event " << i << "/" << N << endl;
// cout << "Generate N = " << Nevents << " events with R_{psi} = " << ws->var("fracP_pp")->getVal() << endl;
// data[i] = model->generateSimGlobal(*Jpsi_Mass,ProtoData(*protoData), Verbose(1));
data_pp[i] = model_pp->generate(*Jpsi_Mass, ProtoData(*protoData_pp),Verbose(0));
data_HI020[i] = model_HI020->generate(*Jpsi_Mass, ProtoData(*protoData_HI020),Verbose(0));
data_HI2040[i] = model_HI2040->generate(*Jpsi_Mass, ProtoData(*protoData_HI2040),Verbose(0));
data_HI40100[i] = model_HI40100->generate(*Jpsi_Mass, ProtoData(*protoData_HI40100),Verbose(0));
data[i] = new RooDataSet("data","data",RooArgSet(*Jpsi_Mass),Index(*sample),Import("HI020",*data_HI020[i]),Import("HI2040",*data_HI2040[i]),Import("HI40100",*data_HI40100[i]),Import("pp",*data_pp[i]));
}
RooPlot *frame2 = Jpsi_Mass->frame();
data_pp[0]->plotOn(frame2);
data[N-1]->plotOn(frame2, Cut("sample==sample::pp"),MarkerColor(kRed), MarkerStyle(24));
data[N-1]->plotOn(frame2, Cut("sample==sample::HI020"), MarkerColor(kRed));
data[N-1]->plotOn(frame2, Cut("sample==sample::HI2040"), MarkerStyle(25), MarkerColor(kBlue));
data[N-1]->plotOn(frame2, Cut("sample==sample::HI40100"), MarkerStyle(24), MarkerColor(kGreen+2));
// data[N-1]->plotOn(frame2, Cut("sample!=sample::pp"), MarkerColor(kRed));
// model->plotOn(frame, Slice(*sample,"pp"), ProjWData(*sample,*protoData));
TCanvas *c0a = new TCanvas("c0a","c0a");
c0a->cd();
frame2->Draw();
// return;
// cout << data->sumEntries() << endl;
for (int i=0;i<N;++i) {
cout << "Fitting event " << i << "/" << N << endl;
fitMall = ws->pdf("sigMassPDFSim")->fitTo(*data[i],Extended(1),Hesse(1),Save(1),NumCPU(8),PrintEvalErrors(-1),Verbose(0),PrintLevel(-1));
if (fitMall->statusCodeHistory(fitMall->numStatusHistory()-1) != 0) {i--; continue;}
// fitMall->Print("v");
// cout << "Fitted R_{psi} = " << ws->var("fracP_pp")->getVal() << " +/- " << ws->var("fracP_pp")->getPropagatedError(*fitMall) << endl;
double R1850_pp = ws->var("fracP_pp")->getVal();
double R1850_HI020 = ws->var("doubleRatio_HI020")->getVal();
double R1850_HI2040 = ws->var("doubleRatio_HI2040")->getVal();
double R1850_HI40100 = ws->var("doubleRatio_HI40100")->getVal();
double R1850_HI0100 = ws->function("doubleRatio_HI0100")->getVal();
h0_pp->Fill(R1850_pp);
h0_HI020->Fill(R1850_HI020);
h0_HI2040->Fill(R1850_HI2040);
h0_HI40100->Fill(R1850_HI40100);
h0_HI0100->Fill(R1850_HI0100);
redData = (RooDataSet*)data[i]->reduce("Jpsi_Mass>2.2&&Jpsi_Mass<4.2");
// cout << redData->sumEntries() << endl;
fitM = ws->pdf("sigMassPDFSim_M2242")->fitTo(*redData,Extended(1),Hesse(1),Save(1),NumCPU(8),PrintEvalErrors(-1),Verbose(0),PrintLevel(-1),Range("M2242"));
if (fitM->statusCodeHistory(fitM->numStatusHistory()-1) != 0) {i--; continue;}
// fitM->Print("v");
// cout << "Fit over M2242: R_{psi} = " << ws->var("fracP_pp")->getVal() << " +/- " << ws->var("fracP_pp")->getPropagatedError(*fitM) << endl;
// RooPlot *frame = Jpsi_Mass->frame(Range("M2242"));
// redData->plotOn(frame);
// ws->pdf("sigMassPDF_M2242")->plotOn(frame,Range("M2242"));
// redData->plotOn(frame,MarkerStyle(24),MarkerColor(kRed),Range("M2242"));
double R2242_pp = ws->var("fracP_pp")->getVal();
double R2242_HI020 = ws->var("doubleRatio_HI020")->getVal();
double R2242_HI2040 = ws->var("doubleRatio_HI2040")->getVal();
double R2242_HI40100 = ws->var("doubleRatio_HI40100")->getVal();
double R2242_HI0100 = ws->function("doubleRatio_HI0100")->getVal();
h1_pp->Fill(R2242_pp);
h1_HI020->Fill(R2242_HI020);
h1_HI2040->Fill(R2242_HI2040);
h1_HI40100->Fill(R2242_HI40100);
h1_HI0100->Fill(R2242_HI0100);
h2_pp->Fill(R1850_pp,R2242_pp);
h2_HI020->Fill(R1850_HI020,R2242_HI020);
h2_HI2040->Fill(R1850_HI2040,R2242_HI2040);
h2_HI40100->Fill(R1850_HI40100,R2242_HI40100);
h2_HI0100->Fill(R1850_HI0100,R2242_HI0100);
}
TCanvas *c1 = new TCanvas("c1","c1");
c1->Divide(2,2);
c1->cd(1);
h0_pp->Draw();
h1_pp->Draw("same");
c1->cd(2);
h0_HI020->Draw();
h1_HI020->Draw("same");
c1->cd(3);
h0_HI2040->Draw();
h1_HI2040->Draw("same");
c1->cd(4);
h0_HI40100->Draw();
h1_HI40100->Draw("same");
// frame->Draw();
cout << "pp" << endl;
cout << h0_pp->GetMean() << "\t" << h0_pp->GetRMS() << endl;
cout << h1_pp->GetMean() << "\t" << h1_pp->GetRMS() << endl;
cout << 1-(h0_pp->GetMean()/h1_pp->GetMean()) << endl;
cout << "HI020" << endl;
cout << h0_HI020->GetMean() << "\t" << h0_HI020->GetRMS() << endl;
cout << h1_HI020->GetMean() << "\t" << h1_HI020->GetRMS() << endl;
cout << 1-(h0_HI020->GetMean()/h1_HI020->GetMean()) << endl;
cout << "HI2040" << endl;
cout << h0_HI2040->GetMean() << "\t" << h0_HI2040->GetRMS() << endl;
cout << h1_HI2040->GetMean() << "\t" << h1_HI2040->GetRMS() << endl;
cout << 1-(h0_HI2040->GetMean()/h1_HI2040->GetMean()) << endl;
cout << "HI40100" << endl;
cout << h0_HI40100->GetMean() << "\t" << h0_HI40100->GetRMS() << endl;
cout << h1_HI40100->GetMean() << "\t" << h1_HI40100->GetRMS() << endl;
cout << 1-(h0_HI40100->GetMean()/h1_HI40100->GetMean()) << endl;
cout << "HI0100" << endl;
cout << h0_HI0100->GetMean() << "\t" << h0_HI0100->GetRMS() << endl;
cout << h1_HI0100->GetMean() << "\t" << h1_HI0100->GetRMS() << endl;
cout << 1-(h0_HI0100->GetMean()/h1_HI0100->GetMean()) << endl;
c1->SaveAs(Form("toy_fits_dblRatio_fwd_M1850_N%i.pdf",N));
TF1 *f3 = new TF1("f3","x",-0.5,3.0);
f3->SetLineWidth(1);
TCanvas *c2 = new TCanvas("c2","c2");
c2->Divide(2,2);
c2->cd(1);
h2_pp->Draw("colz");
f3->Draw("same");
c2->cd(2);
h2_HI020->Draw("colz");
f3->Draw("same");
c2->cd(3);
h2_HI2040->Draw("colz");
f3->Draw("same");
c2->cd(4);
h2_HI40100->Draw("colz");
f3->Draw("same");
TCanvas *c3 = new TCanvas("c3","c3");
c3->Divide(2,1);
c3->cd(1);
h0_HI0100->Draw();
h1_HI0100->Draw("same");
c3->cd(2);
h2_HI0100->Draw("colz");
f3->Draw("same");
TFile *outf = new TFile(Form("toy_fits_dblRatio_fwd_M1850_N%i.root",N),"RECREATE");
h0_pp->Write();
h1_pp->Write();
h2_pp->Write();
h0_HI020->Write();
h1_HI020->Write();
h2_HI020->Write();
h0_HI2040->Write();
h1_HI2040->Write();
h2_HI2040->Write();
h0_HI40100->Write();
h1_HI40100->Write();
h2_HI40100->Write();
h0_HI0100->Write();
h1_HI0100->Write();
h2_HI0100->Write();
outf->Close();
return;
}
void fitqual_plots( const char* wsfile = "outputfiles/ws.root", const char* plottitle="" ) {
TText* tt_title = new TText() ;
tt_title -> SetTextAlign(33) ;
gStyle -> SetOptStat(0) ;
gStyle -> SetLabelSize( 0.06, "y" ) ;
gStyle -> SetLabelSize( 0.08, "x" ) ;
gStyle -> SetLabelOffset( 0.010, "y" ) ;
gStyle -> SetLabelOffset( 0.010, "x" ) ;
gStyle -> SetTitleSize( 0.07, "y" ) ;
gStyle -> SetTitleSize( 0.05, "x" ) ;
gStyle -> SetTitleOffset( 1.50, "x" ) ;
gStyle -> SetTitleH( 0.07 ) ;
gStyle -> SetPadLeftMargin( 0.15 ) ;
gStyle -> SetPadBottomMargin( 0.15 ) ;
gStyle -> SetTitleX( 0.10 ) ;
gDirectory->Delete("h*") ;
TFile* wstf = new TFile( wsfile ) ;
RooWorkspace* ws = dynamic_cast<RooWorkspace*>( wstf->Get("ws") );
ws->Print() ;
int bins_of_met = TMath::Nint( ws->var("bins_of_met")->getVal() ) ;
printf("\n\n Bins of MET : %d\n\n", bins_of_met ) ;
int bins_of_nb = TMath::Nint( ws->var("bins_of_nb")->getVal() ) ;
printf("\n\n Bins of nb : %d\n\n", bins_of_nb ) ;
int nb_lookup[10] ;
if ( bins_of_nb == 2 ) {
nb_lookup[0] = 2 ;
nb_lookup[1] = 4 ;
} else if ( bins_of_nb == 3 ) {
nb_lookup[0] = 2 ;
nb_lookup[1] = 3 ;
nb_lookup[2] = 4 ;
}
TCanvas* cfq1 = (TCanvas*) gDirectory->FindObject("cfq1") ;
if ( cfq1 == 0x0 ) {
if ( bins_of_nb == 3 ) {
cfq1 = new TCanvas("cfq1","hbb fit", 700, 1000 ) ;
} else if ( bins_of_nb == 2 ) {
cfq1 = new TCanvas("cfq1","hbb fit", 700, 750 ) ;
} else {
return ;
}
}
RooRealVar* rv_sig_strength = ws->var("sig_strength") ;
if ( rv_sig_strength == 0x0 ) { printf("\n\n *** can't find sig_strength in workspace.\n\n" ) ; return ; }
ModelConfig* modelConfig = (ModelConfig*) ws->obj( "SbModel" ) ;
RooDataSet* rds = (RooDataSet*) ws->obj( "hbb_observed_rds" ) ;
rds->Print() ;
rds->printMultiline(cout, 1, kTRUE, "") ;
RooAbsPdf* likelihood = modelConfig->GetPdf() ;
///RooFitResult* fitResult = likelihood->fitTo( *rds, Save(true), PrintLevel(0) ) ;
RooFitResult* fitResult = likelihood->fitTo( *rds, Save(true), PrintLevel(3) ) ;
fitResult->Print() ;
char hname[1000] ;
char htitle[1000] ;
char pname[1000] ;
//-- unpack observables.
int obs_N_msig[10][50] ; // first index is n btags, second is met bin.
int obs_N_msb[10][50] ; // first index is n btags, second is met bin.
const RooArgSet* dsras = rds->get() ;
TIterator* obsIter = dsras->createIterator() ;
while ( RooRealVar* obs = (RooRealVar*) obsIter->Next() ) {
for ( int nbi=0; nbi<bins_of_nb; nbi++ ) {
for ( int mbi=0; mbi<bins_of_met; mbi++ ) {
sprintf( pname, "N_%db_msig_met%d", nb_lookup[nbi], mbi+1 ) ;
if ( strcmp( obs->GetName(), pname ) == 0 ) { obs_N_msig[nbi][mbi] = TMath::Nint( obs -> getVal() ) ; }
sprintf( pname, "N_%db_msb_met%d", nb_lookup[nbi], mbi+1 ) ;
if ( strcmp( obs->GetName(), pname ) == 0 ) { obs_N_msb[nbi][mbi] = TMath::Nint( obs -> getVal() ) ; }
} // mbi.
} // nbi.
} // obs iterator.
printf("\n\n") ;
for ( int nbi=0; nbi<bins_of_nb; nbi++ ) {
printf(" nb=%d : ", nb_lookup[nbi] ) ;
for ( int mbi=0; mbi<bins_of_met; mbi++ ) {
printf(" sig=%3d, sb=%3d |", obs_N_msig[nbi][mbi], obs_N_msb[nbi][mbi] ) ;
} // mbi.
printf("\n") ;
} // nbi.
printf("\n\n") ;
int pad(1) ;
cfq1->Clear() ;
cfq1->Divide( 2, bins_of_nb+1 ) ;
for ( int nbi=0; nbi<bins_of_nb; nbi++ ) {
sprintf( hname, "h_bg_%db_msig_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sig, %db, MET", nb_lookup[nbi] ) ;
TH1F* hist_bg_msig = new TH1F( hname, htitle, bins_of_met, 0.5, bins_of_met+0.5 ) ;
hist_bg_msig -> SetFillColor( kBlue-9 ) ;
labelBins( hist_bg_msig ) ;
sprintf( hname, "h_bg_%db_msb_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sb, %db, MET", nb_lookup[nbi] ) ;
TH1F* hist_bg_msb = new TH1F( hname, htitle, bins_of_met, 0.5, bins_of_met+0.5 ) ;
hist_bg_msb -> SetFillColor( kBlue-9 ) ;
labelBins( hist_bg_msb ) ;
sprintf( hname, "h_sig_%db_msig_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sig, %db, MET", nb_lookup[nbi] ) ;
TH1F* hist_sig_msig = new TH1F( hname, htitle, bins_of_met, 0.5, bins_of_met+0.5 ) ;
hist_sig_msig -> SetFillColor( kMagenta+2 ) ;
labelBins( hist_sig_msig ) ;
sprintf( hname, "h_sig_%db_msb_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sb, %db, MET", nb_lookup[nbi] ) ;
TH1F* hist_sig_msb = new TH1F( hname, htitle, bins_of_met, 0.5, bins_of_met+0.5 ) ;
hist_sig_msb -> SetFillColor( kMagenta+2 ) ;
labelBins( hist_sig_msb ) ;
sprintf( hname, "h_all_%db_msig_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sig, %db, MET", nb_lookup[nbi] ) ;
TH1F* hist_all_msig = new TH1F( hname, htitle, bins_of_met, 0.5, bins_of_met+0.5 ) ;
sprintf( hname, "h_all_%db_msb_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sb, %db, MET", nb_lookup[nbi] ) ;
TH1F* hist_all_msb = new TH1F( hname, htitle, bins_of_met, 0.5, bins_of_met+0.5 ) ;
sprintf( hname, "h_data_%db_msig_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sig, %db, MET", nb_lookup[nbi] ) ;
TH1F* hist_data_msig = new TH1F( hname, htitle, bins_of_met, 0.5, bins_of_met+0.5 ) ;
hist_data_msig -> SetLineWidth(2) ;
hist_data_msig -> SetMarkerStyle(20) ;
labelBins( hist_data_msig ) ;
sprintf( hname, "h_data_%db_msb_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sb, %db, MET", nb_lookup[nbi] ) ;
TH1F* hist_data_msb = new TH1F( hname, htitle, bins_of_met, 0.5, bins_of_met+0.5 ) ;
hist_data_msb -> SetLineWidth(2) ;
hist_data_msb -> SetMarkerStyle(20) ;
labelBins( hist_data_msb ) ;
for ( int mbi=0; mbi<bins_of_met; mbi++ ) {
sprintf( pname, "mu_bg_%db_msig_met%d", nb_lookup[nbi], mbi+1 ) ;
RooAbsReal* mu_bg_msig = ws->function( pname ) ;
if ( mu_bg_msig == 0x0 ) { printf("\n\n *** ws missing %s\n\n", pname ) ; return ; }
hist_bg_msig -> SetBinContent( mbi+1, mu_bg_msig->getVal() ) ;
sprintf( pname, "mu_sig_%db_msig_met%d", nb_lookup[nbi], mbi+1 ) ;
RooAbsReal* mu_sig_msig = ws->function( pname ) ;
if ( mu_sig_msig == 0x0 ) { printf("\n\n *** ws missing %s\n\n", pname ) ; return ; }
hist_sig_msig -> SetBinContent( mbi+1, mu_sig_msig->getVal() ) ;
hist_all_msig -> SetBinContent( mbi+1, mu_bg_msig->getVal() + mu_sig_msig->getVal() ) ;
hist_data_msig -> SetBinContent( mbi+1, obs_N_msig[nbi][mbi] ) ;
sprintf( pname, "mu_bg_%db_msb_met%d", nb_lookup[nbi], mbi+1 ) ;
RooAbsReal* mu_bg_msb = ws->function( pname ) ;
if ( mu_bg_msb == 0x0 ) { printf("\n\n *** ws missing %s\n\n", pname ) ; return ; }
hist_bg_msb -> SetBinContent( mbi+1, mu_bg_msb->getVal() ) ;
sprintf( pname, "mu_sig_%db_msb_met%d", nb_lookup[nbi], mbi+1 ) ;
RooAbsReal* mu_sig_msb = ws->function( pname ) ;
if ( mu_sig_msb == 0x0 ) { printf("\n\n *** ws missing %s\n\n", pname ) ; return ; }
hist_sig_msb -> SetBinContent( mbi+1, mu_sig_msb->getVal() ) ;
hist_all_msb -> SetBinContent( mbi+1, mu_bg_msb->getVal() + mu_sig_msb->getVal() ) ;
hist_data_msb -> SetBinContent( mbi+1, obs_N_msb[nbi][mbi] ) ;
} // mbi.
cfq1->cd( pad ) ;
sprintf( hname, "h_stack_%db_msig_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sig, %db, MET", nb_lookup[nbi] ) ;
THStack* hstack_msig = new THStack( hname, htitle ) ;
hstack_msig -> Add( hist_bg_msig ) ;
hstack_msig -> Add( hist_sig_msig ) ;
hist_data_msig -> Draw("e") ;
hstack_msig -> Draw("same") ;
hist_data_msig -> Draw("same e") ;
hist_data_msig -> Draw("same axis") ;
tt_title -> DrawTextNDC( 0.85, 0.85, plottitle ) ;
pad++ ;
cfq1->cd( pad ) ;
sprintf( hname, "h_stack_%db_msb_met", nb_lookup[nbi] ) ;
sprintf( htitle, "mass sig, %db, MET", nb_lookup[nbi] ) ;
THStack* hstack_msb = new THStack( hname, htitle ) ;
hstack_msb -> Add( hist_bg_msb ) ;
hstack_msb -> Add( hist_sig_msb ) ;
hist_data_msb -> Draw("e") ;
hstack_msb -> Draw("same") ;
hist_data_msb -> Draw("same e") ;
hist_data_msb -> Draw("same axis") ;
tt_title -> DrawTextNDC( 0.85, 0.85, plottitle ) ;
pad++ ;
} // nbi.
TH1F* hist_R_msigmsb = new TH1F( "h_R_msigmsb", "R msig/msb vs met bin", bins_of_met, 0.5, 0.5+bins_of_met ) ;
hist_R_msigmsb -> SetLineWidth(2) ;
hist_R_msigmsb -> SetMarkerStyle(20) ;
hist_R_msigmsb -> SetYTitle("R msig/msb") ;
labelBins( hist_R_msigmsb ) ;
for ( int mbi=0; mbi<bins_of_met; mbi++ ) {
sprintf( pname, "R_msigmsb_met%d", mbi+1 ) ;
RooRealVar* rrv_R = ws->var( pname ) ;
if ( rrv_R == 0x0 ) { printf("\n\n *** Can't find %s in ws.\n\n", pname ) ; return ; }
hist_R_msigmsb -> SetBinContent( mbi+1, rrv_R -> getVal() ) ;
hist_R_msigmsb -> SetBinError( mbi+1, rrv_R -> getError() ) ;
} // mbi.
cfq1->cd( pad ) ;
gPad->SetGridy(1) ;
hist_R_msigmsb -> SetMaximum(0.35) ;
hist_R_msigmsb -> Draw("e") ;
tt_title -> DrawTextNDC( 0.85, 0.85, plottitle ) ;
pad++ ;
cfq1->cd( pad ) ;
scan_sigstrength( wsfile ) ;
tt_title -> DrawTextNDC( 0.85, 0.25, plottitle ) ;
TString pdffile( wsfile ) ;
pdffile.ReplaceAll("ws-","fitqual-") ;
pdffile.ReplaceAll("root","pdf") ;
cfq1->SaveAs( pdffile ) ;
TString histfile( wsfile ) ;
histfile.ReplaceAll("ws-","fitqual-") ;
saveHist( histfile, "h*" ) ;
} // fitqual_plots
void buildModel(int sel_i, TFile *fin, TDirectory *fout){
// Define outputs
RooWorkspace *wout = new RooWorkspace();
wout->SetName(Form("normalization_cat%d",sel_i));
fout->cd();
// Input to this is TTrees
// Setup the "x" variable and weights
RooRealVar mvamet("metRaw","metRaw",200,1200);
//RooRealVar mvamet("jet1mprune","jet1mprune",0,200);
//RooRealVar mvamet("jet1tau2o1","jet1tau2o1",0,1);
wout->import(mvamet);
// TH1F Base Style
std::string lName = "basehist";
//const int numberofBins = 18;
//double myBins[numberofBins+1] = {200,210,220,230,240,250,260,270,280,290,300,310,320,330,350,380,430,500,1200};
//TH1F *lMet = new TH1F(lName.c_str(),lName.c_str(),numberofBins,myBins);
TH1F *lMet = new TH1F(lName.c_str(),lName.c_str(),20,200,1200);
//TH1F *lMet = new TH1F(lName.c_str(),lName.c_str(),20,0,1);
// Make Datasets
makeAndImportDataSets(fin,wout,mvamet);
// ==========================================================================================================
const int nProcs = 27;
std::string procnames[nProcs];
procnames[0] = "DY";
procnames[1] = "RDY";
procnames[2] = "W";
procnames[3] = "WHT";
procnames[4] = "TT";
procnames[5] = "T";
procnames[6] = "ZZ";
procnames[7] = "WW";
procnames[8] = "WZ";
procnames[9] = "WH0";
procnames[10] = "ZH0";
procnames[11] = "GGH0";
procnames[12] = "VBFH0";
//procnames[12] = "DY_control_bkg_mc";
procnames[13] = "Zvv_control_mc";
procnames[14] = "T_control_bkg_mc";
procnames[15] = "TT_control_bkg_mc";
procnames[16] = "WW_control_bkg_mc";
procnames[17] = "WZ_control_bkg_mc";
procnames[18] = "ZZ_control_bkg_mc";
procnames[19] = "Wlv_control_mc_1";
procnames[20] = "Wlv_control_mc_2";
procnames[21] = "T_sl_control_bkg_mc";
procnames[22] = "TT_sl_control_bkg_mc";
procnames[23] = "WW_sl_control_bkg_mc";
procnames[24] = "WZ_sl_control_bkg_mc";
procnames[25] = "ZZ_sl_control_bkg_mc";
procnames[26] = "DY_sl_control_bkg_mc";
// Fill TF1s which do not need corrections
for (int p0=0;p0<nProcs;p0++){
std::cout << "Filling hist for " << procnames[p0] << std::endl;;
TH1F *hist_ = (TH1F*)generateTemplate(lMet, (TTree*)fin->Get(procnames[p0].c_str()), mvamet.GetName(), "weight",cutstring); // standard processes are TTrees
hist_->Write();
}
std::cout << "Filling hist for " << "data_obs" << std::endl;;
TH1F *hist_ = (TH1F*)generateTemplate(lMet, (TTree*)fin->Get("data_obs"), mvamet.GetName(), "",cutstring); // standard processes are TTrees
hist_->Write();
std::cout << "Filling hist for " << "Zvv_control" << std::endl;;
hist_ = (TH1F*)generateTemplate(lMet, (TTree*)fin->Get("Zvv_control"), mvamet.GetName(), "",cutstring); // standard processes are TTrees
hist_->Write();
std::cout << "Filling hist for " << "Wlv_control" << std::endl;;
hist_ = (TH1F*)generateTemplate(lMet, (TTree*)fin->Get("Wlv_control"), mvamet.GetName(), "",cutstring); // standard processes are TTrees
hist_->Write();
// ==========================================================================================================
// Fit backgrounds to produce fit model
#ifdef RUN_CORRECTION
buildAndFitModels(fout,wout,mvamet,"Zvv");
buildAndFitModels(fout,wout,mvamet,"Wlv");
double mcyield = wout->data("DY")->sumEntries();
double datayield = wout->var("num_Zvv")->getVal(); // post fit number of data Z->mumu in control
std::cout << "sfactor" << brscaleFactorZvv*datayield/mcyield << std::endl;
TH1F *hist_zvv = (TH1F*)generateTemplate(lMet, (RooFormulaVar*)wout->function("ratio_Zvv") , *(wout->var(mvamet.GetName())), (RooDataSet*) wout->data("DY")
//TH1F *hist_zvv = (TH1F*)generateTemplate(lMet, (RooFormulaVar*)wout->function("") , *(wout->var(mvamet.GetName())), (RooDataSet*) wout->data("DY")
, 1 /*run correction*/
, 1 /*brscaleFactorZvv*datayield/mcyield*/ /*additional weight*/);
hist_zvv->Write();
std::cout << " DataCardInfo ---------------- " << std::endl;
std::cout << Form(" Zvv_norm gmN %d %g ",(int)datayield,hist_zvv->Integral()/datayield) << std::endl;
std::cout << " ----------------------------- " << std::endl;
// Also correct normalization data why not?
hist_zvv = (TH1F*)generateTemplate(lMet, (RooFormulaVar*)wout->function("ratio_Zvv") , *(wout->var(mvamet.GetName())), (RooDataSet*) wout->data("Zvv_control_mc")
, 1 /*run correction*/
, 1. /*additional weight*/);
hist_zvv->Write();
// Single muon
mcyield = wout->data("W")->sumEntries();
datayield = wout->var("num_Wlv")->getVal(); // post fit number of data W->munu in control
std::cout << "sfactor" << brscaleFactorWlv*datayield/mcyield << std::endl;
TH1F *hist_wlv = (TH1F*)generateTemplate(lMet, (RooFormulaVar*)wout->function("ratio_Wlv") , *(wout->var(mvamet.GetName())), (RooDataSet*) wout->data("W")
, 1 /*run correction*/
, 1./*brscaleFactorWlv*datayield/mcyield*/ /*additional weight*/);
hist_wlv->Write();
std::cout << " DataCardInfo ---------------- " << std::endl;
std::cout << Form(" Wlv_norm gmN %d %g ",(int)datayield,hist_wlv->Integral()/datayield) << std::endl;
std::cout << " ----------------------------- " << std::endl;
// Also correct normalization data why not?
hist_wlv = (TH1F*)generateTemplate(lMet, (RooFormulaVar*)wout->function("ratio_Wlv") , *(wout->var(mvamet.GetName())), (RooDataSet*) wout->data("Wlv_control_mc")
, 1 /*run correction*/
, 1. /*additional weight*/);
hist_wlv->Write();
//buildAndFitModels(fout,wout,mvamet,"Wlv");
//TH1F *hist_wlv = (TH1F*)generateTemplate(lMet, (RooFormulaVar*)wout->function("ratio_Wlv"), &mvamet, (RooDataSet*) wout->data(""));
//hist_wlv->Write();
#endif
// Since the W came in 2 parts, we can make the histogram based on the dataset (called uncorrected)
TH1F *hist_wlv_uc = (TH1F*)generateTemplate(lMet, (RooFormulaVar*)wout->function("") , *(wout->var(mvamet.GetName())), (RooDataSet*) wout->data("W")
, 1 /*run correction forwards*/
, 1./*brscaleFactorWlv*datayield/mcyield*/ /*additional weight*/);
hist_wlv_uc->Write();
#ifdef RUN_BKGSYS
// Load and run systematics from fit model
std::vector<TH1F> v_th1f_Z;
generateVariations(lMet,(RooFitResult*)fout->Get("fitResult_Zvv_control"),(RooFormulaVar*)wout->function("ratio_Zvv"),wout->var(mvamet.GetName()),v_th1f_Z,wout,"DY");
std::vector<TH1F> v_th1f_W;
generateVariations(lMet,(RooFitResult*)fout->Get("fitResult_Wlv_control"),(RooFormulaVar*)wout->function("ratio_Wlv"),wout->var(mvamet.GetName()),v_th1f_W,wout,"W");
// Nice plots
hist_zvv = (TH1F*)fout->Get("th1f_corrected_DY");
hist_wlv = (TH1F*)fout->Get("th1f_corrected_W");
double norm = hist_zvv->Integral();
int colit=2, styleit=1;
TCanvas *can_zvv_systs = new TCanvas("can_zvv_systs","can_zvv_systs",800,600);
TLegend *leg = new TLegend(0.6,0.4,0.89,0.89); leg->SetFillColor(0); leg->SetTextFont(42);
hist_zvv->SetLineColor(1);hist_zvv->SetLineWidth(3); hist_zvv->Draw();
for (std::vector<TH1F>::iterator hit=v_th1f_Z.begin();hit!=v_th1f_Z.end();hit++){
hit->SetLineColor(colit);
hit->SetLineWidth(3);
hit->SetLineStyle(styleit%2+1);
leg->AddEntry(&(*hit),hit->GetName(),"L");
hit->Scale(norm/hit->Integral());
hit->Draw("same");
hit->Write();
styleit++;
if (styleit%2==1) colit++;
}
leg->Draw();
can_zvv_systs->Write();
norm = hist_wlv->Integral();
styleit=1; colit=2;
TCanvas *can_wlv_systs = new TCanvas("can_wlv_systs","can_wlv_systs",800,600);
TLegend *leg_2 = new TLegend(0.6,0.4,0.89,0.89); leg_2->SetFillColor(0); leg_2->SetTextFont(42);
hist_wlv->SetLineColor(1);hist_wlv->SetLineWidth(3); hist_wlv->Draw();
for (std::vector<TH1F>::iterator hit=v_th1f_W.begin();hit!=v_th1f_W.end();hit++){
hit->SetLineColor(colit);
hit->SetLineWidth(3);
hit->SetLineStyle(styleit%2+1);
leg_2->AddEntry(&(*hit),hit->GetName(),"L");
hit->Scale(norm/hit->Integral());
hit->Draw("same");
hit->Write();
styleit++;
if (styleit%2==1) colit++;
}
leg_2->Draw();
can_wlv_systs->Write();
#endif
// Save the work
fout->cd();
wout->Write();
// Done!
}
void eregtestingExample(bool dobarrel=true, bool doele=true) {
//output dir
TString dirname = "/data/bendavid/eregexampletest/eregexampletest_test/";
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
TString infile = TString::Format("/data/bendavid/eregexampletest/%s",fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *meantgt = static_cast<RooGBRTargetFlex*>(ws->arg("sigmeant"));
RooRealVar *tgtvar = ws->var("tgtvar");
RooArgList vars;
vars.add(meantgt->FuncVars());
vars.add(*tgtvar);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
//TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
TFile *fdin = TFile::Open("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
//selection cuts for testing
TCut selcut;
if (dobarrel)
selcut = "ph.genpt>25. && ph.isbarrel && ph.ispromptgen";
else
selcut = "ph.genpt>25. && !ph.isbarrel && ph.ispromptgen";
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(evt%10==0)";
TCut prescale10alt = "(evt%10==1)";
TCut prescale25 = "(evt%25==0)";
TCut prescale100 = "(evt%100==0)";
TCut prescale1000 = "(evt%1000==0)";
TCut evenevents = "(evt%2==0)";
TCut oddevents = "(evt%2==1)";
TCut prescale100alt = "(evt%100==1)";
TCut prescale1000alt = "(evt%1000==1)";
TCut prescale50alt = "(evt%50==1)";
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
if (doele)
weightvar.SetTitle(prescale1000alt*selcut);
else
weightvar.SetTitle(prescale10alt*selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
//input variable corresponding to sceta
RooRealVar *scetavar = ws->var("var_1");
//regressed output functions
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.6,2.0,100);
hdata->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
craw->SaveAs("RawE.eps");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.eps");
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.eps");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.eps");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.eps");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.eps");
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.eps");
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor = hdata->createHistogram("hecor",*ecorvar);
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetXaxis()->SetRangeUser(0.6,1.2);
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
TCanvas *cresponse = new TCanvas;
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
cresponse->SaveAs("response.eps");
cresponse->SetLogy();
cresponse->SaveAs("responselog.eps");
printf("make fine histogram\n");
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(20e3,0.,2.));
printf("calc effsigma\n");
double effsigma = effSigma(hecorfine);
printf("effsigma = %5f\n",effsigma);
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
}
void Raa3S_Workspace(const char* filename="fitresult_combo_nofixed.root"){
TFile File(filename);
RooWorkspace * ws;
File.GetObject("wcombo", ws);
// ws->Print();
RooAbsData * data = ws->data("data");
// 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))",0.5,0,1);
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));
ws->import(step);
ws->factory( "Uniform::flat(raa3)" );
//pp Luminosities, Taa and efficiency ratios Systematics
ws->factory( "Taa_hi[5.662e-9]" );
ws->factory( "Taa_kappa[1.057]" );
ws->factory( "expr::alpha_Taa('pow(Taa_kappa,beta_Taa)',Taa_kappa,beta_Taa[0,-5,5])" );
ws->factory( "prod::Taa_nom(Taa_hi,alpha_Taa)" );
ws->factory( "Gaussian::constr_Taa(beta_Taa,glob_Taa[0,-5,5],1)" );
ws->factory( "lumipp_hi[5.4]" );
ws->factory( "lumipp_kappa[1.06]" );
ws->factory( "expr::alpha_lumipp('pow(lumipp_kappa,beta_lumipp)',lumipp_kappa,beta_lumipp[0,-5,5])" );
ws->factory( "prod::lumipp_nom(lumipp_hi,alpha_lumipp)" );
ws->factory( "Gaussian::constr_lumipp(beta_lumipp,glob_lumipp[0,-5,5],1)" );
// ws->factory( "effRat1[1]" );
// ws->factory( "effRat2[1]" );
ws->factory( "effRat3_hi[0.95]" );
ws->factory( "effRat_kappa[1.054]" );
ws->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)" );
ws->factory( "Gaussian::constr_effRat(beta_effRat,glob_effRat[0,-5,5],1)" );
// ws->factory( "prod::effRat2_nom(effRat2_hi,alpha_effRat)" );
ws->factory( "prod::effRat3_nom(effRat3_hi,alpha_effRat)" );
//
ws->factory("Nmb_hi[1.161e9]");
ws->factory("prod::denominator(Taa_nom,Nmb_hi)");
ws->factory( "expr::lumiOverTaaNmbmodified('lumipp_nom/denominator',lumipp_nom,denominator)");
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 = ws->var("N_{#Upsilon(3S)}_pp");
cout << nsig3_pp << endl;
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));
ws->import(nsig3_hi_modified);
// // background yield with systematics
ws->factory( "nbkg_hi_kappa[1.10]" );
ws->factory( "expr::alpha_nbkg_hi('pow(nbkg_hi_kappa,beta_nbkg_hi)',nbkg_hi_kappa,beta_nbkg_hi[0,-5,5])" );
ws->factory( "SUM::nbkg_hi_nom(alpha_nbkg_hi*bkgPdf_hi)" );
ws->factory( "Gaussian::constr_nbkg_hi(beta_nbkg_hi,glob_nbkg_hi[0,-5,5],1)" );
RooAbsPdf* sig1S_hi = ws->pdf("cbcb_hi");
RooAbsPdf* sig2S_hi = ws->pdf("sig2S_hi");
RooAbsPdf* sig3S_hi = ws->pdf("sig3S_hi");
RooAbsPdf* LSBackground_hi = ws->pdf("nbkg_hi_nom");
RooRealVar* nsig1_hi = ws->var("N_{#Upsilon(1S)}_hi");
RooRealVar* nsig2_hi = ws->var("N_{#Upsilon(2S)}_hi");
cout << nsig1_hi << " " << nsig2_hi << " " << nsig3_pp << endl;
RooFormulaVar* nsig3_hi = ws->function("nsig3_hi_modified");
RooRealVar* norm_nbkg_hi = ws->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);
////////////////////////////////////////////////////////////////////////////////
ws->factory( "nbkg_pp_kappa[1.03]" );
ws->factory( "expr::alpha_nbkg_pp('pow(nbkg_pp_kappa,beta_nbkg_pp)',nbkg_pp_kappa,beta_nbkg_pp[0,-5,5])" );
ws->factory( "SUM::nbkg_pp_nom(alpha_nbkg_pp*bkgPdf_pp)" );
ws->factory( "Gaussian::constr_nbkg_pp(beta_nbkg_pp,glob_nbkg_pp[0,-5,5],1)" );
RooAbsPdf* sig1S_pp = ws->pdf("cbcb_pp");
RooAbsPdf* sig2S_pp = ws->pdf("sig2S_pp");
RooAbsPdf* sig3S_pp = ws->pdf("sig3S_pp");
RooAbsPdf* LSBackground_pp = ws->pdf("nbkg_pp_nom");
RooRealVar* nsig1_pp = ws->var("N_{#Upsilon(1S)}_pp");
RooRealVar* nsig2_pp = ws->var("N_{#Upsilon(2S)}_pp");
RooRealVar* nsig3_pp = ws->var("N_{#Upsilon(3S)}_pp");
RooRealVar* norm_nbkg_pp = ws->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);
ws->import(model_num);
ws->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);
ws->import(model_den);
ws->factory("PROD::model_pp(model_den, constr_nbkg_pp)");
ws->factory("SIMUL::joint(dataCat,hi=model_hi,pp=model_pp)");
/////////////////////////////////////////////////////////////////////
RooRealVar * pObs = ws->var("invariantMass"); // get the pointer to the observable
RooArgSet obs("observables");
obs.add(*pObs);
obs.add( *ws->cat("dataCat"));
// /////////////////////////////////////////////////////////////////////
ws->var("glob_lumipp")->setConstant(true);
ws->var("glob_Taa")->setConstant(true);
ws->var("glob_effRat")->setConstant(true);
ws->var("glob_nbkg_pp")->setConstant(true);
ws->var("glob_nbkg_hi")->setConstant(true);
RooArgSet globalObs("global_obs");
globalObs.add( *ws->var("glob_lumipp") );
globalObs.add( *ws->var("glob_Taa") );
globalObs.add( *ws->var("glob_effRat") );
globalObs.add( *ws->var("glob_nbkg_hi") );
globalObs.add( *ws->var("glob_nbkg_pp") );
// ws->Print();
RooArgSet poi("poi");
poi.add( *ws->var("raa3") );
// create set of nuisance parameters
RooArgSet nuis("nuis");
nuis.add( *ws->var("beta_lumipp") );
nuis.add( *ws->var("beta_nbkg_hi") );
nuis.add( *ws->var("beta_nbkg_pp") );
nuis.add( *ws->var("beta_Taa") );
nuis.add( *ws->var("beta_effRat") );
ws->var("#alpha_{CB}_hi")->setConstant(true);
ws->var("#alpha_{CB}_pp")->setConstant(true);
ws->var("#sigma_{CB1}_hi")->setConstant(true);
ws->var("#sigma_{CB1}_pp")->setConstant(true);
ws->var("#sigma_{CB2}/#sigma_{CB1}_hi")->setConstant(true);
ws->var("#sigma_{CB2}/#sigma_{CB1}_pp")->setConstant(true);
ws->var("Centrality")->setConstant(true);
ws->var("N_{#Upsilon(1S)}_hi")->setConstant(true);
ws->var("N_{#Upsilon(1S)}_pp")->setConstant(true);
ws->var("N_{#Upsilon(2S)}_hi")->setConstant(true);
ws->var("N_{#Upsilon(2S)}_pp")->setConstant(true);
ws->var("N_{#Upsilon(3S)}_pp")->setConstant(true);
ws->var("Nmb_hi")->setConstant(true);
// ws->var("QQsign")->setConstant(true);
ws->var("Taa_hi")->setConstant(true);
ws->var("Taa_kappa")->setConstant(true);
// ws->var("beta_Taa")->setConstant(true);
// ws->var("beta_effRat")->setConstant(true);
// ws->var("beta_lumipp")->setConstant(true);
// ws->var("beta_nbkg_hi")->setConstant(true);
// ws->var("beta_nbkg_pp")->setConstant(true);
// ws->var("dataCat")->setConstant(true);
ws->var("decay_hi")->setConstant(true);
ws->var("decay_pp")->setConstant(true);
ws->var("effRat3_hi")->setConstant(true);
ws->var("effRat_kappa")->setConstant(true);
// ws->var("glob_Taa")->setConstant(true);
// ws->var("glob_effRat")->setConstant(true);
// ws->var("glob_lumipp")->setConstant(true);
// ws->var("glob_nbkg_hi")->setConstant(true);
// ws->var("glob_nbkg_pp")->setConstant(true);
// ws->var("invariantMass")->setConstant(true);
ws->var("leftEdge")->setConstant(true);
ws->var("lumipp_hi")->setConstant(true);
ws->var("lumipp_kappa")->setConstant(true);
ws->var("mass1S_hi")->setConstant(true);
ws->var("mass1S_pp")->setConstant(true);
ws->var("muMinusPt")->setConstant(true);
ws->var("muPlusPt")->setConstant(true);
ws->var("n_{Bkgd}_hi")->setConstant(true);
ws->var("n_{Bkgd}_pp")->setConstant(true);
ws->var("nbkg_hi_kappa")->setConstant(true);
ws->var("nbkg_pp_kappa")->setConstant(true);
ws->var("npow")->setConstant(true);
ws->var("N_{#Upsilon(3S)}_pp")->setConstant(true);
// ws->var("raa3")->setConstant(true);
ws->var("rightEdge")->setConstant(true);
ws->var("sigmaFraction_hi")->setConstant(true);
ws->var("sigmaFraction_pp")->setConstant(true);
ws->var("turnOn_hi")->setConstant(true);
ws->var("turnOn_pp")->setConstant(true);
ws->var("upsPt")->setConstant(true);
ws->var("upsRapidity")->setConstant(true);
ws->var("vProb")->setConstant(true);
ws->var("width_hi")->setConstant(true);
ws->var("width_pp")->setConstant(true);
ws->var("x3raw")->setConstant(true);
// RooArgSet fixed_again("fixed_again");
// fixed_again.add( *ws->var("leftEdge") );
// fixed_again.add( *ws->var("rightEdge") );
// fixed_again.add( *ws->var("Taa_hi") );
// fixed_again.add( *ws->var("Nmb_hi") );
// fixed_again.add( *ws->var("lumipp_hi") );
// fixed_again.add( *ws->var("effRat1_hi") );
// fixed_again.add( *ws->var("effRat2_hi") );
// fixed_again.add( *ws->var("effRat3_hi") );
// fixed_again.add( *ws->var("nsig3_pp") );
// fixed_again.add( *ws->var("nsig1_pp") );
// fixed_again.add( *ws->var("nbkg_hi") );
// fixed_again.add( *ws->var("alpha") );
// fixed_again.add( *ws->var("nbkg_kappa") );
// fixed_again.add( *ws->var("Taa_kappa") );
// fixed_again.add( *ws->var("lumipp_kappa") );
// fixed_again.add( *ws->var("mean_hi") );
// fixed_again.add( *ws->var("mean_pp") );
// fixed_again.add( *ws->var("width_hi") );
// fixed_again.add( *ws->var("turnOn_hi") );
// fixed_again.add( *ws->var("bkg_a1_pp") );
// fixed_again.add( *ws->var("bkg_a2_pp") );
// fixed_again.add( *ws->var("decay_hi") );
// fixed_again.add( *ws->var("raa1") );
// fixed_again.add( *ws->var("raa2") );
// fixed_again.add( *ws->var("nsig2_pp") );
// fixed_again.add( *ws->var("sigma1") );
// fixed_again.add( *ws->var("nbkg_pp") );
// fixed_again.add( *ws->var("npow") );
// fixed_again.add( *ws->var("muPlusPt") );
// fixed_again.add( *ws->var("muMinusPt") );
// fixed_again.add( *ws->var("mscale_hi") );
// fixed_again.add( *ws->var("mscale_pp") );
//
// ws->Print();
// create signal+background Model Config
RooStats::ModelConfig sbHypo("SbHypo");
sbHypo.SetWorkspace( *ws );
sbHypo.SetPdf( *ws->pdf("joint") );
sbHypo.SetObservables( obs );
sbHypo.SetGlobalObservables( globalObs );
sbHypo.SetParametersOfInterest( poi );
sbHypo.SetNuisanceParameters( nuis );
sbHypo.SetPriorPdf( *ws->pdf("step") ); // this is optional
// ws->Print();
/////////////////////////////////////////////////////////////////////
RooAbsReal * pNll = sbHypo.GetPdf()->createNLL( *data,NumCPU(2) );
RooMinuit(*pNll).migrad(); // minimize likelihood wrt all parameters before making plots
RooPlot *framepoi = ((RooRealVar *)poi.first())->frame(Bins(10),Range(0.,0.2),Title("LL and profileLL in raa3"));
pNll->plotOn(framepoi,ShiftToZero());
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");
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 = ws->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;
ws->import( sbHypo );
/////////////////////////////////////////////////////////////////////
RooStats::ModelConfig bHypo = sbHypo;
bHypo.SetName("BHypo");
bHypo.SetWorkspace(*ws);
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
double oldval = ((RooRealVar *)poi.first())->getVal( );
((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(*ws);
ws->import( bHypo );
/////////////////////////////////////////////////////////////////////
ws->Print();
bHypo.Print();
sbHypo.Print();
((RooRealVar *)poi.first())->setVal( oldval ); // set raa3=oldval here
// save workspace to file
ws -> SaveAs("TRIAL.root");
return;
}
//-------------------------------------------------------------
//Main macro for generating data and fitting
//=============================================================
void FitMassTwoD(const string workspaceFile = "/afs/cern.ch/work/d/daan/public/releases/CMSSW_5_3_9_patch3/src/CMSAna/HHToBBGG/data/FitWorkspace_asdf.root", const string outputTree = "/afs/cern.ch/work/d/daan/public/releases/CMSSW_5_3_9_patch3/src/CMSAna/HHToBBGG/data/MassFitResults/MassFitTwoD_asdf.root", Int_t plotOption = 0, Int_t storeOption = 1, Int_t constBkg = 1, Int_t NToys = 5000) {
TRandom3 *randomnumber = new TRandom3(1200);
TFile *wsFile = new TFile (workspaceFile.c_str(), "READ");
RooWorkspace *ws = (RooWorkspace*)wsFile->Get("MassFitWorkspace");
//Import variables from workspace
RooAbsPdf *model2Dpdf = ws->pdf("model2Dpdf");
RooRealVar *massBjet = ws->var("massBjet");
RooRealVar *massPho = ws->var("massPho");
RooRealVar *HHHCoupling = ws->var("HHHCoupling"); RooRealVar constHHHCoupling(*HHHCoupling);
RooRealVar *nres = ws->var("N (ResBkg)"); RooRealVar constNres(*nres);
RooRealVar *nnonres = ws->var("N (NonResBkg)"); RooRealVar constNnonres(*nnonres);
RooRealVar *expRateBjet = ws->var("expRateBjet"); RooRealVar constexpBjet(*expRateBjet);
RooRealVar *expRatePho = ws->var("expRatePho"); RooRealVar constexpPho(*expRatePho);
RooFormulaVar *nsig = (RooFormulaVar*)ws->function("nsig");
if (constBkg == 0) {
expRateBjet->setConstant(false);
expRatePho->setConstant(false);
} else {
expRateBjet->setConstant(true);
expRatePho->setConstant(true);
}
//Variables to set constant
RooRealVar *sigMeanBjet = ws->var("sigMeanBjet"); sigMeanBjet->setConstant();
RooRealVar *sigSigmaBjet = ws->var("sigSigmaBjet"); sigSigmaBjet->setConstant();
RooRealVar *sigAlpha = ws->var("sigAlpha"); sigAlpha->setConstant();
RooRealVar *sigPower = ws->var("sigPower"); sigPower->setConstant();
RooRealVar *resMeanBjet = ws->var("resMeanBjet"); resMeanBjet->setConstant();
RooRealVar *resSigmaBjet = ws->var("resSigmaBjet"); resSigmaBjet->setConstant();
RooRealVar *resAlpha = ws->var("resAlpha"); resAlpha->setConstant();
RooRealVar *resPower = ws->var("resPower"); resPower->setConstant();
RooRealVar *resExpo = ws->var("resExpo"); resExpo->setConstant();
RooRealVar *nbbH = ws->var("nbbH"); nbbH->setConstant();
RooRealVar *nOthers = ws->var("nOthers"); nOthers->setConstant();
//Create TTree to store the resulting yield data
TFile *f = new TFile(outputTree.c_str(), "RECREATE");
TTree *resultTree = new TTree("resultTree", "Parameter results from fitting");
Float_t nsigOut, nresOut, nnonresOut;
Float_t nsigStd, nresStd, nnonresStd;
Float_t HHHCouplingOut, HHHCouplingStd;
resultTree->Branch("nsigOut",&nsigOut, "nsigOut/F");
resultTree->Branch("nresOut",&nresOut, "nresOut/F");
resultTree->Branch("nnonresOut",&nnonresOut, "nnonresOut/F");
resultTree->Branch("nsigStd",&nsigStd, "nsigStd/F");
resultTree->Branch("nresStd",&nresStd, "nresStd/F");
resultTree->Branch("nnonresStd",&nnonresStd, "nnonresStd/F");
resultTree->Branch("HHHCouplingOut",&HHHCouplingOut, "HHHCouplingOut/F");
resultTree->Branch("HHHCouplingStd",&HHHCouplingStd, "HHHCouplingStd/F");
//Generate Toy MC experiment data and fits
for(UInt_t t=0; t < NToys; ++t) {
cout << "Toy #" << t << endl;
HHHCoupling->setVal(constHHHCoupling.getVal()); nres->setVal(constNres.getVal()); nnonres->setVal(constNnonres.getVal());
expRateBjet->setVal(constexpBjet.getVal()); expRatePho->setVal(constexpPho.getVal());
Float_t ran = randomnumber->Poisson(325.);
RooDataSet *pseudoData2D = model2Dpdf->generate(RooArgList(*massBjet,*massPho), ran);
RooFitResult *fitResult2D = model2Dpdf->fitTo(*pseudoData2D, RooFit::Save(), RooFit::Extended(kTRUE), RooFit::Strategy(2));
// if (t == 1763) {
// ws->import(*pseudoData2D, kTRUE);
// ws->import(*pseudoData2D, Rename("pseudoData2D"));
// }
// if (plotOption == 1) MakePlots(ws, fitResult2D);
// cout << "DEBUG: " << constexpBjet.getVal() << " , " << constexpPho.getVal() << " | " << expRateBjet->getVal() << " " << expRatePho->getVal() << "\n";
cout << "DEBUG: " << HHHCoupling->getVal() << " " << HHHCoupling->getPropagatedError(*fitResult2D) << "\n";
//Store fit parameters into ROOT file
if (storeOption == 1) {
//Save variables into separate branches of root tree
nsigOut = nsig->getVal();
nresOut = nres->getVal();
nnonresOut = nnonres->getVal();
nsigStd = nsig->getPropagatedError(*fitResult2D);
nresStd = nres->getPropagatedError(*fitResult2D);
nnonresStd = nnonres->getPropagatedError(*fitResult2D);
HHHCouplingOut = HHHCoupling->getVal();
HHHCouplingStd = HHHCoupling->getPropagatedError(*fitResult2D);
//cout << "\n\n\n\n\n\n" << nsigOut << " | " << nresOut << " | " << nnonresOut << " | " << ran << "\n\n\n\n\n" << endl;
resultTree->Fill();
}
}
//Write to the TTree and close it
resultTree->Write();
f->Close();
}
void mvaPUPPETEvaluation() {
//output dir
TString dirname = ".";
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
fname = "mvaPUPPET.root";
TString infile = fname.Data();
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *perpwidth = static_cast<RooGBRTargetFlex*>(ws->arg("perpwidth"));
RooGBRTargetFlex *perpmean = static_cast<RooGBRTargetFlex*>(ws->arg("perpmean"));
RooGBRTargetFlex *parpwidth = static_cast<RooGBRTargetFlex*>(ws->arg("parwidth"));
RooGBRTargetFlex *parmean = static_cast<RooGBRTargetFlex*>(ws->arg("parmean"));
RooRealVar *tgtvarX = ws->var("tgtX");
RooRealVar *tgtvarY = ws->var("tgtY");
RooArgList vars;
vars.add(perpwidth->FuncVars());
vars.add(perpmean->FuncVars());
vars.add(perpwidth->FuncVars());
vars.add(parmean->FuncVars());
vars.add(*tgtvarX);
vars.add(*tgtvarY);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TChain *dtree = new TChain("tree");
dtree->Add("root://eoscms.cern.ch//store//group/dpg_ecal/alca_ecalcalib/ecalMIBI/rgerosa/PUPPETAnalysis/DYJetsToLL_M-50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8_Asympt50ns_MCRUN2_74_V9A_forMVATraining/DYJetsToLL_M-50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/crab_20150724_111858/150724_091912/0000/output_mc_1.root/PUPPET/t");
//TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("");
// dtree = (TTree*)ddir->Get("t");
//selection cuts for testing
TCut selcut;
selcut = "Boson_daughter==13";
TCut selweight = "1";
TCut prescale100alt = "(evt%100==1)";
weightvar.SetTitle(selcut);
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
weightvar.SetTitle(selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdfX = ws->pdf("sigpdfX");
RooAbsPdf *sigpdfY = ws->pdf("sigpdfY");
//input variable corresponding to sceta
RooRealVar *scetavar = ws->var("var_1");
//regressed output functions
RooAbsReal *perpwidthlim = ws->function("perpwidthlim");
RooAbsReal *perpmeanlim = ws->function("perpmeanlim");
RooAbsReal *parwidthlim = ws->function("parwidthlim");
RooAbsReal *parmeanlim = ws->function("parmeanlim");
//////////////////////////////////////////////////////////////////////////////////////
//
// formula for corrected recoil?
//
/*
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
*/
//////////////////////////////////////////////////////////////////////////////////////
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *perpwidthvar = (RooRealVar*)hdataclone->addColumn(*perpwidthlim);
RooRealVar *perpmeanvar = (RooRealVar*)hdataclone->addColumn(*perpmeanlim);
RooRealVar *parwidthvar = (RooRealVar*)hdataclone->addColumn(*parwidthlim);
RooRealVar *parmeanvar = (RooRealVar*)hdataclone->addColumn(*parmeanlim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *crawX = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvarX->frame(-2.0,2.0,100);
hdata->plotOn(plot);
sigpdfX->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
crawX->SaveAs("RawX.png");
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *crawY = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot2 = tgtvarY->frame(-2.0,2.0,100);
hdata->plotOn(plot2);
sigpdfY->plotOn(plot2,ProjWData(*hdatasmall));
plot2->Draw();
crawY->SaveAs("RawY.png");
//////////////////////////////////////////////////////////////////////////////////////
/*
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.eps");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.eps");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.eps");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.eps");
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.eps");
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor = hdata->createHistogram("hecor",*ecorvar);
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetXaxis()->SetRangeUser(0.6,1.2);
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
TCanvas *cresponse = new TCanvas;
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
cresponse->SaveAs("response.eps");
cresponse->SetLogy();
cresponse->SaveAs("responselog.eps");
printf("make fine histogram\n");
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(20e3,0.,2.));
printf("calc effsigma\n");
double effsigma = effSigma(hecorfine);
printf("effsigma = %5f\n",effsigma);
*/
}
void ws_constrained_profile3D( const char* wsfile = "rootfiles/ws-data-unblind.root",
const char* new_poi_name = "n_M234_H4_3b",
int npoiPoints = 20,
double poiMinVal = 0.,
double poiMaxVal = 20.,
double constraintWidth = 1.5,
double ymax = 10.,
int verbLevel=0 ) {
gStyle->SetOptStat(0) ;
//--- make output directory.
char command[10000] ;
sprintf( command, "basename %s", wsfile ) ;
TString wsfilenopath = gSystem->GetFromPipe( command ) ;
wsfilenopath.ReplaceAll(".root","") ;
char outputdirstr[1000] ;
sprintf( outputdirstr, "outputfiles/scans-%s", wsfilenopath.Data() ) ;
TString outputdir( outputdirstr ) ;
printf("\n\n Creating output directory: %s\n\n", outputdir.Data() ) ;
sprintf(command, "mkdir -p %s", outputdir.Data() ) ;
gSystem->Exec( command ) ;
//--- Tell RooFit to shut up about anything less important than an ERROR.
RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR) ;
if ( verbLevel > 0 ) { printf("\n\n Verbose level : %d\n\n", verbLevel) ; }
TFile* wstf = new TFile( wsfile ) ;
RooWorkspace* ws = dynamic_cast<RooWorkspace*>( wstf->Get("ws") );
if ( verbLevel > 0 ) { ws->Print() ; }
RooDataSet* rds = (RooDataSet*) ws->obj( "ra2b_observed_rds" ) ;
if ( verbLevel > 0 ) {
printf("\n\n\n ===== RooDataSet ====================\n\n") ;
rds->Print() ;
rds->printMultiline(cout, 1, kTRUE, "") ;
}
ModelConfig* modelConfig = (ModelConfig*) ws->obj( "SbModel" ) ;
RooAbsPdf* likelihood = modelConfig->GetPdf() ;
RooRealVar* rrv_mu_susy_all0lep = ws->var("mu_susy_all0lep") ;
if ( rrv_mu_susy_all0lep == 0x0 ) {
printf("\n\n\n *** can't find mu_susy_all0lep in workspace. Quitting.\n\n\n") ;
return ;
}
//-- do BG only.
rrv_mu_susy_all0lep->setVal(0.) ;
rrv_mu_susy_all0lep->setConstant( kTRUE ) ;
//-- do a prefit.
printf("\n\n\n ====== Pre fit with unmodified nll var.\n\n") ;
RooFitResult* dataFitResultSusyFixed = likelihood->fitTo(*rds, Save(true),Hesse(false),Minos(false),Strategy(1),PrintLevel(verbLevel));
int dataSusyFixedFitCovQual = dataFitResultSusyFixed->covQual() ;
if ( dataSusyFixedFitCovQual < 2 ) { printf("\n\n\n *** Failed fit! Cov qual %d. Quitting.\n\n", dataSusyFixedFitCovQual ) ; return ; }
double dataFitSusyFixedNll = dataFitResultSusyFixed->minNll() ;
if ( verbLevel > 0 ) {
dataFitResultSusyFixed->Print("v") ;
}
printf("\n\n Nll value, from fit result : %.3f\n\n", dataFitSusyFixedNll ) ;
delete dataFitResultSusyFixed ;
//-- Construct the new POI parameter.
RooAbsReal* new_poi_rar(0x0) ;
new_poi_rar = ws->var( new_poi_name ) ;
if ( new_poi_rar == 0x0 ) {
printf("\n\n New POI %s is not a variable. Trying function.\n\n", new_poi_name ) ;
new_poi_rar = ws->function( new_poi_name ) ;
if ( new_poi_rar == 0x0 ) {
printf("\n\n New POI %s is not a function. I quit.\n\n", new_poi_name ) ;
return ;
}
} else {
printf("\n\n New POI %s is a variable with current value %.1f.\n\n", new_poi_name, new_poi_rar->getVal() ) ;
}
if ( npoiPoints <=0 ) {
printf("\n\n Quitting now.\n\n" ) ;
return ;
}
double startPoiVal = new_poi_rar->getVal() ;
//--- The RooNLLVar is NOT equivalent to what minuit uses.
// RooNLLVar* nll = new RooNLLVar("nll","nll", *likelihood, *rds ) ;
// printf("\n\n Nll value, from construction : %.3f\n\n", nll->getVal() ) ;
//--- output of createNLL IS what minuit uses, so use that.
RooAbsReal* nll = likelihood -> createNLL( *rds, Verbose(true) ) ;
RooRealVar* rrv_poiValue = new RooRealVar( "poiValue", "poiValue", 0., -10000., 10000. ) ;
/// rrv_poiValue->setVal( poiMinVal ) ;
/// rrv_poiValue->setConstant(kTRUE) ;
RooRealVar* rrv_constraintWidth = new RooRealVar("constraintWidth","constraintWidth", 0.1, 0.1, 1000. ) ;
rrv_constraintWidth -> setVal( constraintWidth ) ;
rrv_constraintWidth -> setConstant(kTRUE) ;
if ( verbLevel > 0 ) {
printf("\n\n ======= debug likelihood print\n\n") ;
likelihood->Print("v") ;
printf("\n\n ======= debug nll print\n\n") ;
nll->Print("v") ;
}
//----------------------------------------------------------------------------------------------
RooMinuit* rminuit( 0x0 ) ;
RooMinuit* rminuit_uc = new RooMinuit( *nll ) ;
rminuit_uc->setPrintLevel(verbLevel-1) ;
rminuit_uc->setNoWarn() ;
rminuit_uc->migrad() ;
rminuit_uc->hesse() ;
RooFitResult* rfr_uc = rminuit_uc->fit("mr") ;
double floatParInitVal[10000] ;
char floatParName[10000][100] ;
int nFloatParInitVal(0) ;
RooArgList ral_floats = rfr_uc->floatParsFinal() ;
TIterator* floatParIter = ral_floats.createIterator() ;
{
RooRealVar* par ;
while ( (par = (RooRealVar*) floatParIter->Next()) ) {
sprintf( floatParName[nFloatParInitVal], "%s", par->GetName() ) ;
floatParInitVal[nFloatParInitVal] = par->getVal() ;
nFloatParInitVal++ ;
}
}
//-------
printf("\n\n Unbiased best value for new POI %s is : %7.1f\n\n", new_poi_rar->GetName(), new_poi_rar->getVal() ) ;
double best_poi_val = new_poi_rar->getVal() ;
char minuit_formula[10000] ;
sprintf( minuit_formula, "%s+%s*(%s-%s)*(%s-%s)",
nll->GetName(),
rrv_constraintWidth->GetName(),
new_poi_rar->GetName(), rrv_poiValue->GetName(),
new_poi_rar->GetName(), rrv_poiValue->GetName()
) ;
printf("\n\n Creating new minuit variable with formula: %s\n\n", minuit_formula ) ;
RooFormulaVar* new_minuit_var = new RooFormulaVar("new_minuit_var", minuit_formula,
RooArgList( *nll,
*rrv_constraintWidth,
*new_poi_rar, *rrv_poiValue,
*new_poi_rar, *rrv_poiValue
) ) ;
printf("\n\n Current value is %.2f\n\n",
new_minuit_var->getVal() ) ;
rminuit = new RooMinuit( *new_minuit_var ) ;
RooAbsReal* plot_var = nll ;
printf("\n\n Current value is %.2f\n\n",
plot_var->getVal() ) ;
rminuit->setPrintLevel(verbLevel-1) ;
if ( verbLevel <=0 ) { rminuit->setNoWarn() ; }
//----------------------------------------------------------------------------------------------
//-- If POI range is -1 to -1, automatically determine the range using the set value.
if ( poiMinVal < 0. && poiMaxVal < 0. ) {
printf("\n\n Automatic determination of scan range.\n\n") ;
if ( startPoiVal <= 0. ) {
printf("\n\n *** POI starting value zero or negative %g. Quit.\n\n\n", startPoiVal ) ;
return ;
}
poiMinVal = startPoiVal - 3.5 * sqrt(startPoiVal) ;
poiMaxVal = startPoiVal + 6.0 * sqrt(startPoiVal) ;
if ( poiMinVal < 0. ) { poiMinVal = 0. ; }
printf(" Start val = %g. Scan range: %g to %g\n\n", startPoiVal, poiMinVal, poiMaxVal ) ;
}
//----------------------------------------------------------------------------------------------
double poiVals_scanDown[1000] ;
double nllVals_scanDown[1000] ;
//-- Do scan down from best value.
printf("\n\n +++++ Starting scan down from best value.\n\n") ;
double minNllVal(1.e9) ;
for ( int poivi=0; poivi < npoiPoints/2 ; poivi++ ) {
////double poiValue = poiMinVal + poivi*(poiMaxVal-poiMinVal)/(1.*(npoiPoints-1)) ;
double poiValue = best_poi_val - poivi*(best_poi_val-poiMinVal)/(1.*(npoiPoints/2-1)) ;
rrv_poiValue -> setVal( poiValue ) ;
rrv_poiValue -> setConstant( kTRUE ) ;
//+++++++++++++++++++++++++++++++++++
rminuit->migrad() ;
rminuit->hesse() ;
RooFitResult* rfr = rminuit->save() ;
//+++++++++++++++++++++++++++++++++++
if ( verbLevel > 0 ) { rfr->Print("v") ; }
float fit_minuit_var_val = rfr->minNll() ;
printf(" %02d : poi constraint = %.2f : allvars : MinuitVar, createNLL, PV, POI : %.5f %.5f %.5f %.5f\n",
poivi, rrv_poiValue->getVal(), fit_minuit_var_val, nll->getVal(), plot_var->getVal(), new_poi_rar->getVal() ) ;
cout << flush ;
poiVals_scanDown[poivi] = new_poi_rar->getVal() ;
nllVals_scanDown[poivi] = plot_var->getVal() ;
if ( nllVals_scanDown[poivi] < minNllVal ) { minNllVal = nllVals_scanDown[poivi] ; }
delete rfr ;
} // poivi
printf("\n\n +++++ Resetting floats to best fit values.\n\n") ;
for ( int pi=0; pi<nFloatParInitVal; pi++ ) {
RooRealVar* par = ws->var( floatParName[pi] ) ;
par->setVal( floatParInitVal[pi] ) ;
} // pi.
printf("\n\n +++++ Starting scan up from best value.\n\n") ;
//-- Now do scan up.
double poiVals_scanUp[1000] ;
double nllVals_scanUp[1000] ;
for ( int poivi=0; poivi < npoiPoints/2 ; poivi++ ) {
double poiValue = best_poi_val + poivi*(poiMaxVal-best_poi_val)/(1.*(npoiPoints/2-1)) ;
rrv_poiValue -> setVal( poiValue ) ;
rrv_poiValue -> setConstant( kTRUE ) ;
//+++++++++++++++++++++++++++++++++++
rminuit->migrad() ;
rminuit->hesse() ;
RooFitResult* rfr = rminuit->save() ;
//+++++++++++++++++++++++++++++++++++
if ( verbLevel > 0 ) { rfr->Print("v") ; }
float fit_minuit_var_val = rfr->minNll() ;
printf(" %02d : poi constraint = %.2f : allvars : MinuitVar, createNLL, PV, POI : %.5f %.5f %.5f %.5f\n",
poivi, rrv_poiValue->getVal(), fit_minuit_var_val, nll->getVal(), plot_var->getVal(), new_poi_rar->getVal() ) ;
cout << flush ;
poiVals_scanUp[poivi] = new_poi_rar->getVal() ;
nllVals_scanUp[poivi] = plot_var->getVal() ;
if ( nllVals_scanUp[poivi] < minNllVal ) { minNllVal = nllVals_scanUp[poivi] ; }
delete rfr ;
} // poivi
double poiVals[1000] ;
double nllVals[1000] ;
int pointCount(0) ;
for ( int pi=0; pi<npoiPoints/2; pi++ ) {
poiVals[pi] = poiVals_scanDown[(npoiPoints/2-1)-pi] ;
nllVals[pi] = nllVals_scanDown[(npoiPoints/2-1)-pi] ;
pointCount++ ;
}
for ( int pi=1; pi<npoiPoints/2; pi++ ) {
poiVals[pointCount] = poiVals_scanUp[pi] ;
nllVals[pointCount] = nllVals_scanUp[pi] ;
pointCount++ ;
}
npoiPoints = pointCount ;
printf("\n\n --- TGraph arrays:\n") ;
for ( int i=0; i<npoiPoints; i++ ) {
printf(" %2d : poi = %6.1f, nll = %g\n", i, poiVals[i], nllVals[i] ) ;
}
printf("\n\n") ;
double nllDiffVals[1000] ;
double poiAtMinlnL(-1.) ;
double poiAtMinusDelta2(-1.) ;
double poiAtPlusDelta2(-1.) ;
for ( int poivi=0; poivi < npoiPoints ; poivi++ ) {
nllDiffVals[poivi] = 2.*(nllVals[poivi] - minNllVal) ;
double poiValue = poiMinVal + poivi*(poiMaxVal-poiMinVal)/(1.*npoiPoints) ;
if ( nllDiffVals[poivi] < 0.01 ) { poiAtMinlnL = poiValue ; }
if ( poiAtMinusDelta2 < 0. && nllDiffVals[poivi] < 2.5 ) { poiAtMinusDelta2 = poiValue ; }
if ( poiAtMinlnL > 0. && poiAtPlusDelta2 < 0. && nllDiffVals[poivi] > 2.0 ) { poiAtPlusDelta2 = poiValue ; }
} // poivi
printf("\n\n Estimates for poi at delta ln L = -2, 0, +2: %g , %g , %g\n\n", poiAtMinusDelta2, poiAtMinlnL, poiAtPlusDelta2 ) ;
//--- Main canvas
TCanvas* cscan = (TCanvas*) gDirectory->FindObject("cscan") ;
if ( cscan == 0x0 ) {
printf("\n Creating canvas.\n\n") ;
cscan = new TCanvas("cscan","Delta nll") ;
}
char gname[1000] ;
TGraph* graph = new TGraph( npoiPoints, poiVals, nllDiffVals ) ;
sprintf( gname, "scan_%s", new_poi_name ) ;
graph->SetName( gname ) ;
double poiBest(-1.) ;
double poiMinus1stdv(-1.) ;
double poiPlus1stdv(-1.) ;
double poiMinus2stdv(-1.) ;
double poiPlus2stdv(-1.) ;
double twoDeltalnLMin(1e9) ;
int nscan(1000) ;
for ( int xi=0; xi<nscan; xi++ ) {
double x = poiVals[0] + xi*(poiVals[npoiPoints-1]-poiVals[0])/(nscan-1) ;
double twoDeltalnL = graph -> Eval( x, 0, "S" ) ;
if ( poiMinus1stdv < 0. && twoDeltalnL < 1.0 ) { poiMinus1stdv = x ; printf(" set m1 : %d, x=%g, 2dnll=%g\n", xi, x, twoDeltalnL) ;}
if ( poiMinus2stdv < 0. && twoDeltalnL < 4.0 ) { poiMinus2stdv = x ; printf(" set m2 : %d, x=%g, 2dnll=%g\n", xi, x, twoDeltalnL) ;}
if ( twoDeltalnL < twoDeltalnLMin ) { poiBest = x ; twoDeltalnLMin = twoDeltalnL ; }
if ( twoDeltalnLMin < 0.3 && poiPlus1stdv < 0. && twoDeltalnL > 1.0 ) { poiPlus1stdv = x ; printf(" set p1 : %d, x=%g, 2dnll=%g\n", xi, x, twoDeltalnL) ;}
if ( twoDeltalnLMin < 0.3 && poiPlus2stdv < 0. && twoDeltalnL > 4.0 ) { poiPlus2stdv = x ; printf(" set p2 : %d, x=%g, 2dnll=%g\n", xi, x, twoDeltalnL) ;}
if ( xi%100 == 0 ) { printf( " %4d : poi=%6.2f, 2DeltalnL = %6.2f\n", xi, x, twoDeltalnL ) ; }
}
printf("\n\n POI estimate : %g +%g -%g [%g,%g], two sigma errors: +%g -%g [%g,%g]\n\n",
poiBest,
(poiPlus1stdv-poiBest), (poiBest-poiMinus1stdv), poiMinus1stdv, poiPlus1stdv,
(poiPlus2stdv-poiBest), (poiBest-poiMinus2stdv), poiMinus2stdv, poiPlus2stdv
) ;
printf(" %s val,pm1sig,pm2sig: %7.2f %7.2f %7.2f %7.2f %7.2f\n",
new_poi_name, poiBest, (poiPlus1stdv-poiBest), (poiBest-poiMinus1stdv), (poiPlus2stdv-poiBest), (poiBest-poiMinus2stdv) ) ;
char htitle[1000] ;
sprintf(htitle, "%s profile likelihood scan: -2ln(L/Lm)", new_poi_name ) ;
TH1F* hscan = new TH1F("hscan", htitle, 10, poiMinVal, poiMaxVal ) ;
hscan->SetMinimum(0.) ;
hscan->SetMaximum(ymax) ;
hscan->DrawCopy() ;
graph->SetLineColor(4) ;
graph->SetLineWidth(3) ;
graph->Draw("CP") ;
gPad->SetGridx(1) ;
gPad->SetGridy(1) ;
cscan->Update() ;
TLine* line = new TLine() ;
line->SetLineColor(2) ;
line->DrawLine(poiMinVal, 1., poiPlus1stdv, 1.) ;
line->DrawLine(poiMinus1stdv,0., poiMinus1stdv, 1.) ;
line->DrawLine(poiPlus1stdv ,0., poiPlus1stdv , 1.) ;
TText* text = new TText() ;
text->SetTextSize(0.04) ;
char tstring[1000] ;
sprintf( tstring, "%s = %.1f +%.1f -%.1f", new_poi_name, poiBest, (poiPlus1stdv-poiBest), (poiBest-poiMinus1stdv) ) ;
text -> DrawTextNDC( 0.15, 0.85, tstring ) ;
sprintf( tstring, "68%% interval [%.1f, %.1f]", poiMinus1stdv, poiPlus1stdv ) ;
text -> DrawTextNDC( 0.15, 0.78, tstring ) ;
char hname[1000] ;
sprintf( hname, "hscanout_%s", new_poi_name ) ;
TH1F* hsout = new TH1F( hname,"scan results",4,0.,4.) ;
double obsVal(-1.) ;
hsout->SetBinContent(1, obsVal ) ;
hsout->SetBinContent(2, poiPlus1stdv ) ;
hsout->SetBinContent(3, poiBest ) ;
hsout->SetBinContent(4, poiMinus1stdv ) ;
TAxis* xaxis = hsout->GetXaxis() ;
xaxis->SetBinLabel(1,"Observed val.") ;
xaxis->SetBinLabel(2,"Model+1sd") ;
xaxis->SetBinLabel(3,"Model") ;
xaxis->SetBinLabel(4,"Model-1sd") ;
char outrootfile[10000] ;
sprintf( outrootfile, "%s/scan-ff-%s.root", outputdir.Data(), new_poi_name ) ;
char outpdffile[10000] ;
sprintf( outpdffile, "%s/scan-ff-%s.pdf", outputdir.Data(), new_poi_name ) ;
cscan->Update() ; cscan->Draw() ;
printf("\n Saving %s\n", outpdffile ) ;
cscan->SaveAs( outpdffile ) ;
//--- save in root file
printf("\n Saving %s\n", outrootfile ) ;
TFile fout(outrootfile,"recreate") ;
graph->Write() ;
hsout->Write() ;
fout.Close() ;
delete ws ;
wstf->Close() ;
}
/*
* Prepares the workspace to be used by the hypothesis test calculator
*/
void workspace_preparer(char *signal_file_name, char *signal_hist_name_in_file, char *background_file_name, char *background_hist_name_in_file, char *data_file_name, char *data_hist_name_in_file, char *config_file) {
// Include the config_reader class.
TString path = gSystem->GetIncludePath();
path.Append(" -I/home/max/cern/cls/mario");
gSystem->SetIncludePath(path);
gROOT->LoadMacro("config_reader.cxx");
// RooWorkspace used to store values.
RooWorkspace * pWs = new RooWorkspace("ws");
// Create a config_reader (see source for details) to read the config
// file.
config_reader reader(config_file, pWs);
// Read MR and RR bounds from the config file.
double MR_lower = reader.find_double("MR_lower");
double MR_upper = reader.find_double("MR_upper");
double RR_lower = reader.find_double("RR_lower");
double RR_upper = reader.find_double("RR_upper");
double MR_initial = (MR_lower + MR_upper)/2;
double RR_initial = (RR_lower + RR_upper)/2;
// Define the Razor Variables
RooRealVar MR = RooRealVar("MR", "MR", MR_initial, MR_lower, MR_upper);
RooRealVar RR = RooRealVar("RSQ", "RSQ", RR_initial, RR_lower, RR_upper);
// Argument lists
RooArgList pdf_arg_list(MR, RR, "input_args_list");
RooArgSet pdf_arg_set(MR, RR, "input_pdf_args_set");
/***********************************************************************/
/* PART 1: IMPORTING SIGNAL AND BACKGROUND HISTOGRAMS */
/***********************************************************************/
/*
* Get the signal's unextended pdf by converting the TH2D in the file
* into a RooHistPdf
*/
TFile *signal_file = new TFile(signal_file_name);
TH2D *signal_hist = (TH2D *)signal_file->Get(signal_hist_name_in_file);
RooDataHist *signal_RooDataHist = new RooDataHist("signal_roodatahist",
"signal_roodatahist",
pdf_arg_list,
signal_hist);
RooHistPdf *unextended_sig_pdf = new RooHistPdf("unextended_sig_pdf",
"unextended_sig_pdf",
pdf_arg_set,
*signal_RooDataHist);
/*
* Repeat this process for the background.
*/
TFile *background_file = new TFile(background_file_name);
TH2D *background_hist =
(TH2D *)background_file->Get(background_hist_name_in_file);
RooDataHist *background_RooDataHist =
new RooDataHist("background_roodatahist", "background_roodatahist",
pdf_arg_list, background_hist);
RooHistPdf *unextended_bkg_pdf = new RooHistPdf("unextended_bkg_pdf",
"unextended_bkg_pdf",
pdf_arg_set,
*background_RooDataHist);
/*
* Now, we want to create the bprime variable, which represents the
* integral over the background-only sample. We will perform the
* integral automatically (that's why this is the only nuisance
* parameter declared in this file - its value can be determined from
* the input histograms).
*/
ostringstream bprime_string;
ostringstream bprime_pdf_string;
bprime_string << "bprime[" << background_hist->Integral() << ", 0, 999999999]";
bprime_pdf_string << "Poisson::bprime_pdf(bprime, " << background_hist->Integral() << ")";
pWs->factory(bprime_string.str().c_str());
pWs->factory(bprime_pdf_string.str().c_str());
/*
* This simple command will create all values from the config file
* with 'make:' at the beginning and a delimiter at the end (see config
* _reader if you don't know what a delimiter is). In other
* words, the luminosity, efficiency, transfer factors, and their pdfs
* are created from this command. The declarations are contained in the
* config file to be changed easily without having to modify this code.
*/
reader.factory_all();
/*
* Now, we want to create the extended pdfs from the unextended pdfs, as
* well as from the S and B values we manufactured in the config file.
* S and B are the values by which the signal and background pdfs,
* respectively, are extended. Recall that they were put in the
* workspace in the reader.facotry_all() command.
*/
RooAbsReal *S = pWs->function("S");
RooAbsReal *B = pWs->function("B");
RooExtendPdf *signalpart = new RooExtendPdf("signalpart", "signalpart",
*unextended_sig_pdf, *S);
RooExtendPdf *backgroundpart =
new RooExtendPdf("backgroundpart", "backgroundpart",
*unextended_bkg_pdf, *B);
RooArgList *pdf_list = new RooArgList(*signalpart, *backgroundpart,
"list");
// Add the signal and background pdfs to make a TotalPdf
RooAddPdf *TotalPdf = new RooAddPdf("TotalPdf", "TotalPdf", *pdf_list);
RooArgList *pdf_prod_list = new RooArgList(*TotalPdf,
*pWs->pdf("lumi_pdf"),
*pWs->pdf("eff_pdf"),
*pWs->pdf("rho_pdf"),
*pWs->pdf("bprime_pdf"));
// This creates the final model pdf.
RooProdPdf *model = new RooProdPdf("model", "model", *pdf_prod_list);
/*
* Up until now, we have been using the workspace pWs to contain all of
* our values. Now, all of our values that we require are in use in the
* RooProdPdf called "model". So, we need to import "model" into a
* RooWorkspace. To avoid recopying values into the rooworkspace, when
* the values may already be present (which can cause problems), we will
* simply create a new RooWorkspace to avoid confusion and problems. The
* new RooWorkspace is created here.
*/
RooWorkspace *newworkspace = new RooWorkspace("newws");
newworkspace->import(*model);
// Immediately delete pWs, so we don't accidentally use it again.
delete pWs;
// Show off the newworkspace
newworkspace->Print();
// observables
RooArgSet obs(*newworkspace->var("MR"), *newworkspace->var("RSQ"), "obs");
// global observables
RooArgSet globalObs(*newworkspace->var("nom_lumi"), *newworkspace->var("nom_eff"), *newworkspace->var("nom_rho"));
//fix global observables to their nominal values
newworkspace->var("nom_lumi")->setConstant();
newworkspace->var("nom_eff")->setConstant();
newworkspace->var("nom_rho")->setConstant();
//Set Parameters of interest
RooArgSet poi(*newworkspace->var("sigma"), "poi");
//Set Nuisnaces
RooArgSet nuis(*newworkspace->var("prime_lumi"), *newworkspace->var("prime_eff"), *newworkspace->var("prime_rho"), *newworkspace->var("bprime"));
// priors (for Bayesian calculation)
newworkspace->factory("Uniform::prior_signal(sigma)"); // for parameter of interest
newworkspace->factory("Uniform::prior_bg_b(bprime)"); // for data driven nuisance parameter
newworkspace->factory("PROD::prior(prior_signal,prior_bg_b)"); // total prior
//Observed data is pulled from histogram.
//TFile *data_file = new TFile(data_file_name);
TFile *data_file = new TFile(data_file_name);
TH2D *data_hist = (TH2D *)data_file->Get(data_hist_name_in_file);
RooDataHist *pData = new RooDataHist("data", "data", obs, data_hist);
newworkspace->import(*pData);
// Now, we will draw our data from a RooDataHist.
/*TFile *data_file = new TFile(data_file_name);
TTree *data_tree = (TTree *) data_file->Get(data_hist_name_in_file);
RooDataSet *pData = new RooDataSet("data", "data", data_tree, obs);
newworkspace->import(*pData);*/
// Craft the signal+background model
ModelConfig * pSbModel = new ModelConfig("SbModel");
pSbModel->SetWorkspace(*newworkspace);
pSbModel->SetPdf(*newworkspace->pdf("model"));
pSbModel->SetPriorPdf(*newworkspace->pdf("prior"));
pSbModel->SetParametersOfInterest(poi);
pSbModel->SetNuisanceParameters(nuis);
pSbModel->SetObservables(obs);
pSbModel->SetGlobalObservables(globalObs);
// set all but obs, poi and nuisance to const
SetConstants(newworkspace, pSbModel);
newworkspace->import(*pSbModel);
// background-only model
// use the same PDF as s+b, with sig=0
// POI value under the background hypothesis
// (We will set the value to 0 later)
Double_t poiValueForBModel = 0.0;
ModelConfig* pBModel = new ModelConfig(*(RooStats::ModelConfig *)newworkspace->obj("SbModel"));
pBModel->SetName("BModel");
pBModel->SetWorkspace(*newworkspace);
newworkspace->import(*pBModel);
// find global maximum with the signal+background model
// with conditional MLEs for nuisance parameters
// and save the parameter point snapshot in the Workspace
// - safer to keep a default name because some RooStats calculators
// will anticipate it
RooAbsReal * pNll = pSbModel->GetPdf()->createNLL(*pData);
RooAbsReal * pProfile = pNll->createProfile(RooArgSet());
pProfile->getVal(); // this will do fit and set POI and nuisance parameters to fitted values
RooArgSet * pPoiAndNuisance = new RooArgSet();
if(pSbModel->GetNuisanceParameters())
pPoiAndNuisance->add(*pSbModel->GetNuisanceParameters());
pPoiAndNuisance->add(*pSbModel->GetParametersOfInterest());
cout << "\nWill save these parameter points that correspond to the fit to data" << endl;
pPoiAndNuisance->Print("v");
pSbModel->SetSnapshot(*pPoiAndNuisance);
delete pProfile;
delete pNll;
delete pPoiAndNuisance;
// Find a parameter point for generating pseudo-data
// with the background-only data.
// Save the parameter point snapshot in the Workspace
pNll = pBModel->GetPdf()->createNLL(*pData);
pProfile = pNll->createProfile(poi);
((RooRealVar *)poi.first())->setVal(poiValueForBModel);
pProfile->getVal(); // this will do fit and set nuisance parameters to profiled values
pPoiAndNuisance = new RooArgSet();
if(pBModel->GetNuisanceParameters())
pPoiAndNuisance->add(*pBModel->GetNuisanceParameters());
pPoiAndNuisance->add(*pBModel->GetParametersOfInterest());
cout << "\nShould use these parameter points to generate pseudo data for bkg only" << endl;
pPoiAndNuisance->Print("v");
pBModel->SetSnapshot(*pPoiAndNuisance);
delete pProfile;
delete pNll;
delete pPoiAndNuisance;
// save workspace to file
newworkspace->writeToFile("ws_twobin.root");
// clean up
delete newworkspace;
delete pData;
delete pSbModel;
delete pBModel;
} // ----- end of tutorial ----------------------------------------
void eregtest_flextest(bool dobarrel, bool doele) {
TString dirname = "/afs/cern.ch/work/b/bendavid/bare/eregtestoutalphafix2_float/";
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
//TString infile = TString::Format("/afs/cern.ch/work/b/bendavid/bare/eregAug10RCalphafixphiblind//%s",fname.Data());
TString infile = TString::Format("/data/bendavid/regflextesting/%s",fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//RooGBRFunction *func = static_cast<RooGBRFunction*>(ws->arg("func"));
RooGBRTargetFlex *sigmeant = (RooGBRTargetFlex*)ws->function("sigmeant");
RooRealVar *tgtvar = ws->var("tgtvar");
//tgtvar->removeRange();
//tgtvar->setRange(0.98,1.02);
RooRealVar *rawptvar = new RooRealVar("rawptvar","ph.scrawe/cosh(ph.eta)",1.);
if (!dobarrel) rawptvar->SetTitle("(ph.scrawe+ph.scpse)/cosh(ph.eta)");
RooRealVar *rawevar = new RooRealVar("rawevar","ph.scrawe",1.);
if (!dobarrel) rawevar->SetTitle("(ph.scrawe+ph.scpse)");
RooRealVar *nomevar = new RooRealVar("nomevar","ph.e",1.);
RooArgList vars;
vars.add(sigmeant->FuncVars());
vars.add(*tgtvar);
vars.add(*rawptvar);
vars.add(*rawevar);
vars.add(*nomevar);
RooArgList condvars;
condvars.add(sigmeant->FuncVars());
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
TFile *fdin = TFile::Open("/data/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
//TFile *fdin = TFile::Open("/data/bendavid/idTrees_7TeV_Sept17/hgg-2013Final7TeV_ID_s11-h125gg-gf-lv3_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
// if (0)
// {
//
// TFile *fdin = TFile::Open("/data/bendavid/8TeVFinalTreesSept17/hgg-2013Final8TeV_s12-diphoj-v7n_noskim.root");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPresel");
// dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
//
// }
if (0)
{
TFile *fdin = TFile::Open("/data/bendavid/diphoTrees8TeVOct6/hgg-2013Final8TeV_s12-h123gg-gf-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
// //TFile *fdin = TFile::Open("/home/mingyang/cms/hist/hgg-2013Moriond/merged/hgg-2013Moriond_s12-diphoj-3-v7a_noskim.root");
// //TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/trainingtreesJul1/hgg-2013Final8TeV_s12-zllm50-v7n_noskim.root");
// TFile *fdin = TFile::Open("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
// //TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
// //TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
// TTree *dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
/* TFile *fdinsig = TFile::Open("/home/mingyang/cms/hist/hgg-2013Moriond/merged/hgg-2013Moriond_s12-h125gg-gf-v7a_noskim.root");
TDirectory *ddirsig = (TDirectory*)fdinsig->FindObjectAny("PhotonTreeWriterPreselNoSmear");
TTree *dtreesig = (TTree*)ddirsig->Get("hPhotonTreeSingle"); */
TCut selcut;
if (dobarrel) {
selcut = "ph.pt>25. && ph.isbarrel && ph.ispromptgen && abs(ph.sceta)>(-1.0)";
//selcut = "ph.pt>25. && ph.isbarrel && ph.ispromptgen && abs(ph.sceta)>(-1.0) && run==194533 && lumi==5 && evt==1400";
}
else {
selcut = "ph.pt>25 && !ph.isbarrel && ph.ispromptgen";
//selcut = "ph.pt>25 && !ph.isbarrel && ph.ispromptgen && run==194533 && lumi==5 && evt==1400";
}
// TCut selcut = "ph.pt>25. && ph.isbarrel && ph.ispromptgen && abs(ph.sceta)<1.0";
//TCut selcut = "ph.pt>25. && ph.isbarrel && (ph.scrawe/ph.gene)>0. && (ph.scrawe/ph.gene)<2. && ph.ispromptgen";
//TCut selcut = "ph.pt>25. && ph.isbarrel && (ph.gene/ph.scrawe)>0. && (ph.gene/ph.scrawe)<2.";
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(evt%10==0)";
TCut prescale10alt = "(evt%10==1)";
TCut prescale25 = "(evt%25==0)";
TCut prescale100 = "(evt%100==0)";
TCut prescale1000 = "(evt%1000==0)";
TCut evenevents = "(evt%2==0)";
TCut oddevents = "(evt%2==1)";
TCut prescale100alt = "(evt%100==1)";
TCut prescale1000alt = "(evt%1000==1)";
TCut prescale50alt = "(evt%50==1)";
//TCut oddevents = prescale100;
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
// for (int iev=0; iev<hdata->numEntries(); ++iev) {
// const RooArgSet *dset = hdata->get(iev);
//
// condvars = *dset;
// condvars.Print("V");
//
// }
//return;
// if (doele)
// weightvar.SetTitle(prescale100alt*selcut);
// else
// weightvar.SetTitle(selcut);
//RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
// const HybridGBRForestD *forest = func->Forest();
// for (unsigned int itgt=0; itgt<forest->Trees().size(); ++itgt) {
// int ntrees = 0;
// for (unsigned int itree = 0; itree<forest->Trees().at(itgt).size(); ++itree) {
// if (forest->Trees()[itgt][itree].Responses().size()>1) ++ntrees;
// }
// printf("itgt = %i, ntrees = %i\n", int(itgt),ntrees);
// }
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
RooRealVar *scetavar = ws->var("var_1");
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
RooAbsReal *alphalim = ws->function("sigalphalim");
RooAbsReal *alpha2lim = ws->function("sigalpha2lim");
//RooFormulaVar ecor("ecor","","1./(@0*@1)",RooArgList(*tgtvar,*sigmeanlim));
RooFormulaVar ecor("ecor","","@1/@0",RooArgList(*tgtvar,*sigmeanlim));
//RooFormulaVar ecor("ecor","","@0/@1",RooArgList(*tgtvar,*sigmeanlim));
//RooFormulaVar ecor("ecor","","exp(@1-@0)",RooArgList(*tgtvar,*sigmeanlim));
RooAbsReal *condnll = sigpdf->createNLL(*hdata,ConditionalObservables(sigmeant->FuncVars()));
double condnllval = condnll->getVal();
//RooFormulaVar ecor("ecor","","@1/@0",RooArgList(*tgtvar,*sigmeanlim));
//RooFormulaVar ecor("ecor","","@0/@1",RooArgList(*tgtvar,*sigmeanlim));
//RooFormulaVar ecor("ecor","","@0",RooArgList(*tgtvar));
//RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
// ecorvar->setRange(0.,2.);
// ecorvar->setBins(800);
// RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
// //RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
// rawvar->setRange(0.,2.);
// rawvar->setBins(800);
/* RooFormulaVar eraw("eraw","","@0",RooArgList(*tgtvar));
RooRealVar *erawvar = (RooRealVar*)hdatasig->addColumn(eraw);
erawvar->setRange(0.,2.);
erawvar->setBins(400); */
//RooFormulaVar ecor("ptcor","","@0/(@1)",RooArgList(*tgtvar,*sigmeanlim));
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *ecorvar = (RooRealVar*)hdataclone->addColumn(ecor);
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = 0;
if (signlim) nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = 0;
if (sign2lim) n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
RooRealVar *alphavar = 0;;
if (alphalim) alphavar = (RooRealVar*)hdataclone->addColumn(*alphalim);
RooRealVar *alpha2var = 0;
if (alpha2lim) alpha2var = (RooRealVar*)hdataclone->addColumn(*alpha2lim);
RooFormulaVar ecorfull("ecorfull","","@0*@1",RooArgList(*sigmeanlim,*rawevar));
RooRealVar *ecorfullvar = (RooRealVar*)hdataclone->addColumn(ecorfull);
RooFormulaVar ediff("ediff","","(@0 - @1)/@1",RooArgList(*nomevar,ecorfull));
RooRealVar *ediffvar = (RooRealVar*)hdataclone->addColumn(ediff);
RooFormulaVar fullerr("fullerr","","@0*@1",RooArgList(*ecorvar,*sigwidthlim));
RooRealVar *fullerrvar = (RooRealVar*)hdataclone->addColumn(fullerr);
RooFormulaVar relerr("relerr","","@0/@1",RooArgList(*sigwidthlim,*sigmeanlim));
RooRealVar *relerrvar = (RooRealVar*)hdataclone->addColumn(relerr);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
//RooFormulaVar raw("raw","","exp(-@0)",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdataclone->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
RooNormPdf sigpdfpeaknorm("sigpdfpeaknorm","",*sigpdf,*tgtvar);
RooRealVar *sigpdfpeaknormvar = (RooRealVar*)hdataclone->addColumn(sigpdfpeaknorm);
RooFormulaVar equivsigma("equivsigma","","@0/sqrt(2.0*TMath::Pi())/@1",RooArgList(sigpdfpeaknorm,*sigmeanlim));
RooRealVar *equivsigmavar = (RooRealVar*)hdataclone->addColumn(equivsigma);
// for (int iev=0; iev<hdataclone->numEntries(); ++iev) {
// const RooArgSet *dset = hdataclone->get(iev);
//
// //condvars = *dset;
// //condvars.Print("V");
// dset->Print("V");
// }
//
// return;
//hdataclone = (RooDataSet*)hdataclone->reduce("(rawptvar/sigmeanlim)>45.");
//hdataclone = (RooDataSet*)hdataclone->reduce("relerr>0.1");
// hdataclone = (RooDataSet*)hdataclone->reduce("sigwidthlim>0.017");
// RooLinearVar *tgtscaled = (RooLinearVar*)ws->function("tgtscaled");
//
// TCanvas *ccor = new TCanvas;
// //RooPlot *plot = tgtvar->frame(0.6,1.2,100);
// RooPlot *plotcor = tgtscaled->frame(0.6,2.0,100);
// hdataclone->plotOn(plotcor);
// sigpdf->plotOn(plotcor,ProjWData(*hdataclone));
// plotcor->Draw();
// ccor->SaveAs("CorE.eps");
// ccor->SetLogy();
// plotcor->SetMinimum(0.1);
// ccor->SaveAs("CorElog.eps");
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.8,1.4,400);
//RooPlot *plot = tgtvar->frame(0.0,5.,400);
//RooPlot *plot = tgtvar->frame(0.,5.,400);
//RooPlot *plot = tgtvar->frame(-2.0,2.0,200);
hdataclone->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdataclone));
plot->Draw();
craw->SaveAs("RawE.eps");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.eps");
/* new TCanvas;
RooPlot *plotsig = tgtvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotsig);
sigpdf.plotOn(plotsig,ProjWData(*hdatasig));
plotsig->Draw(); */
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.0,5.0,200);
//RooPlot *plotmean = meanvar->frame(0.5,1.5,200);
//RooPlot *plotmean = meanvar->frame(-1.0,1.0,200);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.eps");
cmean->SetLogy();
plotmean->SetMinimum(0.1);
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,1.0,200);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.eps");
cwidth->SetLogy();
plotwidth->SetMinimum(0.1);
if (signlim) {
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,20.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.eps");
TCanvas *cnwide = new TCanvas;
RooPlot *plotnwide = nvar->frame(0.,2100.,200);
hdataclone->plotOn(plotnwide);
plotnwide->Draw();
cnwide->SaveAs("nwide.eps");
}
if (sign2lim) {
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,20.,200);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.eps");
TCanvas *cn2wide = new TCanvas;
RooPlot *plotn2wide = n2var->frame(0.,2100.,200);
hdataclone->plotOn(plotn2wide);
plotn2wide->Draw();
cn2wide->SaveAs("n2wide.eps");
}
if (alphalim) {
TCanvas *calpha = new TCanvas;
RooPlot *plotalpha = alphavar->frame(0.,6.,200);
hdataclone->plotOn(plotalpha);
plotalpha->Draw();
calpha->SaveAs("alpha.eps");
calpha->SetLogy();
plotalpha->SetMinimum(0.1);
}
if (alpha2lim) {
TCanvas *calpha2 = new TCanvas;
RooPlot *plotalpha2 = alpha2var->frame(0.,6.,200);
hdataclone->plotOn(plotalpha2);
plotalpha2->Draw();
calpha2->SaveAs("alpha2.eps");
}
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.eps");
//TH1 *heold = hdatasigtest->createHistogram("heold",testvar);
//TH1 *heraw = hdata->createHistogram("heraw",*tgtvar,Binning(800,0.,2.));
TH1 *heraw = hdataclone->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor = hdataclone->createHistogram("hecor",*ecorvar);
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetXaxis()->SetRangeUser(0.6,1.2);
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
TCanvas *cresponse = new TCanvas;
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
cresponse->SaveAs("response.eps");
cresponse->SetLogy();
cresponse->SaveAs("responselog.eps");
TCanvas *cpeakval = new TCanvas;
RooPlot *plotpeak = sigpdfpeaknormvar->frame(0.,10.,100);
hdataclone->plotOn(plotpeak);
plotpeak->Draw();
TCanvas *cequivsigmaval = new TCanvas;
RooPlot *plotequivsigma = equivsigmavar->frame(0.,0.04,100);
hdataclone->plotOn(plotequivsigma);
plotequivsigma->Draw();
TCanvas *cediff = new TCanvas;
RooPlot *plotediff = ediffvar->frame(-0.01,0.01,100);
hdataclone->plotOn(plotediff);
plotediff->Draw();
printf("make fine histogram\n");
TH1 *hecorfine = hdataclone->createHistogram("hecorfine",*ecorvar,Binning(20e3,0.,2.));
printf("calc effsigma\n");
double effsigma = effSigma(hecorfine);
printf("effsigma = %5f\n",effsigma);
printf("condnll = %5f\n",condnllval);
TFile *fhist = new TFile("hist.root","RECREATE");
fhist->WriteTObject(hecor);
fhist->Close();
return;
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
TH2 *profhist = (TH2*)hdataclone->createHistogram("relerrvsE",*ecorfullvar,Binning(50,0.,200.), YVar(*relerrvar,Binning(100,0.,0.05)));
new TCanvas;
profhist->Draw("COLZ");
new TCanvas;
profhist->ProfileX()->Draw();
new TCanvas;
profhist->ProfileY()->Draw();
TH2 *profhistequiv = (TH2*)hdataclone->createHistogram("equiverrvsE",*ecorfullvar,Binning(50,0.,200.), YVar(*equivsigmavar,Binning(100,0.,0.05)));
new TCanvas;
profhistequiv->Draw("COLZ");
new TCanvas;
profhistequiv->ProfileX()->Draw();
new TCanvas;
profhistequiv->ProfileY()->Draw();
}
