#ifndef BASIC_ANALYSIS #define BASIC_ANALYSIS #include #include #include #include #include #include #include "TTree.h" #include "RooHist.h" #include "constants.h" std::pair DivWithErr(double x, double dx, double y, double dy) { double err_x = (1 / y) * dx; double err_y = - (x / (y*y)) * dy; return std::make_pair(x / y, TMath::Sqrt((TMath::Sq(err_x) + TMath::Sq(err_y)))); } std::pair MultWithErr(double x, double dx, double y, double dy) { double err_x = y * dx; double err_y = - x * dy; return std::make_pair(x * y, TMath::Sqrt((TMath::Sq(err_x) + TMath::Sq(err_y)))); } double RoundUp(double x, int n = 0) { if(std::abs(x) > std::numeric_limits::max() / n) // v * p would overflow throw std::overflow_error("rounding would overflow"); const double multiplier = std::pow(10.0, n); return std::ceil(x * multiplier) / multiplier; } double RoundDown(double x, int n = 0) { if(std::abs(x) > std::numeric_limits::max() / n) // v * p would overflow throw std::overflow_error("rounding would overflow"); const double multiplier = std::pow(10.0, n); return std::floor(x * multiplier) / multiplier; } double Round(double x, int n = 0) { if(std::abs(x) > std::numeric_limits::max() / n) // v * p would overflow throw std::overflow_error("rounding would overflow"); const double multiplier = std::pow(10.0, n); return std::round(x * multiplier) / multiplier; } std::string ErrToStr(double val, double err, int n) { return TString::Format("%.*f #pm %.*f", n, Round(val, n), n, RoundUp(err, n)).Data(); } std::string ErrToStr(std::pair val_err, int n) { return ErrToStr(val_err.first, val_err.second, n); } std::pair CalcSignificance(double sig_val, double sig_err, double bkg_val, double bkg_err) { double significance_val = sig_val / TMath::Sqrt(sig_val + bkg_val); double err_prop_sig = (sig_val + 2 * bkg_val) / (2 * TMath::Power((sig_val + bkg_val), (3 / 2))); double err_prop_bkg = -sig_val / (2 * TMath::Power((sig_val + bkg_val), (3 / 2))); double significance_err = TMath::Sqrt(TMath::Sq(err_prop_sig * sig_err) + TMath::Sq(err_prop_bkg * bkg_err)); return std::make_pair(significance_val, significance_err); } class FourVect { private: Float_t px, py, pz, energy; Float_t *PtrPX() { return &px; } Float_t *PtrPY() { return &py; } Float_t *PtrPZ() { return &pz; } Float_t *PtrEnergy() { return &energy; } public: static FourVect *Init(TTree *tree, const char *particle) { FourVect *v = new FourVect{}; tree->SetBranchAddress(TString::Format("%s_PX", particle).Data(), v->PtrPX()); tree->SetBranchAddress(TString::Format("%s_PY", particle).Data(), v->PtrPY()); tree->SetBranchAddress(TString::Format("%s_PZ", particle).Data(), v->PtrPZ()); tree->SetBranchAddress(TString::Format("%s_ENERGY", particle).Data(), v->PtrEnergy()); return v; } TLorentzVector LorentzVector() { return TLorentzVector(px, py, pz, energy); } TLorentzVector LorentzVector(double sub_mass) { TVector3 momentum(px, py, pz); float energy = TMath::Sqrt(TMath::Sq(sub_mass) + momentum.Mag2()); return TLorentzVector(momentum, energy); } std::string ToString() { return TString::Format("(%f, %f, %f, %f)", px, py, pz, energy).Data(); } }; struct FittedParam { std::string title; std::string name; double value; double error; bool at_limit; bool constant; int decimals; bool print_const; bool ignore_print; FittedParam(RooRealVar var, int decimals, bool print_const = false, bool ignore_print = false) { this->title = var.GetTitle(); this->name = var.GetName(); double val = var.getVal(); this->value = val; this->constant = var.isConstant(); this->print_const = print_const; this->ignore_print = ignore_print; if (!this->constant) { this->error = var.getError(); this->at_limit = ((val == var.getMin()) || (val == var.getMax())); } else { this->error = 0.; } this->decimals = decimals; } FittedParam(std::string name, std::string title, double value, double err, int decimals, bool ignore_print = false) { this->title = title; this->name = name; this->value = value; this->error = err; this->decimals = decimals; this->constant = false; this->at_limit = false; this->ignore_print = ignore_print; } std::string ToString(bool latex = false) const { if (this->constant) { return TString::Format("%s = %.*f (c)", this->title.c_str(), this->decimals, this->value).Data(); } else { if (this->error == 0) { return TString::Format("%s = %.*f", this->title.c_str(), this->decimals, this->value).Data(); } else { return TString::Format("%s = %.*f %s %.*f", this->title.c_str(), this->decimals, this->value, (latex ? "\\pm" : "#pm"), this->decimals, this->error).Data(); } } } }; struct ShapeParamters { double alpha_left; double n_left; double alpha_right; double n_right; double sigma_lr; std::string ToString() { return TString::Format("aL: %.2f\nnL: %.2f\naR: %.2f\nnR: %.2f\nS: %.2f\n", this->alpha_left, this->n_left, this->alpha_right, this->n_right, this->sigma_lr).Data(); } }; struct RooFitSummary { RooPlot *fit_histogram; RooPlot *pull_histogram; std::map pdf_names; std::pair signal_yield; std::pair background_yield; std::vector fitted_params; ShapeParamters shape_parameters; }; void DrawInDefaultCanvas(TH1 *histogram, const char *folder, double margin_left = 0.1, Option_t *option = "") { std::filesystem::create_directory(TString::Format("output_files/analysis/%s", folder).Data()); TString name = TString::Format("%s_canvas", histogram->GetName()); TCanvas *c = new TCanvas(name, histogram->GetName(), 0, 0, 800, 600); c->SetLeftMargin(margin_left); histogram->SetStats(0); histogram->Draw(option); c->Draw(); c->SaveAs(TString::Format("output_files/analysis/%s/%s.pdf", folder, name.Data()).Data()); } void DrawInDefaultCanvasStacked(std::vector histograms, std::vector colors, std::vector fill_style, const char *folder, const char* title, double margin_left = 0.12, Option_t *option = "") { std::filesystem::create_directory(TString::Format("output_files/analysis/%s", folder).Data()); TString name = TString::Format("%s_stack_canvas", histograms[0]->GetName()); TCanvas *c = new TCanvas(name, histograms[0]->GetName(), 0, 0, 800, 600); c->SetLeftMargin(margin_left); Double_t max = 0; for (size_t i = 0; i < histograms.size(); i++) { if (histograms[i]->GetEntries() > max) { max = histograms[i]->GetEntries(); } } TString stack_name = TString::Format("%s_stack", histograms[0]->GetName()); TString stack_title = TString::Format("%s;%s;#Events normed to 1/%.0f", title, histograms[0]->GetXaxis()->GetTitle(), max); std::string drwopt_2 = std::string(option).empty() ? "HIST" : TString::Format("%s HIST", option).Data(); auto stack = new THStack(stack_name, stack_title); for (size_t i = 0; i < histograms.size(); i++) { const Double_t scaling_factor = 1.; auto hist_clone = (TH1 *)histograms[i]->Clone(TString::Format("%s_clone", histograms[i]->GetName())); hist_clone->Scale(scaling_factor / max); hist_clone->SetLineColor(colors[i]); // hist_clone->SetMaximum(scaling_factor + (scaling_factor * 0.05)); // hist_clone->SetMaximum(max + (max * 0.05)); hist_clone->SetMinimum(0.); hist_clone->SetStats(0); if (fill_style[i] != 0) { hist_clone->SetFillStyle(fill_style[i]); hist_clone->SetFillColor(colors[i]); } if (i > 0) { stack->Add(hist_clone, drwopt_2.c_str()); } else { stack->Add(hist_clone, drwopt_2.c_str()); } } stack->Draw("NOSTACK"); c->BuildLegend(0.55, 0.70, 0.87, 0.89); c->Draw(); c->SaveAs(TString::Format("output_files/analysis/%s/%s.pdf", folder, name.Data()).Data()); } void DrawInDefaultCanvas(RooPlot *rooPlot, const char *folder, double margin_left = 0, Option_t *option = "") { std::filesystem::create_directory(TString::Format("output_files/analysis/%s", folder).Data()); TString name = TString::Format("%s_canvas", rooPlot->GetName()); TCanvas *c = new TCanvas(name, rooPlot->GetName(), 0, 0, 800, 600); c->SetLeftMargin(margin_left); rooPlot->Draw(option); c->Draw(); c->SaveAs(TString::Format("output_files/analysis/%s/%s.pdf", folder, name.Data()).Data()); } void PrintStyles(RooPlot *plt) { auto Xaxis = plt->GetXaxis(); auto Yaxis = plt->GetYaxis(); std::cout << "## Styles for plot " << plt->GetName() << std::endl; std::cout << "## X axis\n" << "Label Size: " << Xaxis->GetLabelSize() << ",\n" << "Label Offset: " << Xaxis->GetLabelOffset() << ",\n" << "Title Size: " << Xaxis->GetTitleSize() << ",\n" << "Title Offset: " << Xaxis->GetTitleOffset() << "." << std::endl; std::cout << "## Y axis\n" << "Label Size: " << Yaxis->GetLabelSize() << ",\n" << "Label Offset: " << Yaxis->GetLabelOffset() << ",\n" << "Title Size: " << Yaxis->GetTitleSize() << ",\n" << "Title Offset: " << Yaxis->GetTitleOffset() << "." << std::endl; } void DrawInDefaultCanvas(RooFitSummary fitSummary, const char *folder) { std::filesystem::create_directory(TString::Format("output_files/analysis/%s", folder).Data()); TString name = TString::Format("%s_canvas", fitSummary.fit_histogram->GetName()); TCanvas *c = new TCanvas(name, fitSummary.fit_histogram->GetTitle(), 0, 0, 800, 600); Double_t xlow, ylow, xup, yup; c->GetPad(0)->GetPadPar(xlow, ylow, xup, yup); c->Divide(1, 2); Double_t upPad_ylow = ylow + 0.25 * (yup - ylow); Double_t dwPad_yup = ylow + 0.25 * (yup - ylow); TVirtualPad *upPad = c->GetPad(1); upPad->SetPad(xlow, upPad_ylow, xup, yup); TVirtualPad *dwPad = c->GetPad(2); dwPad->SetPad(xlow, ylow, xup, dwPad_yup); dwPad->SetTopMargin(0); Double_t upPad_area = (yup - upPad_ylow) * (xup - xlow); Double_t dwPad_area = (dwPad_yup - ylow) * (xup - xlow); // std::cout << "### UP AREA: " << upPad_area << " LOW AREA: " << dwPad_area << std::endl; const Double_t pull_title_size = 0.09; const Double_t pull_label_size = 0.09; Double_t fit_title_size = (pull_title_size * dwPad_area) / upPad_area; Double_t fit_label_size = (pull_label_size * dwPad_area) / upPad_area; c->cd(1); auto fit_Xaxis = fitSummary.fit_histogram->GetXaxis(); auto fit_Yaxis = fitSummary.fit_histogram->GetYaxis(); fit_Xaxis->SetLabelOffset(0.02); fit_Xaxis->SetLabelSize(fit_label_size); fit_Xaxis->SetTitleOffset(1.4); fit_Xaxis->SetTitleSize(fit_title_size); fit_Yaxis->SetLabelOffset(0.01); fit_Yaxis->SetLabelSize(fit_label_size); fit_Yaxis->SetTitleSize(fit_title_size); fit_Yaxis->SetTitleOffset(0); fitSummary.fit_histogram->Draw(); TLegend *leg1 = new TLegend(0.55, 0.45, 0.87, 0.89); leg1->SetFillColor(kWhite); leg1->SetLineColor(kWhite); for (const auto &[name, title] : fitSummary.pdf_names) { leg1->AddEntry(fitSummary.fit_histogram->findObject(name.c_str()), title.c_str(), "LP"); } for (const auto &par : fitSummary.fitted_params) { if ((!par.ignore_print) && ((!par.constant) || par.print_const)) { leg1->AddEntry((TObject *)0, par.ToString().c_str(), ""); } } leg1->Draw(); c->cd(2); Double_t pull_min = fitSummary.pull_histogram->GetMinimum(); Double_t pull_max = fitSummary.pull_histogram->GetMaximum(); // std::cout << "### (" << fitSummary.pull_histogram->GetName() << ") PULL MIN: " << pull_min << " PULL MAX: " << pull_max << std::endl; double bound = 0; if (TMath::Abs(pull_min) > TMath::Abs(pull_max)) { bound = TMath::Abs(pull_min); } else { bound = TMath::Abs(pull_max); } auto pull_Xaxis = fitSummary.pull_histogram->GetXaxis(); auto pull_Yaxis = fitSummary.pull_histogram->GetYaxis(); pull_Xaxis->SetLabelOffset(0.02); pull_Xaxis->SetLabelSize(pull_label_size); pull_Xaxis->SetTitleSize(pull_title_size); pull_Xaxis->SetTitle(""); pull_Yaxis->SetLabelOffset(0.01); pull_Yaxis->SetLabelSize(pull_label_size); pull_Yaxis->SetTitleSize(pull_title_size); pull_Yaxis->SetTitleOffset(0.45); pull_Yaxis->SetTitle("Pull Distribution"); fitSummary.pull_histogram->SetTitle(""); fitSummary.pull_histogram->SetMaximum(bound); fitSummary.pull_histogram->SetMinimum(-bound); fitSummary.pull_histogram->Draw(); auto line_mid = new TLine(B_MASS_VAR_MIN, 0, B_MASS_VAR_MAX, 0); line_mid->SetLineColor(kOrange + 4); line_mid->Draw(); auto line_up = new TLine(B_MASS_VAR_MIN, bound / 2, B_MASS_VAR_MAX, bound / 2); line_up->SetLineStyle(kDashed); line_up->SetLineColor(kOrange + 4); line_up->Draw(); auto line_low = new TLine(B_MASS_VAR_MIN, -bound / 2, B_MASS_VAR_MAX, -bound / 2); line_low->SetLineStyle(kDashed); line_low->SetLineColor(kOrange + 4); line_low->Draw(); c->Draw(); c->SaveAs(TString::Format("output_files/analysis/%s/%s.pdf", folder, name.Data()).Data()); } void PrintProgress(const char *title, unsigned int total, unsigned int every, unsigned int current) { if ((current + 1) % every == 0 || current + 1 == total) { std::cout << "[" << title << "] Processed event: " << current + 1 << " (" << TString::Format("%.2f", ((double)(current + 1) / (double)total) * 100.) << "%)" << std::endl; } } RooPlot *CreateRooFitHistogram(TH1D *hist) { RooRealVar roo_var_mass("var_mass", "B Mass Variable", B_MASS_VAR_MIN, B_MASS_VAR_MAX); roo_var_mass.setRange("fitting_range", B_MASS_FIT_MIN, B_MASS_FIT_MAX); RooDataHist roohist_B_M("roohist_B_M", "B Mass Histogram", roo_var_mass, RooFit::Import(*hist)); RooPlot *roo_frame_mass = roo_var_mass.frame(RooFit::Title(hist->GetTitle()), RooFit::Name(TString::Format("%s_rplt", hist->GetName()))); roohist_B_M.plotOn(roo_frame_mass, RooFit::Binning(B_MASS_HIST_BINS), RooFit::Name("B Mass Distribution")); roo_frame_mass->GetXaxis()->SetTitle(hist->GetXaxis()->GetTitle()); return roo_frame_mass; } RooFitSummary CreateRooDataSetAndFitCB(TTree *dataSet, TString var_name, TString xAxis, bool hasExpBkg, bool useExtShape, ShapeParamters extShape, bool const_sigma = false, Double_t fit_low = 0, Double_t fit_up = 0) { auto suffix_name = [name = dataSet->GetName()](const char *text) { return TString::Format("%s_%s", text, name); }; Double_t fitRangeUp = fit_low == 0 ? B_MASS_FIT_MIN : fit_low; Double_t fitRangeLow = fit_up == 0 ? B_MASS_FIT_MAX : fit_up; RooRealVar roo_var_mass(var_name, "B Mass Variable", B_MASS_VAR_MIN, B_MASS_VAR_MAX); const char *fitting_range_name = "fitting_range"; roo_var_mass.setRange(fitting_range_name, fitRangeUp, fitRangeLow); const char *draw_range_name = "draw_range"; roo_var_mass.setRange(draw_range_name, B_MASS_VAR_MIN, B_MASS_VAR_MAX); TString dataset_name = suffix_name("roodataset_B_M"); // RooDataHist roodataset_B_M(hist_name, "B Mass Histogram", roo_var_mass, RooFit::Import(*hist)); RooDataSet roodataset_B_M(dataset_name, "B Mass Data Set", roo_var_mass, RooFit::Import(*dataSet)); RooPlot *roo_frame_mass = roo_var_mass.frame(RooFit::Title(dataSet->GetTitle()), RooFit::Name(TString::Format("%s_rplt", dataSet->GetName()))); roodataset_B_M.plotOn(roo_frame_mass, RooFit::Name(dataset_name)); roo_frame_mass->GetXaxis()->SetTitle(xAxis); // Crystal Ball for Signal RooRealVar var_mass_x0(suffix_name("var_mass_x0"), "#mu", 5278., 5170., 5500.); RooRealVar var_mass_sigmaLR(suffix_name("var_mass_sigmaLR"), "#sigma_{LR}", 16., 5., 40.); RooRealVar var_mass_alphaL(suffix_name("var_mass_alphaL"), "#alpha_{L}", 2., 0., 4.); RooRealVar var_mass_nL(suffix_name("var_mass_nL"), "n_{L}", 5., 0., 15.); RooRealVar var_mass_alphaR(suffix_name("var_mass_alphaR"), "#alpha_{R}", 2., 0., 4.); RooRealVar var_mass_nR(suffix_name("var_mass_nR"), "n_{R}", 5., 0., 15.); if (useExtShape) { if (extShape.alpha_left != 0.) { var_mass_alphaL.setConstant(true); var_mass_alphaL.setVal(extShape.alpha_left); } if (extShape.n_left != 0.) { var_mass_nL.setConstant(true); var_mass_nL.setVal(extShape.n_left); } if (extShape.alpha_right != 0.) { var_mass_alphaR.setConstant(true); var_mass_alphaR.setVal(extShape.alpha_right); } if (extShape.n_right != 0.) { var_mass_nR.setConstant(true); var_mass_nR.setVal(extShape.n_right); } if (extShape.sigma_lr != 0. && const_sigma) { var_mass_sigmaLR.setConstant(true); var_mass_sigmaLR.setVal(extShape.sigma_lr); } } TString signal_name = suffix_name("sig_cb"); RooCrystalBall sig_cb(signal_name, "CB Signal", roo_var_mass, var_mass_x0, var_mass_sigmaLR, var_mass_alphaL, var_mass_nL, var_mass_alphaR, var_mass_nR); std::vector fitted_params{}; std::map pdf_names{}; pdf_names[signal_name.Data()] = sig_cb.getTitle().Data(); TString pull_compare_name{}; double sig_val = 0.; double sig_err = 0.; double bkg_val = 0.; double bkg_err = 0.; if (hasExpBkg) { // Exponential for Background RooRealVar var_mass_bkg_c(suffix_name("var_mass_bkg_c"), "#lambda", -0.0014, -0.004, -0.000); TString background_name = suffix_name("bgk_exp"); RooExponential bkg_exp(background_name, "Exp Background", roo_var_mass, var_mass_bkg_c); pdf_names[background_name.Data()] = bkg_exp.getTitle().Data(); RooRealVar var_mass_nsig(suffix_name("nsig"), "N_{Sig}", 0., dataSet->GetEntries()); RooRealVar var_mass_nbkg(suffix_name("nbkg"), "N_{Bkg}", 0., dataSet->GetEntries()); TString fitted_pdf_name = suffix_name("sigplusbkg"); RooAddPdf fitted_pdf(fitted_pdf_name, "Sig + Bkg", RooArgList(sig_cb, bkg_exp), RooArgList(var_mass_nsig, var_mass_nbkg)); pdf_names[fitted_pdf_name.Data()] = fitted_pdf.getTitle().Data(); RooFitResult *fitres = fitted_pdf.fitTo(roodataset_B_M, RooFit::Save(), RooFit::PrintLevel(-1), RooFit::Range(fitting_range_name)); // sigplusbkg.plotOn(roo_frame_mass, RooFit::VisualizeError(*fitres, 1), RooFit::FillColor(kOrange + 1), RooFit::FillStyle(3144)); fitted_pdf.plotOn(roo_frame_mass, RooFit::LineColor(kRed), RooFit::LineStyle(kSolid), RooFit::Range(draw_range_name), RooFit::Name(fitted_pdf_name)); fitted_pdf.plotOn(roo_frame_mass, RooFit::Components(RooArgSet(bkg_exp)), RooFit::LineColor(kBlue - 7), RooFit::LineStyle(kDashed), RooFit::Range(draw_range_name), RooFit::Name(background_name)); fitted_pdf.plotOn(roo_frame_mass, RooFit::Components(RooArgSet(sig_cb)), RooFit::LineColor(kRed - 7), RooFit::LineStyle(kDashed), RooFit::Range(draw_range_name), RooFit::Name(signal_name)); fitted_params.push_back(FittedParam(var_mass_nsig, 0)); fitted_params.push_back(FittedParam(var_mass_nbkg, 0)); double mu_val = var_mass_x0.getVal(); double sigma_val = var_mass_sigmaLR.getVal(); sig_val = var_mass_nsig.getVal(); sig_err = var_mass_nsig.getError(); bkg_val = var_mass_nbkg.getVal(); bkg_err = var_mass_nbkg.getError(); double sig_bkg_sum_val = sig_val + bkg_val; double sig_bkg_sum_err = TMath::Sqrt(TMath::Sq(sig_err) + TMath::Sq(bkg_err)); const int sigma_space = 2; double int_lo = mu_val - sigma_space * sigma_val; double int_up = mu_val + sigma_space * sigma_val; roo_var_mass.setRange("peak_integral_range", int_lo, int_up); std::cout << "#### Integral Over: " << int_lo << " -> " << int_up << std::endl; auto bkg_int = bkg_exp.createIntegral(roo_var_mass, RooFit::NormSet(roo_var_mass), RooFit::Range("peak_integral_range")); auto bkg_yield_under_sig = std::make_pair(bkg_int->getVal() * sig_bkg_sum_val, bkg_int->getVal() * sig_bkg_sum_err); fitted_params.push_back(FittedParam("bkg_int_sig", TString::Format("N_{Bkg,%d#sigma}", sigma_space).Data(), bkg_yield_under_sig.first, bkg_yield_under_sig.second, 0)); auto significance = CalcSignificance(sig_val, sig_err, bkg_val, bkg_err); auto sig_over_bkg_3sig = DivWithErr(sig_val, sig_err, bkg_yield_under_sig.first, bkg_yield_under_sig.second); auto sig_over_bkg_full = DivWithErr(sig_val, sig_err, bkg_val, bkg_err); // fitted_params.push_back(FittedParam("significance", "N_{Sig}/#sqrt{N_{Sig} + N_{Bkg}}", significance.first, significance.second, 2)); fitted_params.push_back(FittedParam("sig_over_bkg", "N_{Sig}/N_{Bkg}", sig_over_bkg_full.first, sig_over_bkg_full.second, 2, true)); fitted_params.push_back(FittedParam("sig_over_bkg", TString::Format("N_{Sig}/N_{Bkg,%d#sigma}", sigma_space).Data(), sig_over_bkg_3sig.first, sig_over_bkg_3sig.second, 2, true)); fitted_params.push_back(FittedParam(var_mass_bkg_c, 5)); pull_compare_name = fitted_pdf_name; } else { RooFitResult *fitres = sig_cb.fitTo(roodataset_B_M, RooFit::Save(), RooFit::PrintLevel(-1), RooFit::Range(fitting_range_name)); // sigplusbkg.plotOn(roo_frame_mass, RooFit::VisualizeError(*fitres, 1), RooFit::FillColor(kOrange + 1), RooFit::FillStyle(3144)); sig_cb.plotOn(roo_frame_mass, RooFit::LineColor(kRed), RooFit::LineStyle(kSolid), RooFit::Range(draw_range_name), RooFit::Name(signal_name)); pull_compare_name = signal_name; } fitted_params.push_back(FittedParam(var_mass_x0, 2)); fitted_params.push_back(FittedParam(var_mass_sigmaLR, 2, true)); fitted_params.push_back(FittedParam(var_mass_alphaL, 2)); fitted_params.push_back(FittedParam(var_mass_nL, 2)); fitted_params.push_back(FittedParam(var_mass_alphaR, 2)); fitted_params.push_back(FittedParam(var_mass_nR, 2)); RooPlot *roo_frame_pull = roo_var_mass.frame(RooFit::Title("Pull Distribution"), RooFit::Name(TString::Format("%s_pull_rplt", dataSet->GetName()))); RooHist *pull_hist = roo_frame_mass->pullHist(dataset_name, pull_compare_name); roo_frame_pull->addPlotable(pull_hist, "P"); // Double_t pull_min = pull_hist->GetMinimum(); // Double_t pull_max = pull_hist->GetMaximum(); // std::cout << "##### (" << pull_hist->GetName() << ") PULL MIN: " << pull_min << " PULL MAX: " << pull_max << std::endl; return RooFitSummary{ roo_frame_mass, roo_frame_pull, pdf_names, std::make_pair(sig_val, sig_err), std::make_pair(bkg_val, bkg_err), fitted_params, ShapeParamters{ var_mass_alphaL.getVal(), var_mass_nL.getVal(), var_mass_alphaR.getVal(), var_mass_nR.getVal(), var_mass_sigmaLR.getVal()}}; } bool InRange(double value, double center, double low_intvl, double up_intvl) { return center - low_intvl < value && value < center + up_intvl; } bool InRange(double value, double center, double intvl) { return InRange(value, center, intvl, intvl); } #endif