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bmm4toystudy.cc
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bmm4toystudy.cc
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#include "bmm4common.h"
void ProduceToyTauSPlot(RooWorkspace *wspace_res, RooWorkspace *wspace, RooDataSet *toy_data, int toy_idx, bool sys_study = false, bool display = false)
{
cout << ">>> ProduceToyTauSPlot() start" << endl;
enum {_bs, _bd, _peak, _semi, _h2mu, _comb, _nspec};
vector<TString> specs= {"bs", "bd", "peak", "semi", "h2mu", "comb"};
TH1D *h_tau = new TH1D("h_tau_bs", "", Tau_bins.size()-1, Tau_bins.data());
h_tau->Sumw2();
RooFitResult *res1 = NULL, *res2 = NULL;
vector<TH1D*> h_tau_sys;
vector<double> diff_tau_sys;
vector<TString> cmd_tau_sys;
if (sys_study) {
cmd_tau_sys.push_back(Form("0HistEffModel"));
cmd_tau_sys.push_back(Form("+respar_bsmm_mix_taue"));
cmd_tau_sys.push_back(Form("-respar_bsmm_mix_taue"));
cmd_tau_sys.push_back(Form("+fs_over_fu_S13"));
cmd_tau_sys.push_back(Form("-fs_over_fu_S13"));
for (auto& cat: CatMan.cats) {
cmd_tau_sys.push_back(Form("+N_bu_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("-N_bu_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("+effratio_bs_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("-effratio_bs_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("+effratio_bd_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("-effratio_bd_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("+N_semi_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("-N_semi_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("+N_h2mu_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("-N_h2mu_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("+N_peak_%s", cat.id.Data()));
cmd_tau_sys.push_back(Form("-N_peak_%s", cat.id.Data()));
}
h_tau_sys.assign(cmd_tau_sys.size(),NULL);
diff_tau_sys.assign(cmd_tau_sys.size(),0.);
for (int sysidx = 0; sysidx < (int)cmd_tau_sys.size(); sysidx++) {
h_tau_sys[sysidx] = new TH1D(Form("h_tau_sys_%03d",sysidx), "", Tau_bins.size()-1, Tau_bins.data());
h_tau_sys[sysidx]->Sumw2();
}
}
for (int sysidx = -1; sysidx < (int)cmd_tau_sys.size(); sysidx++) {
if (!sys_study && sysidx>=0) break; // skip nuisances variations
double nuisance_preserve = 0.;
if (sysidx>=0) {
TString var = cmd_tau_sys[sysidx](0,1);
TString key = cmd_tau_sys[sysidx](1,cmd_tau_sys[sysidx].Length()-1);
// Take post-fit nuisance variation
if (var!="0") {
RooRealVar *nuisance = wspace->var(key);
nuisance_preserve = nuisance->getVal();
if (var=="-") nuisance->setVal(nuisance_preserve-nuisance->getError());
if (var=="+") nuisance->setVal(nuisance_preserve+nuisance->getError());
}
}
for (auto& cat: CatMan.cats) {
RooRealVar *Mass = wspace->var("Mass");
RooRealVar *ReducedMassRes = wspace->var("ReducedMassRes");
RooCategory *PairCat = wspace->cat("PairCat");
RooArgSet norm(*Mass,*ReducedMassRes,*PairCat);
double yield[_nspec];
yield[_bs] = wspace->function(Form("N_bs_formula_%s",cat.id.Data()))->getVal();
yield[_bd] = wspace->function(Form("N_bd_formula_%s",cat.id.Data()))->getVal();
yield[_peak] = wspace->function(Form("N_peak_formula_%s",cat.id.Data()))->getVal();
yield[_semi] = wspace->function(Form("N_semi_formula_%s",cat.id.Data()))->getVal();
yield[_h2mu] = wspace->var(Form("N_h2mu_%s",cat.id.Data()))->getVal();
yield[_comb] = wspace->var(Form("N_comb_%s",cat.id.Data()))->getVal();
TMatrixD covInv(_nspec, _nspec);
covInv = 0.;
for (int evt=0; evt<toy_data->numEntries(); evt++) {
const RooArgSet* arg = toy_data->get(evt);
if (arg->getCatIndex("GlobalCat")!=cat.index) continue;
Mass->setVal(arg->getRealValue("Mass"));
ReducedMassRes->setVal(arg->getRealValue("ReducedMassRes"));
PairCat->setIndex(arg->getCatIndex("PairCat"));
double pdf[_nspec];
for (int idx = 0; idx<_nspec; idx++)
pdf[idx] = wspace->pdf(Form("pdf_%s_%s",specs[idx].Data(),cat.id.Data()))->getVal(&norm);
double pdf_total = 0.;
for (int idx = 0; idx<_nspec; idx++) pdf_total += yield[idx]*pdf[idx];
for (int row = 0; row<_nspec; row++)
for (int col = 0; col<_nspec; col++)
covInv(row,col) += pdf[row]*pdf[col]/(pdf_total*pdf_total);
}
TMatrixD covMatrix(TMatrixD::kInverted,covInv);
for (int evt=0; evt<toy_data->numEntries(); evt++) {
const RooArgSet* arg = toy_data->get(evt);
if (arg->getCatIndex("GlobalCat")!=cat.index) continue;
if (arg->getCatIndex("SelCat")!=1) continue;
Mass->setVal(arg->getRealValue("Mass"));
ReducedMassRes->setVal(arg->getRealValue("ReducedMassRes"));
PairCat->setIndex(arg->getCatIndex("PairCat"));
double pdf[_nspec];
for (int idx = 0; idx<_nspec; idx++)
pdf[idx] = wspace->pdf(Form("pdf_%s_%s",specs[idx].Data(),cat.id.Data()))->getVal(&norm);
double denominator = 0.;
for (int idx = 0; idx<_nspec; idx++) denominator += yield[idx]*pdf[idx];
double numerator = 0.;
for (int idx = 0; idx<_nspec; idx++) numerator += covMatrix(_bs,idx)*pdf[idx];
double weight = numerator/denominator;
if (sysidx<0) h_tau->Fill(arg->getRealValue("Tau"),weight);
else h_tau_sys[sysidx]->Fill(arg->getRealValue("Tau"),weight);
}
}
RooRealVar *Tau = wspace->var("Tau");
RooRealVar *EffTau_bs = wspace->var("EffTau_bs");
RooAbsPdf *Tau_pdf_bs = wspace->pdf("Tau_pdf_bs_mix");
EffTau_bs->setConstant(false);
EffTau_bs->setMax(8.0);
EffTau_bs->setVal(1.61); // always start from SM value
if (sysidx<0) { // central fit
Fit_sPlot(h_tau, Tau_pdf_bs, Tau, EffTau_bs, &res1, &res2);
wspace_res->import(*res1,Form("fitresult_taubs_toy_%d",toy_idx)); // results with corrected uncertainties
wspace_res->import(*res2,Form("fitresult_taubs_wl_toy_%d",toy_idx)); // results from the 2nd weighted likelihood fit
}else {
TString key = cmd_tau_sys[sysidx](1,cmd_tau_sys[sysidx].Length()-1);
RooFitResult *res1sys = NULL, *res2sys = NULL;
if (key=="HistEffModel") {
RooResolutionModel *TauRes_Model = (RooResolutionModel*)wspace->obj(Form("TauRes_Model_bsmm_mix"));
RooFormulaVar *TauEff_Model = (RooFormulaVar*)wspace->obj(Form("TauEff_Model_Hist_bsmm_mix"));
RooDecay RawDecay("RawDecay_alter","",*Tau,*EffTau_bs,*TauRes_Model,RooDecay::SingleSided);
RooEffProd Tau_pdf("Tau_pdf_alter","",RawDecay,*TauEff_Model);
Fit_sPlot(h_tau_sys[sysidx], &Tau_pdf, Tau, EffTau_bs, &res1sys, &res2sys);
}else
Fit_sPlot(h_tau_sys[sysidx], Tau_pdf_bs, Tau, EffTau_bs, &res1sys, &res2sys);
RooRealVar* tau0 = (RooRealVar*)res1->floatParsFinal().find("EffTau_bs");
RooRealVar* tau1 = (RooRealVar*)res1sys->floatParsFinal().find("EffTau_bs");
diff_tau_sys[sysidx] = tau1->getVal()-tau0->getVal();
delete res1sys;
delete res2sys;
}
if (sysidx<0 && display) {
RooDataHist *h_tau_data = new RooDataHist("h_tau_data", "", RooArgList(*Tau), h_tau);
TString title = "CMS Preliminary";
RooPlot* frame = Tau->frame(Title(" "));
h_tau->SetMarkerStyle(20);
h_tau->SetLineColor(kBlack);
h_tau_data->plotOn(frame,MarkerStyle(20),LineColor(kBlack));
Tau_pdf_bs->plotOn(frame, DrawOption("L"), LineColor(kBlue), LineWidth(2), LineStyle(1), NumCPU(NCPU));
TCanvas* canvas = new TCanvas("canvas", "", 600, 600);
canvas->SetMargin(0.14,0.06,0.13,0.07);
frame->GetYaxis()->SetTitleOffset(1.15);
frame->GetYaxis()->SetTitle("Entries");
frame->GetXaxis()->SetTitleOffset(1.15);
frame->GetXaxis()->SetLabelOffset(0.01);
frame->GetXaxis()->SetTitle("#tau [ps]");
frame->GetXaxis()->SetTitleSize(0.043);
frame->GetYaxis()->SetTitleSize(0.043);
frame->SetStats(false);
frame->Draw("E");
gStyle->SetErrorX(0);
TLatex tex;
tex.SetTextFont(42);
tex.SetTextSize(0.035);
tex.SetTextAlign(11);
tex.SetNDC();
tex.DrawLatex(0.14,0.94,title);
TLine lin;
lin.SetLineColor(kGray+1);
lin.SetLineWidth(2);
lin.SetLineStyle(7);
lin.DrawLine(1.,0.,12.,0.);
canvas->Update();
TLegend *leg1 = new TLegend(0.50,0.86,0.91,0.91);
leg1->SetNColumns(1);
leg1->SetFillColor(kWhite);
leg1->SetLineColor(kWhite);
leg1->AddEntry(h_tau, "weighted toy (B_{s})", "lep");
leg1->Draw();
canvas->Print("fig/tau_splot_fit_toy_bs.pdf");
delete leg1;
delete h_tau_data;
delete frame;
delete canvas;
}
if (sysidx>=0) { // restore the nuisance value
TString var = cmd_tau_sys[sysidx](0,1);
TString key = cmd_tau_sys[sysidx](1,cmd_tau_sys[sysidx].Length()-1);
if (var!="0") {
RooRealVar *nuisance = wspace->var(key);
nuisance->setVal(nuisance_preserve);
}
}
} // ending of systematics loop
if (sys_study) {
double err_p = 0., err_m = 0.;
for (int sysidx = 0; sysidx < (int)cmd_tau_sys.size(); sysidx++) {
TString var = cmd_tau_sys[sysidx](0,1);
TString key = cmd_tau_sys[sysidx](1,cmd_tau_sys[sysidx].Length()-1);
cout << ">>> SYS(" << var << ") " << key << ": " << diff_tau_sys[sysidx] << endl;
if (diff_tau_sys[sysidx]>0.) err_p += diff_tau_sys[sysidx]*diff_tau_sys[sysidx];
if (diff_tau_sys[sysidx]<0.) err_m += diff_tau_sys[sysidx]*diff_tau_sys[sysidx];
delete h_tau_sys[sysidx];
}
err_p = sqrt(err_p);
err_m = sqrt(err_m);
RooFitResult res3(*res1);
RooRealVar* tau1 = (RooRealVar*)res3.floatParsFinal().find("EffTau_bs");
tau1->setError(max(err_p, err_m));
tau1->setAsymError(-err_m, err_p);
wspace_res->import(res3,Form("fitresult_taubs_syst_toy_%d",toy_idx)); // systematic results
RooRealVar* tau0 = (RooRealVar*)res1->floatParsFinal().find("EffTau_bs");
cout << ">>> EffTau central: " << tau0->getVal() << " +- " <<
tau0->getError() << " (+" << tau0->getErrorHi() << "/" << tau0->getErrorLo() << ")" <<
" (+" << err_p << "/-" << err_m << ")" << endl;
}
delete h_tau;
delete res1;
delete res2;
}
// Available options:
// ---------
// prefit - adopt pre-fit nuisances, randomize all of the nuisances according to the constraints
// freq - generate frequentist toy, adopt post-fit nuisances, randomize all of the constrained means
// freezenui - freeze all of the nuisances in the fit
// ---------
// signif - do significance estimation
// bdstat - Calculate profile Likelihood test statistics (F&C study or upper limit calculation for Bd)
// ---------
// tausplot - add decay time component, produce splot, and fit
// tausyst - enable systematic studies for tausplot
//
void PerformToyStudy(RooWorkspace *wspace_res, RooWorkspace* wspace_gen, RooWorkspace* wspace_fit, int iterations = 10, bool do_minos = false, TString opt = "prefit;signif")
{
cout << ">>> PerformToyStudy() start" << endl;
RooRealVar *Mass = wspace_gen->var("Mass");
RooRealVar *ReducedMassRes = wspace_gen->var("ReducedMassRes");
RooRealVar *Tau = wspace_gen->var("Tau");
RooRealVar *TauRes = wspace_gen->var("TauRes");
RooCategory *SelCat = wspace_gen->cat("SelCat");
RooCategory *PairCat = wspace_gen->cat("PairCat");
RooCategory *GlobalCat = wspace_gen->cat("GlobalCat");
RooArgSet varlist(*Mass,*ReducedMassRes,*PairCat,*Tau,*TauRes,*SelCat,*GlobalCat);
for(int idx=0; idx<iterations; idx++) {
cout << ">>> # iterations: " << idx+1 << "/" << iterations << endl;
RooWorkspace* wspace = new RooWorkspace(*wspace_fit); // clone wspace_fit
if (opt.Contains("prefit")) { // adopt pre-fit nuisances, randomize all of the nuisances according to the constraints
RooDataSet *tmp_evt;
// change the wspace_gen
RooRealVar *fs_over_fu = wspace_gen->var("fs_over_fu");
RooRealVar *fs_over_fu_S13 = wspace_gen->var("fs_over_fu_S13");
RooRealVar *one_over_BRBR = wspace_gen->var("one_over_BRBR");
RooAbsPdf *fs_over_fu_gau = wspace_gen->pdf("fs_over_fu_gau");
RooAbsPdf *fs_over_fu_S13_gau = wspace_gen->pdf("fs_over_fu_S13_gau");
RooAbsPdf *one_over_BRBR_gau = wspace_gen->pdf("one_over_BRBR_gau");
tmp_evt = fs_over_fu_gau->generate(RooArgSet(*fs_over_fu),1);
fs_over_fu->setVal(tmp_evt->get(0)->getRealValue(fs_over_fu->GetName())); delete tmp_evt;
tmp_evt = fs_over_fu_S13_gau->generate(RooArgSet(*fs_over_fu_S13),1);
fs_over_fu_S13->setVal(tmp_evt->get(0)->getRealValue(fs_over_fu_S13->GetName())); delete tmp_evt;
tmp_evt = one_over_BRBR_gau->generate(RooArgSet(*one_over_BRBR),1);
one_over_BRBR->setVal(tmp_evt->get(0)->getRealValue(one_over_BRBR->GetName())); delete tmp_evt;
for (auto& cat: CatMan.cats) {
// change the wspace_gen
RooRealVar *N_bu = wspace_gen->var(Form("N_bu_%s", cat.id.Data()));
RooRealVar *N_peak = wspace_gen->var(Form("N_peak_%s", cat.id.Data()));
RooRealVar *N_semi = wspace_gen->var(Form("N_semi_%s", cat.id.Data()));
RooRealVar *N_h2mu = wspace_gen->var(Form("N_h2mu_%s", cat.id.Data()));
RooRealVar *effratio_bs = wspace_gen->var(Form("effratio_bs_%s", cat.id.Data()));
RooRealVar *effratio_bd = wspace_gen->var(Form("effratio_bd_%s", cat.id.Data()));
RooAbsPdf *N_bu_gau = wspace_gen->pdf(Form("N_bu_%s_gau", cat.id.Data()));
RooAbsPdf *N_peak_lnn = wspace_gen->pdf(Form("N_peak_%s_lnn", cat.id.Data()));
RooAbsPdf *N_semi_lnn = wspace_gen->pdf(Form("N_semi_%s_lnn", cat.id.Data()));
RooAbsPdf *N_h2mu_lnn = wspace_gen->pdf(Form("N_h2mu_%s_lnn", cat.id.Data()));
RooAbsPdf *effratio_bs_gau = wspace_gen->pdf(Form("effratio_bs_%s_gau", cat.id.Data()));
RooAbsPdf *effratio_bd_gau = wspace_gen->pdf(Form("effratio_bd_%s_gau", cat.id.Data()));
tmp_evt = N_bu_gau->generate(RooArgSet(*N_bu),1);
N_bu->setVal(tmp_evt->get(0)->getRealValue(N_bu->GetName())); delete tmp_evt;
tmp_evt = N_peak_lnn->generate(RooArgSet(*N_peak),1);
N_peak->setVal(tmp_evt->get(0)->getRealValue(N_peak->GetName())); delete tmp_evt;
tmp_evt = N_semi_lnn->generate(RooArgSet(*N_semi),1);
N_semi->setVal(tmp_evt->get(0)->getRealValue(N_semi->GetName())); delete tmp_evt;
tmp_evt = N_h2mu_lnn->generate(RooArgSet(*N_h2mu),1);
N_h2mu->setVal(tmp_evt->get(0)->getRealValue(N_h2mu->GetName())); delete tmp_evt;
tmp_evt = effratio_bs_gau->generate(RooArgSet(*effratio_bs),1);
effratio_bs->setVal(tmp_evt->get(0)->getRealValue(effratio_bs->GetName())); delete tmp_evt;
tmp_evt = effratio_bd_gau->generate(RooArgSet(*effratio_bd),1);
effratio_bd->setVal(tmp_evt->get(0)->getRealValue(effratio_bd->GetName())); delete tmp_evt;
}
}else if (opt.Contains("freq")) { // generate frequentist toy, adopt post-fit nuisances, randomize all of the constrained means
RooDataSet *tmp_evt;
// change the clone of wspace_fit
RooRealVar *fs_over_fu = wspace->var("fs_over_fu");
RooRealVar *fs_over_fu_S13 = wspace->var("fs_over_fu_S13");
RooRealVar *one_over_BRBR = wspace->var("one_over_BRBR");
RooRealVar *fs_over_fu_mean = wspace->var("fs_over_fu_mean");
RooRealVar *fs_over_fu_S13_mean = wspace->var("fs_over_fu_S13_mean");
RooRealVar *one_over_BRBR_mean = wspace->var("one_over_BRBR_mean");
RooAbsPdf *fs_over_fu_gau = wspace->pdf("fs_over_fu_gau");
RooAbsPdf *fs_over_fu_S13_gau = wspace->pdf("fs_over_fu_S13_gau");
RooAbsPdf *one_over_BRBR_gau = wspace->pdf("one_over_BRBR_gau");
fs_over_fu_mean->setVal(fs_over_fu->getVal());
tmp_evt = fs_over_fu_gau->generate(RooArgSet(*fs_over_fu),1);
fs_over_fu_mean->setVal(tmp_evt->get(0)->getRealValue(fs_over_fu->GetName())); delete tmp_evt;
fs_over_fu_S13_mean->setVal(fs_over_fu_S13->getVal());
tmp_evt = fs_over_fu_S13_gau->generate(RooArgSet(*fs_over_fu_S13),1);
fs_over_fu_S13_mean->setVal(tmp_evt->get(0)->getRealValue(fs_over_fu_S13->GetName())); delete tmp_evt;
one_over_BRBR_mean->setVal(one_over_BRBR->getVal());
tmp_evt = one_over_BRBR_gau->generate(RooArgSet(*one_over_BRBR),1);
one_over_BRBR_mean->setVal(tmp_evt->get(0)->getRealValue(one_over_BRBR->GetName())); delete tmp_evt;
for (auto& cat: CatMan.cats) {
// change the clone of wspace_fit
RooRealVar *N_bu = wspace->var(Form("N_bu_%s", cat.id.Data()));
RooRealVar *N_peak = wspace->var(Form("N_peak_%s", cat.id.Data()));
RooRealVar *N_semi = wspace->var(Form("N_semi_%s", cat.id.Data()));
RooRealVar *N_h2mu = wspace->var(Form("N_h2mu_%s", cat.id.Data()));
RooRealVar *effratio_bs = wspace->var(Form("effratio_bs_%s", cat.id.Data()));
RooRealVar *effratio_bd = wspace->var(Form("effratio_bd_%s", cat.id.Data()));
RooRealVar *N_bu_mean = wspace->var(Form("N_bu_%s_mean", cat.id.Data()));
RooRealVar *N_peak_mean = wspace->var(Form("N_peak_%s_mean", cat.id.Data()));
RooRealVar *N_semi_mean = wspace->var(Form("N_semi_%s_mean", cat.id.Data()));
RooRealVar *N_h2mu_mean = wspace->var(Form("N_h2mu_%s_mean", cat.id.Data()));
RooRealVar *effratio_bs_mean = wspace->var(Form("effratio_bs_%s_mean", cat.id.Data()));
RooRealVar *effratio_bd_mean = wspace->var(Form("effratio_bd_%s_mean", cat.id.Data()));
RooAbsPdf *N_bu_gau = wspace->pdf(Form("N_bu_%s_gau", cat.id.Data()));
RooAbsPdf *N_peak_lnn = wspace->pdf(Form("N_peak_%s_lnn", cat.id.Data()));
RooAbsPdf *N_semi_lnn = wspace->pdf(Form("N_semi_%s_lnn", cat.id.Data()));
RooAbsPdf *N_h2mu_lnn = wspace->pdf(Form("N_h2mu_%s_lnn", cat.id.Data()));
RooAbsPdf *effratio_bs_gau = wspace->pdf(Form("effratio_bs_%s_gau", cat.id.Data()));
RooAbsPdf *effratio_bd_gau = wspace->pdf(Form("effratio_bd_%s_gau", cat.id.Data()));
N_bu_mean->setVal(N_bu->getVal());
tmp_evt = N_bu_gau->generate(RooArgSet(*N_bu),1);
N_bu_mean->setVal(tmp_evt->get(0)->getRealValue(N_bu->GetName())); delete tmp_evt;
N_peak_mean->setVal(N_peak->getVal());
tmp_evt = N_peak_lnn->generate(RooArgSet(*N_peak),1);
N_peak_mean->setVal(tmp_evt->get(0)->getRealValue(N_peak->GetName())); delete tmp_evt;
N_semi_mean->setVal(N_semi->getVal());
tmp_evt = N_semi_lnn->generate(RooArgSet(*N_semi),1);
N_semi_mean->setVal(tmp_evt->get(0)->getRealValue(N_semi->GetName())); delete tmp_evt;
N_h2mu_mean->setVal(N_h2mu->getVal());
tmp_evt = N_h2mu_lnn->generate(RooArgSet(*N_h2mu),1);
N_h2mu_mean->setVal(tmp_evt->get(0)->getRealValue(N_h2mu->GetName())); delete tmp_evt;
effratio_bs_mean->setVal(effratio_bs->getVal());
tmp_evt = effratio_bs_gau->generate(RooArgSet(*effratio_bs),1);
effratio_bs_mean->setVal(tmp_evt->get(0)->getRealValue(effratio_bs->GetName())); delete tmp_evt;
effratio_bd_mean->setVal(effratio_bd->getVal());
tmp_evt = effratio_bd_gau->generate(RooArgSet(*effratio_bd),1);
effratio_bd_mean->setVal(tmp_evt->get(0)->getRealValue(effratio_bd->GetName())); delete tmp_evt;
}
}else if (opt.Contains("freezenui")) { // freeze all of the nuisances in the fit
// change the clone of wspace_fit
wspace->var("fs_over_fu")->setConstant(true);
wspace->var("fs_over_fu_S13")->setConstant(true);
wspace->var("one_over_BRBR")->setConstant(true);
for (auto& cat: CatMan.cats) {
// change the clone of wspace_fit
wspace->var(Form("N_bu_%s", cat.id.Data()))->setConstant(true);
wspace->var(Form("N_peak_%s", cat.id.Data()))->setConstant(true);
wspace->var(Form("N_semi_%s", cat.id.Data()))->setConstant(true);
wspace->var(Form("N_h2mu_%s", cat.id.Data()))->setConstant(true);
wspace->var(Form("effratio_bs_%s", cat.id.Data()))->setConstant(true);
wspace->var(Form("effratio_bd_%s", cat.id.Data()))->setConstant(true);
}
}
RooDataSet *toy_data = new RooDataSet("toy_data","",varlist);
// do category-by-category, component-by-component generation, replace the buggy CBShape
for (auto& cat: CatMan.cats) {
GlobalCat->setIndex(cat.index);
RooProdPdf *TauSelCat_pdf_bs = 0, *TauSelCat_pdf_bd = 0, *TauSelCat_pdf_peak = 0, *TauSelCat_pdf_semi = 0, *TauSelCat_pdf_h2mu = 0, *TauSelCat_pdf_comb = 0;
if (opt.Contains("tausplot")) {
TauSelCat_pdf_bs = new RooProdPdf("TauSelCat_pdf_bs", "", *wspace_gen->pdf(Form("Tau_pdf_bs_%s",cat.id.Data())),
*wspace_gen->pdf(Form("SelCat_pdf_bs_%s",cat.id.Data())));
TauSelCat_pdf_bd = new RooProdPdf("TauSelCat_pdf_bd", "", *wspace_gen->pdf(Form("Tau_pdf_bd_%s",cat.id.Data())),
*wspace_gen->pdf(Form("SelCat_pdf_bd_%s",cat.id.Data())));
TauSelCat_pdf_peak = new RooProdPdf("TauSelCat_pdf_peak","", *wspace_gen->pdf(Form("Tau_pdf_peak_%s",cat.id.Data())),
*wspace_gen->pdf(Form("SelCat_pdf_peak_%s",cat.id.Data())));
TauSelCat_pdf_semi = new RooProdPdf("TauSelCat_pdf_semi","", *wspace_gen->pdf(Form("Tau_pdf_semi_%s",cat.id.Data())),
*wspace_gen->pdf(Form("SelCat_pdf_semi_%s",cat.id.Data())));
TauSelCat_pdf_h2mu = new RooProdPdf("TauSelCat_pdf_h2mu","", *wspace_gen->pdf(Form("Tau_pdf_h2mu_%s",cat.id.Data())),
*wspace_gen->pdf(Form("SelCat_pdf_h2mu_%s",cat.id.Data())));
TauSelCat_pdf_comb = new RooProdPdf("TauSelCat_pdf_comb","", *wspace_gen->pdf(Form("Tau_pdf_comb_%s",cat.id.Data())),
*wspace_gen->pdf(Form("SelCat_pdf_comb_%s",cat.id.Data())));
}
RooAbsPdf *pdf_bs = wspace_gen->pdf(Form("pdf_bs_%s", cat.id.Data()));
RooAbsPdf *pdf_bd = wspace_gen->pdf(Form("pdf_bd_%s", cat.id.Data()));
RooAbsPdf *pdf_comb = wspace_gen->pdf(Form("pdf_comb_%s", cat.id.Data()));
RooAbsPdf *pdf_semi = wspace_gen->pdf(Form("pdf_semi_%s", cat.id.Data()));
RooAbsPdf *pdf_h2mu = wspace_gen->pdf(Form("pdf_h2mu_%s", cat.id.Data()));
RooAbsPdf *pdf_peak = wspace_gen->pdf(Form("pdf_peak_%s", cat.id.Data()));
int N_bs = RooRandom::randomGenerator()->Poisson(wspace_gen->function(Form("N_bs_formula_%s", cat.id.Data()))->getVal());
int N_bd = RooRandom::randomGenerator()->Poisson(wspace_gen->function(Form("N_bd_formula_%s", cat.id.Data()))->getVal());
int N_comb = RooRandom::randomGenerator()->Poisson(wspace_gen->var(Form("N_comb_%s", cat.id.Data()))->getVal());
int N_semi = RooRandom::randomGenerator()->Poisson(wspace_gen->function(Form("N_semi_formula_%s", cat.id.Data()))->getVal());
int N_h2mu = RooRandom::randomGenerator()->Poisson(wspace_gen->var(Form("N_h2mu_%s", cat.id.Data()))->getVal());
int N_peak = RooRandom::randomGenerator()->Poisson(wspace_gen->function(Form("N_peak_formula_%s", cat.id.Data()))->getVal());
RooDataSet *toy_gen, *toy_tau;
toy_gen = pdf_comb->generate(RooArgSet(*Mass,*ReducedMassRes,*PairCat),N_comb);
if (opt.Contains("tausplot")) {
toy_tau = TauSelCat_pdf_comb->generate(RooArgSet(*Tau,*SelCat),N_comb);
toy_gen->merge(toy_tau);
delete toy_tau;
}
toy_gen->addColumn(*GlobalCat);
toy_data->append(*toy_gen);
delete toy_gen;
toy_gen = pdf_semi->generate(RooArgSet(*Mass,*ReducedMassRes,*PairCat),N_semi);
if (opt.Contains("tausplot")) {
toy_tau = TauSelCat_pdf_semi->generate(RooArgSet(*Tau,*SelCat),N_semi);
toy_gen->merge(toy_tau);
delete toy_tau;
}
toy_gen->addColumn(*GlobalCat);
toy_data->append(*toy_gen);
delete toy_gen;
toy_gen = pdf_h2mu->generate(RooArgSet(*Mass,*ReducedMassRes,*PairCat),N_h2mu);
if (opt.Contains("tausplot")) {
toy_tau = TauSelCat_pdf_h2mu->generate(RooArgSet(*Tau,*SelCat),N_h2mu);
toy_gen->merge(toy_tau);
delete toy_tau;
}
toy_gen->addColumn(*GlobalCat);
toy_data->append(*toy_gen);
delete toy_gen;
toy_gen = pdf_peak->generate(RooArgSet(*Mass,*ReducedMassRes,*PairCat),N_peak);
if (opt.Contains("tausplot")) {
toy_tau = TauSelCat_pdf_peak->generate(RooArgSet(*Tau,*SelCat),N_peak);
toy_gen->merge(toy_tau);
delete toy_tau;
}
toy_gen->addColumn(*GlobalCat);
toy_data->append(*toy_gen);
delete toy_gen;
double resample;
RooAcceptReject AR_bs(*pdf_bs, RooArgSet(*Mass,*ReducedMassRes,*PairCat), *pdf_bs->getGeneratorConfig(), false, 0);
RooAcceptReject AR_bd(*pdf_bd, RooArgSet(*Mass,*ReducedMassRes,*PairCat), *pdf_bd->getGeneratorConfig(), false, 0);
toy_gen = new RooDataSet("toy_gen","",RooArgSet(*Mass,*ReducedMassRes,*PairCat));
resample = 0.;
for (int count=0; count<N_bs; count++)
toy_gen->add(*AR_bs.generateEvent(N_bs-count,resample));
if (opt.Contains("tausplot")) {
toy_tau = TauSelCat_pdf_bs->generate(RooArgSet(*Tau,*SelCat),N_bs);
toy_gen->merge(toy_tau);
delete toy_tau;
}
toy_gen->addColumn(*GlobalCat);
toy_data->append(*toy_gen);
delete toy_gen;
toy_gen = new RooDataSet("toy_gen","",RooArgSet(*Mass,*ReducedMassRes,*PairCat));
resample = 0.;
for (int count=0; count<N_bd; count++)
toy_gen->add(*AR_bd.generateEvent(N_bd-count,resample));
if (opt.Contains("tausplot")) {
toy_tau = TauSelCat_pdf_bd->generate(RooArgSet(*Tau,*SelCat),N_bd);
toy_gen->merge(toy_tau);
delete toy_tau;
}
toy_gen->addColumn(*GlobalCat);
toy_data->append(*toy_gen);
delete toy_gen;
if (opt.Contains("tausplot")) {
delete TauSelCat_pdf_bs;
delete TauSelCat_pdf_bd;
delete TauSelCat_pdf_peak;
delete TauSelCat_pdf_semi;
delete TauSelCat_pdf_h2mu;
delete TauSelCat_pdf_comb;
}
}
RooArgSet global_ext_constr(*wspace->pdf("fs_over_fu_gau"),*wspace->pdf("fs_over_fu_S13_gau"),*wspace->pdf("one_over_BRBR_gau"));
RooArgSet minos_list;
for (auto& POI: POI_list) minos_list.add(*wspace->var(POI));
vector<RooCmdArg> fit_cmd;
fit_cmd.push_back(ExternalConstraints(global_ext_constr));
fit_cmd.push_back(Strategy(2));
fit_cmd.push_back(Extended(true));
fit_cmd.push_back(NumCPU(NCPU));
fit_cmd.push_back(Hesse(true));
fit_cmd.push_back(Optimize(true));
if (USING_MINUIT2) fit_cmd.push_back(Minimizer("Minuit2","migrad"));
//fit_cmd.push_back(Offset(true));
fit_cmd.push_back(Save(true));
if (do_minos) fit_cmd.push_back(Minos(minos_list));
RooLinkedList fit_linkl;
for (auto& cmd : fit_cmd) fit_linkl.Add(&cmd);
RooFitResult *res = fit_with_retry(*wspace->pdf("global_pdf"),*toy_data,fit_linkl,1);
res->Print("v");
wspace_res->import(*res,Form("fitresult_toy_%d",idx));
const RooArgSet *all_floats = wspace->set("all_floats");
wspace->saveSnapshot("best_fit",*all_floats);
if (opt.Contains("signif")) {
// Significance estimation for Bd
wspace->var("BF_bd")->setVal(0.);
wspace->var("BF_bd")->setConstant(true);
RooFitResult *res_zerobd = fit_with_retry(*wspace->pdf("global_pdf"),*toy_data,fit_linkl,1);
wspace_res->import(*res_zerobd,Form("fitresult_zerobd_toy_%d",idx));
wspace->loadSnapshot("best_fit");
// Significance estimation for Bs
wspace->var("BF_bs")->setVal(0.);
wspace->var("BF_bs")->setConstant(true);
RooFitResult *res_zerobs = fit_with_retry(*wspace->pdf("global_pdf"),*toy_data,fit_linkl,1);
wspace_res->import(*res_zerobs,Form("fitresult_zerobs_toy_%d",idx));
wspace->loadSnapshot("best_fit");
delete res_zerobd;
delete res_zerobs;
}else if (opt.Contains("bdstat")) { // assume the default fit is carried out with BF_bd fixed to the target branching fraction
// release Bd BF
wspace->var("BF_bd")->setConstant(false);
RooFitResult *res_floatbd = fit_with_retry(*wspace->pdf("global_pdf"),*toy_data,fit_linkl,1);
wspace_res->import(*res_floatbd,Form("fitresult_floatbd_toy_%d",idx));
wspace->loadSnapshot("best_fit");
delete res_floatbd;
}
if (opt.Contains("tausplot")) ProduceToyTauSPlot(wspace_res, wspace, toy_data, idx, opt.Contains("tausyst"));
delete toy_data;
delete wspace;
delete res;
}
}
void ProducePullPlots(TString path, bool saveTuple = true)
{
cout << ">>> ProducePullPlots() start" << endl;
TFileCollection fcoll("fcoll");
fcoll.Add(path);
for (auto& POI: POI_list) {
vector<double> x_val;
for (int file = 0; file < fcoll.GetNFiles(); file++) {
TFileInfo* finfo = (TFileInfo*)fcoll.GetList()->At(file);
TFile fin_res(finfo->GetCurrentUrl()->GetFile());
if ((file+1)%10==0) cout << ">>> Reading [" << file+1 << "/" << fcoll.GetNFiles() << "] " << endl;
RooWorkspace *wspace_res = (RooWorkspace *)fin_res.Get("wspace");
int idx = 0;
while (true) {
RooFitResult *res = (RooFitResult*)wspace_res->obj(Form("fitresult_toy_%d",idx));
if (POI == "EffTau_bs") {
res = (RooFitResult*)wspace_res->obj(Form("fitresult_taubs_toy_%d",idx));
RooFitResult *res_wl = (RooFitResult*)wspace_res->obj(Form("fitresult_taubs_wl_toy_%d",idx));
if (res_wl==NULL || res_wl->status()!=0) break;
}
if (res==NULL || res->status()!=0) break;
idx++;
if (res->status()==0) {
RooRealVar* init = (RooRealVar*)res->floatParsInit().find(POI);
RooRealVar* final = (RooRealVar*)res->floatParsFinal().find(POI);
if (init==NULL || final==NULL) break;
if (POI == "EffTau_bs") {
double var = (final->getVal()-init->getVal())/final->getError();
if (final->getError()<8. && final->getError()>0.02)
x_val.push_back(var);
}else {
double err_hi = fabs(final->getErrorHi());
double err_lo = fabs(final->getErrorLo());
if (err_hi==0.) err_hi = final->getError();
if (err_lo==0.) err_lo = final->getError();
double var = (final->getVal()-init->getVal());
if (var>0.) var /= err_lo;
if (var<0.) var /= err_hi;
if (err_hi>0. && err_lo>0.) x_val.push_back(var);
}
}
}
wspace_res->Delete();
}
if (x_val.size()==0) continue;
RooRealVar pull("pull","",-6.,6.);
RooDataSet *rds_pull = new RooDataSet("rds_pull","",RooArgSet(pull));
for (int idx=0; idx<(int)x_val.size(); idx++) {
pull.setVal(x_val[idx]);
rds_pull->add(RooArgSet(pull));
}
TString title = Form("CMS simluation");
RooPlot* frame = pull.frame(Bins(30), Title(" "));
RooRealVar Mean("Mean", "", 0., -3.0, 3.0);
RooRealVar Sigma("Sigma","", 1., 0.5, 2.0);
RooGaussian model("model","", pull, Mean, Sigma);
RooRealVar SigmaL("SigmaL","", 1., 0.5, 2.0);
RooRealVar SigmaR("SigmaR","", 1., 0.5, 2.0);
RooBifurGauss model2("model2","", pull, Mean, SigmaL, SigmaR);
model.fitTo(*rds_pull,Minos(true));
rds_pull->plotOn(frame);
model.plotOn(frame, LineColor(kBlue), LineWidth(3), NumCPU(NCPU));
frame->SetMinimum(0.);
frame->SetMaximum(frame->GetMaximum()*1.3);
TCanvas* canvas = new TCanvas("canvas", "", 600, 600);
canvas->SetMargin(0.14,0.06,0.13,0.07);
frame->GetYaxis()->SetTitleOffset(1.15);
frame->GetYaxis()->SetTitle("Entries");
frame->GetXaxis()->SetTitleOffset(1.15);
frame->GetXaxis()->SetLabelOffset(0.01);
frame->GetXaxis()->SetTitle(Form("Pull [%s]",POI.Data()));
frame->GetXaxis()->SetTitleSize(0.043);
frame->GetYaxis()->SetTitleSize(0.043);
frame->Draw();
gStyle->SetErrorX(0);
TLatex tex;
tex.SetTextFont(42);
tex.SetTextSize(0.035);
tex.SetTextAlign(11);
tex.SetNDC();
tex.DrawLatex(0.14,0.94,title);
canvas->Update();
TLegend *leg1 = new TLegend(0.20,0.82,0.91,0.91);
leg1->SetTextSize(0.042);
leg1->SetHeader(Form("Pull fit: #mu = %.2f #pm%.2f, #sigma = %.2f #pm%.2f",
Mean.getVal(),Mean.getError(),Sigma.getVal(),Sigma.getError()));
leg1->SetFillColor(kWhite);
leg1->SetLineColor(kWhite);
leg1->SetFillStyle(0);
leg1->Draw();
canvas->Print(Form("fig/pull_%s.pdf",POI.Data()));
delete frame;
delete canvas;
pull.setRange("center",-3.,3.);
frame = pull.frame(Bins(30), Title(" "));
model.fitTo(*rds_pull,Minos(true),Range("center"));
rds_pull->plotOn(frame);
model.plotOn(frame, LineColor(kBlue), LineWidth(3), NumCPU(NCPU));
frame->SetMinimum(0.);
frame->SetMaximum(frame->GetMaximum()*1.3);
canvas = new TCanvas("canvas", "", 600, 600);
canvas->SetMargin(0.14,0.06,0.13,0.07);
frame->GetYaxis()->SetTitleOffset(1.15);
frame->GetYaxis()->SetTitle("Entries");
frame->GetXaxis()->SetTitleOffset(1.15);
frame->GetXaxis()->SetLabelOffset(0.01);
frame->GetXaxis()->SetTitle(Form("Pull [%s]",POI.Data()));
frame->GetXaxis()->SetTitleSize(0.043);
frame->GetYaxis()->SetTitleSize(0.043);
frame->Draw();
gStyle->SetErrorX(0);
tex.DrawLatex(0.14,0.94,title);
canvas->Update();
leg1->SetHeader(Form("Fit [-3,+3]: #mu = %.2f #pm%.2f, #sigma = %.2f #pm%.2f",
Mean.getVal(),Mean.getError(),Sigma.getVal(),Sigma.getError()));
leg1->Draw();
canvas->Print(Form("fig/pull_%s_narrow.pdf",POI.Data()));
delete frame;
delete canvas;
frame = pull.frame(Bins(30), Title(" "));
model2.fitTo(*rds_pull,Minos(true));
rds_pull->plotOn(frame);
model2.plotOn(frame, LineColor(kBlue), LineWidth(3), NumCPU(NCPU));
frame->SetMinimum(0.);
frame->SetMaximum(frame->GetMaximum()*1.3);
canvas = new TCanvas("canvas", "", 600, 600);
canvas->SetMargin(0.14,0.06,0.13,0.07);
frame->GetYaxis()->SetTitleOffset(1.15);
frame->GetYaxis()->SetTitle("Entries");
frame->GetXaxis()->SetTitleOffset(1.15);
frame->GetXaxis()->SetLabelOffset(0.01);
frame->GetXaxis()->SetTitle(Form("Pull [%s]",POI.Data()));
frame->GetXaxis()->SetTitleSize(0.043);
frame->GetYaxis()->SetTitleSize(0.043);
frame->Draw();
gStyle->SetErrorX(0);
tex.DrawLatex(0.14,0.94,title);
canvas->Update();
leg1->SetHeader(Form("#mu = %.2f#pm%.2f, #sigma_{L}/#sigma_{R} = %.2f#pm%.2f/%.2f#pm%.2f",
Mean.getVal(),Mean.getError(),SigmaL.getVal(),SigmaL.getError(),SigmaR.getVal(),SigmaR.getError()));
leg1->Draw();
canvas->Print(Form("fig/pull_%s_bifgauss.pdf",POI.Data()));
delete rds_pull;
delete leg1;
delete frame;
delete canvas;
if (saveTuple) {
TFile *fout = new TFile(Form("fig/pull_%s.root",POI.Data()),"recreate");
TNtupleD *nt = new TNtupleD("nt","","pull");
for (int idx=0; idx<(int)x_val.size(); idx++) {
nt->Fill(&x_val[idx]);
}
nt->Write();
fout->Close();
delete fout;
}
}
}
void ProduceMeanErrorPlots(TString path, bool saveTuple = true)
{
cout << ">>> ProduceMeanErrorPlots() start" << endl;
TFileCollection fcoll("fcoll");
fcoll.Add(path);
for (auto& POI: POI_list) {
vector<double> x_val[6]; // mean, para_err, err_hi, err_lo, sys_hi, sys_lo
for (int file = 0; file < fcoll.GetNFiles(); file++) {
TFileInfo* finfo = (TFileInfo*)fcoll.GetList()->At(file);
TFile fin_res(finfo->GetCurrentUrl()->GetFile());
if ((file+1)%10==0) cout << ">>> Reading [" << file+1 << "/" << fcoll.GetNFiles() << "] " << endl;
RooWorkspace *wspace_res = (RooWorkspace *)fin_res.Get("wspace");
int idx = 0;
while (true) {
RooFitResult *res = (RooFitResult*)wspace_res->obj(Form("fitresult_toy_%d",idx));
if (POI == "EffTau_bs") {
res = (RooFitResult*)wspace_res->obj(Form("fitresult_taubs_toy_%d",idx));
RooFitResult *res_wl = (RooFitResult*)wspace_res->obj(Form("fitresult_taubs_wl_toy_%d",idx));
if (res_wl==NULL || res_wl->status()!=0) break;
}
if (res==NULL || res->status()!=0) break;
idx++;
if (res->status()==0) {
RooRealVar* final = (RooRealVar*)res->floatParsFinal().find(POI);
if (final==NULL) break;
if (POI == "EffTau_bs")
if (final->getError()>=8. || final->getError()<=0.02) continue;
x_val[0].push_back(final->getVal());
x_val[1].push_back(final->getError());
x_val[2].push_back(final->getErrorHi());
x_val[3].push_back(final->getErrorLo());
if (POI == "EffTau_bs") {
RooFitResult *res_syst = (RooFitResult*)wspace_res->obj(Form("fitresult_taubs_syst_toy_%d",idx));
if (res_syst!=NULL) {
RooRealVar* syst = (RooRealVar*)res_syst->floatParsFinal().find(POI);
x_val[4].push_back(syst->getErrorHi());
x_val[5].push_back(syst->getErrorLo());
}
}
}
}
wspace_res->Delete();
}
TString title = Form("CMS simluation");
vector<TString> types = {"mean","error","errorhi","errorlo","systhi","systlo"};
vector<TString> xtitles = {"Fitted","Error","Error(+)","Error(-)","Sys. Error(+)","Sys. Error(-)"};
for(int type=0; type<6; type++) {
if (x_val[type].size()==0) continue;
sort(x_val[type].begin(),x_val[type].end());
double x_min = x_val[type][x_val[type].size()*1/100];
double x_max = x_val[type][x_val[type].size()*99/100];
//double x_min = TMath::MinElement(x_val[type].size(),x_val[type].data());
//double x_max = TMath::MaxElement(x_val[type].size(),x_val[type].data());
double x_mean = TMath::Mean(x_val[type].size(),x_val[type].data());
double x_rms = TMath::RMS(x_val[type].size(),x_val[type].data());
double x_median = TMath::Median(x_val[type].size(),x_val[type].data());
TH1D* frame = new TH1D("frame","", 24, x_min-(x_max-x_min)*0.1, x_max+(x_max-x_min)*0.1);
for(auto& val : x_val[type]) frame->Fill(val);
frame->SetMinimum(0.);
frame->SetStats(false);
frame->SetFillColor(50);
frame->SetMaximum(frame->GetMaximum()*1.3);
TCanvas* canvas = new TCanvas("canvas", "", 600, 600);
canvas->SetMargin(0.14,0.06,0.13,0.07);
frame->GetYaxis()->SetTitleOffset(1.15);
frame->GetYaxis()->SetTitle("Entries");
frame->GetXaxis()->SetTitleOffset(1.15);
frame->GetXaxis()->SetLabelOffset(0.01);
frame->GetXaxis()->SetTitle(Form("%s [%s]",xtitles[type].Data(),POI.Data()));
frame->GetXaxis()->SetTitleSize(0.043);
frame->GetYaxis()->SetTitleSize(0.043);
frame->Draw();
gStyle->SetErrorX(0);
TLatex tex;
tex.SetTextFont(42);
tex.SetTextSize(0.035);
tex.SetTextAlign(11);
tex.SetNDC();
tex.DrawLatex(0.14,0.94,title);
canvas->Update();
TLegend *leg1 = new TLegend(0.20,0.82,0.91,0.91);
leg1->SetTextSize(0.042);
leg1->SetHeader(Form("median: %.3g, mean: %.3g, rms: %.3g",x_median,x_mean,x_rms));
leg1->SetFillColor(kWhite);
leg1->SetLineColor(kWhite);
leg1->Draw();
canvas->Print(Form("fig/toy_%s_%s.pdf",types[type].Data(),POI.Data()));
delete leg1;
delete frame;
delete canvas;
}
if (saveTuple) {
TFile *fout = new TFile(Form("fig/meanerr_%s.root",POI.Data()),"recreate");
TNtupleD *nt = new TNtupleD("nt","","mean:error:errorhi:errorlo:systhi:systlo");
for (int idx=0; idx<(int)x_val[0].size(); idx++) {
double buffer[6];
for(int type=0; type<6; type++) {
if ((int)x_val[type].size()>idx) buffer[type] = x_val[type][idx];
else buffer[type] = 0.;
}
nt->Fill(buffer);
}
nt->Write();
fout->Close();
delete fout;
}
}
}
void ProduceSignificancePlots(TString path, bool saveTuple = true)
{
cout << ">>> ProduceSignificancePlots() start" << endl;
TFileCollection fcoll("fcoll");
fcoll.Add(path);
vector<double> x_val[2];
for (int file = 0; file < fcoll.GetNFiles(); file++) {
TFileInfo* finfo = (TFileInfo*)fcoll.GetList()->At(file);
TFile fin_res(finfo->GetCurrentUrl()->GetFile());
if ((file+1)%10==0) cout << ">>> Reading [" << file+1 << "/" << fcoll.GetNFiles() << "] " << endl;
RooWorkspace *wspace_res = (RooWorkspace *)fin_res.Get("wspace");
int idx = 0;
while (true) {
RooFitResult *res = (RooFitResult*)wspace_res->obj(Form("fitresult_toy_%d",idx));
RooFitResult *res_zerobd = (RooFitResult*)wspace_res->obj(Form("fitresult_zerobd_toy_%d",idx));
RooFitResult *res_zerobs = (RooFitResult*)wspace_res->obj(Form("fitresult_zerobs_toy_%d",idx));
if (res==NULL || res_zerobd==NULL || res_zerobs==NULL) break;
if (res->status()==0 && res_zerobd->status()==0)
x_val[0].push_back(sqrt(max(0.,res_zerobd->minNll() - res->minNll())*2.));
if (res->status()==0 && res_zerobs->status()==0)
x_val[1].push_back(sqrt(max(0.,res_zerobs->minNll() - res->minNll())*2.));
idx++;