TCanvas* pHitSpecPos( ) { TCanvas* c = new TCanvas("cHitSpecPos","cHitSpecPos",1000,1100); c->Divide(2,2); TVirtualPad* p; TH2D *h; TText t; t.SetTextColor(4); p =c->cd(1); p->SetLogy(); p->SetGrid(1,0); h = (TH2D*)gROOT->FindObject("hHitSpec_PtVsPhi_BarMinus"); h->GetYaxis()->SetRange(4,33); h->DrawCopy("box"); t.DrawTextNDC(0.17,0.15, "BARREL MU MINUS"); p =c->cd(2); p->SetLogy(); p->SetGrid(1,0); h = (TH2D*)gROOT->FindObject("hHitSpec_PtVsPhi_BarPlus"); h->GetYaxis()->SetRange(4,32); h->DrawCopy("box"); t.DrawTextNDC(0.17,0.15, "BARREL MU PLUS"); p =c->cd(3); p->SetLogy(); p->SetGrid(1,0); h = (TH2D*)gROOT->FindObject("hHitSpec_PtVsPhi_EndMinus"); h->GetYaxis()->SetRange(4,32); h->DrawCopy("box"); t.DrawTextNDC(0.17,0.15, "ENDCAP MU MINUS"); p =c->cd(4); p->SetLogy(); p->SetGrid(1,0); h = (TH2D*)gROOT->FindObject("hHitSpec_PtVsPhi_EndPlus"); h->GetYaxis()->SetRange(4,32); h->DrawCopy("box"); t.DrawTextNDC(0.17,0.15, "ENDCAP MU PLUS"); return c; }
TCanvas* pHitSpecPosGen( ) { TCanvas* c = new TCanvas("cHitSpecPosGen","cHitSpecPosGen",1200,600); c->Divide(2,1); TVirtualPad* p; TH2D *h; TH2D *hAtPhi0; TText t; t.SetTextColor(4); p =c->cd(1); p->SetLogy(); p->SetGrid(0,1); h = (TH2D*)gROOT->FindObject("hHitSpec_PtVsPhiGen_Minus"); hAtPhi0 = (TH2D*)gROOT->FindObject("hHitSpec_PtVsPhiGenAtPhi0_Minus"); h->GetYaxis()->SetRange(4,33); h->GetXaxis()->SetNdivisions(505); h->GetXaxis()->SetLabelSize(0.04); h->DrawCopy("box"); hAtPhi0->SetLineColor(2); hAtPhi0->DrawCopy("box same"); t.DrawTextNDC(0.17,0.15, "BARREL MU MINUS"); std::cout <<h->GetTitle() << std::endl; for (int iy = 1; iy <=h->GetNbinsY(); iy++) { std::cout <<" pt: " << h->GetYaxis()->GetBinLowEdge(iy); double xmin=100.; double xAtMax = 0.; double valAtMax = 0.; double xmax=-100.; for (int ix = 1; ix <=h->GetNbinsX(); ix++) { double val = h->GetBinContent(ix,iy); double xbmin = h->GetXaxis()->GetBinLowEdge(ix); double xcent = h->GetXaxis()->GetBinCenter(ix); double xbmax = h->GetXaxis()->GetBinUpEdge(ix); if (val > valAtMax) { valAtMax = val; xAtMax = xcent; } if (val > 1 && (xbmin < xmin)) xmin = xbmin; if (val > 1 && (xbmax > xmax)) xmax = xbmax; } std::cout <<" set DPHI0 = "<<1.025-xAtMax <<"; set DPHI_MARGIN = " <<std::max( (xAtMax-xmin), (xmax-xAtMax)) <<";" << std::endl; } p =c->cd(2); p->SetLogy(); p->SetGrid(1,1); h = (TH2D*)gROOT->FindObject("hHitSpec_PtVsPhiGen_Plus"); hAtPhi0 = (TH2D*)gROOT->FindObject("hHitSpec_PtVsPhiGenAtPhi0_Plus"); h->GetYaxis()->SetRange(4,32); h->GetXaxis()->SetNdivisions(505); h->GetXaxis()->SetLabelSize(0.04); h->DrawCopy("box"); hAtPhi0->SetLineColor(2); hAtPhi0->DrawCopy("box same"); t.DrawTextNDC(0.17,0.15, "BARREL MU PLUS"); std::cout <<h->GetTitle() << std::endl; for (int iy = 1; iy <=h->GetNbinsY(); iy++) { std::cout <<" pt: " << h->GetYaxis()->GetBinLowEdge(iy); double xmin=100.; double xAtMax = 0.; double valAtMax = 0.; double xmax=-100.; for (int ix = 1; ix <=h->GetNbinsX(); ix++) { double val = h->GetBinContent(ix,iy); double xbmin = h->GetXaxis()->GetBinLowEdge(ix); double xcent = h->GetXaxis()->GetBinCenter(ix); double xbmax = h->GetXaxis()->GetBinUpEdge(ix); if (val > valAtMax) { valAtMax = val; xAtMax = xcent; } if (val > 1 && (xbmin < xmin)) xmin = xbmin; if (val > 1 && (xbmax > xmax)) xmax = xbmax; } std::cout <<" set DPHI0 = "<<1.025-xAtMax <<"; set DPHI_MARGIN = " <<std::max( (xAtMax-xmin), (xmax-xAtMax)) <<";" << std::endl; } return c; }
void EstimateBg_76X(bool save=0, std::string in = "", std::string out = "/afs/cern.ch/user/j/jkarancs/public/NOTES/notes/AN-14-290/trunk/Plots/v1.0/", std::string ext="png") { gStyle->SetOptTitle(0); gStyle->SetOptStat(0); bool latex = save; bool ABCD_prime = 0; bool TT_only = 0; std::stringstream ss, ss2; ss<<DPHI_CUT; ss2<<R_CUT; std::string dphi_cut = ss.str().replace(ss.str().find("."),1,"p"); std::string r_cut = ss2.str().replace(ss2.str().find("."),1,"p"); std::string filename = in.size() ? in : //"results/Plotter_out_2016_05_31_08h48m57_replot.root"; "results/Plotter_out_2016_06_24_14h28m51.root"; std::vector<std::string> samples[4]; //samples[0].push_back("TTJetsMGHT"); //samples[0].push_back("TTJetsMG"); //samples[0].push_back("TTJetsNLOFXFX"); //samples[0].push_back("TTNLO"); //samples[0].push_back("TTNLOHerwig"); //samples[0].push_back("TTPowheg"); //samples[0].push_back("TTPowhegmpiOff"); //samples[0].push_back("TTPowhegnoCR"); //samples[0].push_back("TTPowhegHerwig"); //+data+ samples[1].push_back("SingleElectron"); //+data+ samples[1].push_back("SingleMuon"); if (TT_only) { samples[1].push_back("TTJetsMGHT"); samples[1].push_back("TTJetsMG"); samples[1].push_back("TTJetsNLOFXFX"); samples[1].push_back("TTNLO"); samples[1].push_back("TTNLOHerwig"); samples[1].push_back("TTPowheg"); samples[1].push_back("TTPowhegmpiOFF"); samples[1].push_back("TTPowhegnoCR"); samples[1].push_back("TTPowhegHerwig"); } else { samples[1].push_back("TTJetsMGHT"); //samples[1].push_back("TTJetsMG"); //samples[1].push_back("TTJetsNLOFXFX"); //samples[1].push_back("TTNLO"); //samples[1].push_back("TTNLOHerwig"); //samples[1].push_back("TTPowheg"); //samples[1].push_back("TTPowhegmpiOff"); //samples[1].push_back("TTPowhegnoCR"); //samples[1].push_back("TTPowhegHerwig"); samples[1].push_back("ZJets"); samples[1].push_back("TTX"); samples[1].push_back("WJets"); samples[1].push_back("Diboson"); samples[1].push_back("Top"); samples[1].push_back("QCD"); //ZERO samples[1].push_back("TZQ"); //ZERO samples[1].push_back("ZJetsToQQ"); // Also WJetsToQQ //ZERO samples[1].push_back("GJets"); } //samples[1].push_back("Data"); // NTop Sideband All background summed samples[2].push_back("All Bkg."); // Signal in NTop bins samples[3].push_back("T1tttt"); bool baderror = false; double weight[] = { 0.32686, 0.0505037, 0.00921411, 6.80717, 0.354934, 0.00484915 }; int rebin = /*(R_CUT*10-int(R_CUT*10))==0 ? 10 :*/ (R_CUT*20-int(R_CUT*20))==0 ? 5 : (R_CUT*50-int(R_CUT*50))==0 ? 2 : 1; double sideband_fit_low_range[] = { 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15 }; int i_h_side[] = { 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }; int i_h_signal[] = { 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 }; double scale_factors[] = { 1, 1, 1, 1, 1, 1, 1}; // All normal //double scale_factors[] = { /* TT */ 1, /* W */ 1, /* Z */ 1, /* T */ 1, /* TTV */ 1, /* QCD */ 2, /* VV */ 1 }; // QCD high //double scale_factors[] = { /* TT */ 5, /* W */ 1, /* Z */ 1, /* T */ 1, /* TTV */ 5, /* QCD */ 1, /* VV */ 1 }; // TT/TTV high //double scale_factors[] = { /* TT */ 1, /* W */ 2, /* Z */ 2, /* T */ 2, /* TTV */ 1, /* QCD */ 1, /* VV */ 2 }; // T/V/VV high Double_t Rranges_ABCD[][4] = { { DPHI_CUT, 3.2, 0.0, DPHI_CUT }, { R_CUT_LOW-1e-10, R_CUT, R_CUT-1e-10, 1.20 }, { R_CUT_LOW-1e-10, R_CUT, R_CUT-1e-10, 1.20 }, { R_CUT_LOW-1e-10, R_CUT, R_CUT-1e-10, 1.20 } }; bool doFitting = false; double sum_a = 0, sum_b = 0, sum_c = 0, sum_d = 0, sum_d_abcd = 0, sum_d_nevt = 0; double sum_a_err = 0, sum_b_err = 0, sum_c_err = 0, sum_d_err = 0, sum_d_abcd_err = 0; double sum_b_fit = 0, sum_d_fit = 0, sum_d_fit_comb = 0; double sum_b_fit_err = 0, sum_d_fit_err = 0, sum_d_fit_comb_err = 0; double comb_d = 0, comb_d_err = 0, comb_d_abcd = 0, comb_d_abcd_err = 0; if (latex) { printf("\\begin{table*}[htbH]\n"); printf("\\small\n"); printf("\\begin{center}\n"); printf("\\topcaption{Estimated Standard Model background yields in ABCD regions. A, B is in the sideband, C and D is the signal band, D is the signal region.\\label{tab:SMBkgEstimate}}\n"); printf("\\begin{tabular}{lrrrrrrrr}\n"); } TFile *f = TFile::Open(filename.c_str()); for (size_t iMethod = 0; iMethod<4; ++iMethod) if (!(iMethod==0&&samples[0].size()==0)){ // Print Top row for each method if (latex) { if (iMethod==0) { printf("\\hline\n"); printf("Method 2 & A & B & C & D = B*C/A & D obs. & Ratio pred./obs. & Pull & KS test\\\\\n"); } else if (iMethod==1){ printf("\\hline\n"); printf("Method 1 & A & B & C & D = B*C/A & D obs. & Ratio pred./obs. & Pull & KS test\\\\\n"); } printf("\\hline\n"); } else { std::stringstream r_sb_cut; if (R_CUT_LOW==0) r_sb_cut<<"R<"<<R_CUT; else r_sb_cut<<R_CUT_LOW<<"<R<"<<R_CUT; const char* prime = ABCD_prime ? "'" : ""; //if (iMethod==0) printf("| *Sample* | *A (DPhi>2.8, SB)* | *B (DPhi<2.8, SB)* | *C (DPhi>2.8, Sig.B.)* | - | *D = B*C/A pred.* | *D (DPhi<2.8, Sig.B.) obs.* | *Ratio pred./obs.* |\n"); //else if (iMethod==1) printf("| *Sample* | *A (R<%1.1f, SB)* | *B (R>%1.1f, SB)* | *C (R<%1.1f, Sig.B.)* | *D = B (R fit, SB) * C/A pred.* | *D = B*C/A pred.* | *D (R>%1.1f, Sig.B.) obs.* | *Ratio pred./obs.* | \n", R_CUT, R_CUT, R_CUT, R_CUT); if (iMethod==0) printf("| *Sample* | *A (DPhi>%1.1f, %s)* | *B (DPhi<%1.1f, %s)* | *C (DPhi>%1.1f, R>0.4)* | *D = B*C/A pred.* | *D (DPhi<%1.1f, R>0.4) obs.* | *Ratio pred./obs.* | *Pull (pred-obs)/error* | *KS test* |\n", DPHI_CUT, r_sb_cut.str().c_str(), DPHI_CUT, r_sb_cut.str().c_str(), DPHI_CUT, DPHI_CUT); else if (iMethod==1) printf("| *Sample* | *A%s (%s, <2 tag)* | *B%s (R>%1.1f, <2 tag)* | *C%s (%s, 2 tag)* | *D%s = B%s*C%s/A%s pred.* | *D%s (R>%1.1f, 2 tag) obs.* | *Ratio pred./obs.* | *Pull (pred-obs)/error* | *KS test* |\n", prime, r_sb_cut.str().c_str(), prime, R_CUT, prime, r_sb_cut.str().c_str(), prime, prime, prime, prime, prime, R_CUT); } TH1D *h_side_sum, *h_signal_sum; for (size_t iSample = 0; iSample<samples[iMethod].size(); ++iSample) { std::string canname = iMethod==0 ? std::string("DPhiBins")+(ABCD_prime ? "/RBins_0To1HadTop_" : "/RBins_2HadTop_")+samples[iMethod][iSample] : iMethod==1 ? std::string("RFine/Tau32Cuts_")+(ABCD_prime ? "Fail" : "Pass")+"DPhiCut_"+samples[iMethod][iSample] : iMethod==2 ? std::string("RFine/Tau32Cuts_")+(ABCD_prime ? "Fail" : "Pass")+"DPhiCut_Background" : iMethod==3 ? std::string("RFine/Tau32Cuts_")+(ABCD_prime ? "Fail" : "Pass")+"DPhiCut_"+samples[iMethod][iSample] : ""; TCanvas *can = (TCanvas*)(f->Get(canname.c_str())); can = (TCanvas*)can->Clone(); can->Draw(); TH1D *h_side = (TH1D*)can->GetListOfPrimitives()->At(i_h_side[iMethod]); TH1D *h_signal = (TH1D*)can->GetListOfPrimitives()->At(i_h_signal[iMethod]); // Simulate different cross section by scaling a certain background if (iMethod==1) { TH1D *h_side_temp_scaled = (TH1D*)h_side->Clone(); h_side_temp_scaled->Scale(scale_factors[iSample]); TH1D *h_signal_temp_scaled = (TH1D*)h_signal->Clone(); h_signal_temp_scaled->Scale(scale_factors[iSample]); if (iSample==0) { h_side_sum = h_side_temp_scaled; h_signal_sum = h_signal_temp_scaled; } else { h_side_sum->Add(h_side_temp_scaled); h_signal_sum->Add(h_signal_temp_scaled); } } else if (iMethod==2) { h_side = h_side_sum; h_signal = h_signal_sum; } TH1D *h_pred =(TH1D*)h_side->Clone(); if (iMethod!=0&&rebin>1) { h_side->Rebin(rebin); h_signal->Rebin(rebin); h_pred->Rebin(rebin); } TLegend *leg = (TLegend*)can->GetListOfPrimitives()->At(can->GetListOfPrimitives()->GetEntries()-1); leg->SetX1(0.35); leg->SetX2(0.65); leg->SetY1(0.6); // Add ratio plot int y1 = 350; int y2 = 150; int mid2 = 10; can->Divide(1,2); // Pad 1 (80+500+20 x 40+500) TVirtualPad* p = can->cd(1); p->SetPad(0,(y2+60+mid2)/(y1+y2+100.0+mid2),1,1); p->SetTopMargin(40.0/(y1+40)); p->SetBottomMargin(0); p->SetRightMargin(0.05); p->SetLogy(1); h_side->GetYaxis()->SetRangeUser(1.00001e-4,1e4); h_side->Draw("HIST"); h_signal->Draw("SAMEHISTE1"); leg->Draw(); // Pad 2 (80+500+20 x 200+60) p = can->cd(2); p->SetGrid(0,1); p->SetPad(0,0,1,(y2+60+mid2)/(y1+y2+100.0+mid2)); p->SetTopMargin(((float)mid2)/(y2+60+mid2)); p->SetBottomMargin(60.0/(y2+60+mid2)); p->SetRightMargin(0.05); TH1D* ratio = (TH1D*)h_signal->Clone(); TH1D* div = (TH1D*)h_side->Clone(); //ratio->Scale(1/ratio->GetSumOfWeights()); double sum_bins_ratio = iMethod==0 ? ratio->Integral(): ratio->Integral(ratio->FindBin(R_CUT_LOW),ratio->FindBin(Rranges_ABCD[iMethod][3])); ratio->Scale(1/sum_bins_ratio); ratio->SetTitleSize(32.0/(y2+60+mid2),"xyz"); ratio->SetLabelSize(20.0/(y2+60+mid2),"xyz"); //ratio->Scale(1/div->GetSumOfWeights()); double sum_bins_div = iMethod==0 ? div->Integral(): div->Integral(div->FindBin(R_CUT_LOW),div->FindBin(Rranges_ABCD[iMethod][3])); div->Scale(1/sum_bins_div); ratio->Divide(div); //ratio->GetYaxis()->SetRangeUser(0,2); ratio->GetXaxis()->SetTitleOffset(0.7); ratio->GetYaxis()->SetNdivisions(305); ratio->GetYaxis()->SetTitle("Ratio (Norm.)"); ratio->GetYaxis()->SetTitleOffset(0.4); ratio->SetTitleSize(24.0/(y2+60+mid2),"y"); ratio->SetTitle(""); ratio->SetMarkerStyle(20); ratio->SetMarkerColor(1); ratio->SetLineColor(1); ratio->GetYaxis()->SetRangeUser(0,4); ratio->Draw("PE1"); TLine* l = new TLine(ratio->GetXaxis()->GetXmin(), 1, ratio->GetXaxis()->GetXmax(), 1); l->SetLineWidth(2); //l->SetLineColor(2); l->SetLineStyle(2); l->Draw(); gPad->Update(); // Fit ratio //TF1 *fit_ratio; //if (iMethod==1) { // fit_ratio = new TF1("fit_ratio","pol0", Rranges_ABCD[iMethod][0], Rranges_ABCD[iMethod][1]); // fit_ratio->SetLineColor(1); // ratio->Fit("fit_ratio","RE"); // fit_ratio->SetRange(Rranges_ABCD[iMethod][0], Rranges_ABCD[iMethod][2]); // fit_ratio->Draw("SAME"); //} p = can->cd(1); // calculate integrals double integral[2][2] = { { 0, 0 }, { 0, 0 } }; double integral_error[2][2] = { { 0, 0 }, { 0, 0 } }; double nevt[2][2] = { { 0, 0 }, { 0, 0 } }; //std::cout<<samples[iMethod][iSample]<<":"<<std::endl; for (int i=0; i<2; ++i) { for (int bin=1; bin<=h_side->GetNbinsX(); ++bin) { if (h_signal->GetXaxis()->GetBinLowEdge(bin)>=Rranges_ABCD[iMethod][i*2] && h_signal->GetXaxis()->GetBinUpEdge(bin)<=Rranges_ABCD[iMethod][i*2+1]) { //std::cout<<bin<<"="<<h_side->GetBinCenter(bin); //if (i==0) std::cout<<" in, "; //else std::cout<<" out, "; double c0 = h_side->GetBinContent(bin), c1 = h_signal->GetBinContent(bin); double e0 = h_side->GetBinError(bin), e1 = h_signal->GetBinError(bin); //std::cout<<h_signal->GetBinError(bin)<<" "<<sqrt(c1*weight[iSample])<<std::endl; if (baderror&&iMethod==1) { e0 = sqrt(c0*weight[iSample]); e1 = sqrt(c1*weight[iSample]); } nevt[0][i] += (int)(c0*c0/(e0*e0) + 0.5); nevt[1][i] += (int)(c1*c1/(e1*e1) + 0.5); integral[0][i] += c0; integral[1][i] += c1; //if (iMethod==1) { // weight bin by projected ratio (correction) // double bincent = h_signal->GetXaxis()->GetBinLowEdge(bin); // integral[0][1] *= fit_ratio->Eval(bincent); //} integral_error[0][i] += e0*e0; integral_error[1][i] += e1*e1; //if (iSample==0&&e1>0) std::cout<<bin<<" "<<c1<<" +- "<<e1*e1<<" nevt = "<<((int)(c1*c1/(e1*e1) + 0.5))<<std::endl; } } //if (iSample==1&&i==1) std::cout<<integral[1][i]<<" +- "<<integral_error[1][i]<<std::endl; integral_error[0][i] = sqrt(integral_error[0][i]); integral_error[1][i] = sqrt(integral_error[1][i]); } //std::cout<<nevt[1][1]<<std::endl; // predict yields using 2 methods (ABCD and constrained R-shape fit method combined) // ABCD method double a = integral[0][0], b = integral[0][1], c = integral[1][0], d = integral[1][1]; double a_err = integral_error[0][0], b_err = integral_error[0][1], c_err = integral_error[1][0], d_err = integral_error[1][1]; // Calculate error // z = x / y -> z_err = sqrt( (x*x*y_err*y_err + y*y*x_err*x_err)/(y*y*y*y) ) // z = x * y -> z_err = sqrt ( x*x*y_err*y_err + y*y*x_err*x_err ) double c_per_a_err = sqrt((c*c*a_err*a_err + a*a*c_err*c_err)/(a*a*a*a)); double d_abcd = b * (c/a), d_abcd_err = sqrt(b*b*c_per_a_err*c_per_a_err + (c/a)*(c/a)*b_err*b_err); double d_nevt = nevt[1][1]; double d_ratio = d_abcd / d; double d_ratio_err = sqrt((d_err/d)*(d_err/d) + (d_abcd_err/d_abcd)*(d_abcd_err/d_abcd))*d_ratio; double d_pull = (d_abcd-d)/sqrt(d_abcd_err*d_abcd_err + d_err*d_err); // Scaled plot h_pred->Scale(c/a); h_pred->SetLineColor(1); h_pred->SetLineStyle(2); h_pred->Draw("SAMEHIST"); leg->AddEntry(h_pred, "Prediction (ABCD)", "l"); double fit_integral[2][2], fit_integral_error[2][2], d_fit_comb = 0, d_fit_comb_err = 0; if (iMethod==1) { // Fit in the full range of NTop Sideband // Do fitting and calculate integrals TF1 *fit_side = new TF1("NTopSide_fit","exp([0]+[1]*x)", iMethod==2 ? 0.2 : sideband_fit_low_range[iSample], Rranges_ABCD[iMethod][3]); fit_side->SetLineColor(h_side->GetLineColor()); h_side->Fit("NTopSide_fit","QRE"); //fit_side->Draw("SAME"); double Rranges_ACfit[3] = { sideband_fit_low_range[iSample], Rranges_ABCD[iMethod][2], Rranges_ABCD[iMethod][3] }; for (int i=0; i<2; ++i) { fit_integral[0][i] = fit_side->Integral(Rranges_ACfit[i], Rranges_ACfit[i+1])/h_signal->GetXaxis()->GetBinWidth(1); fit_integral_error[0][i] = fit_side->IntegralError(Rranges_ACfit[i], Rranges_ACfit[i+1])/h_signal->GetXaxis()->GetBinWidth(1); } double par0 = fit_side->GetParameter(0), par0_error = fit_side->GetParError(0); double par1 = fit_side->GetParameter(1), par1_error = fit_side->GetParError(1); double par1min, par1max; fit_side->GetParLimits(1, par1min, par1max); // Fit in the Signal region // Fitting in sideband, get B area under curve and scale by C/A TF1 *fit_signal = new TF1("NTopSignal_RSide_fit","exp([0]+[1]*x)", Rranges_ACfit[0], Rranges_ABCD[iMethod][3]); fit_signal->SetLineColor(h_signal->GetLineColor()); //fit_signal->SetParameter(1, par1); //fit_signal->SetParLimits(1, par1min, par1max); h_signal->Fit("NTopSignal_RSide_fit","QREB"); //fit_signal->Draw("SAME"); for (int i=0; i<2; ++i) { fit_integral[1][i] = fit_signal->Integral(Rranges_ACfit[i], Rranges_ACfit[i+1])/h_signal->GetXaxis()->GetBinWidth(1); fit_integral_error[1][i] = fit_signal->IntegralError(Rranges_ACfit[i], Rranges_ACfit[i+1])/h_signal->GetXaxis()->GetBinWidth(1); } d_fit_comb = fit_integral[0][1] * (c/a); d_fit_comb_err = sqrt(fit_integral[0][1]*fit_integral[0][1]*c_per_a_err*c_per_a_err + (c/a)*(c/a)*fit_integral_error[0][1]*fit_integral_error[0][1]); TF1 *fit_pred = new TF1("Predicted_fit","exp([0]+[1]*x)", Rranges_ACfit[0], Rranges_ACfit[2]); fit_pred->SetLineColor(1); fit_pred->SetLineStyle(2); fit_pred->FixParameter(0, par0+std::log(c/a)); fit_pred->FixParameter(1, par1); h_signal->Fit("Predicted_fit","QREB+"); //fit_pred->Draw("SAME"); } // Save plot if (iMethod==3) samples[iMethod][iSample] = "T1tttt"; std::string name = samples[iMethod][iSample]; if (iMethod==2) name = "AllBkg"; if (save) can->SaveAs((out+"BkgEst/ABCD_closure_"+name+"."+ext).c_str()); // Check compatibility of prediction to observed distribution double ks_test = h_pred->KolmogorovTest(h_signal); if (iMethod==1) { sum_a += a; sum_b += b; sum_c += c; sum_d += d; sum_a_err += a_err*a_err; sum_b_err += b_err*b_err; sum_c_err += c_err*c_err; sum_d_err += d_err*d_err; sum_d_abcd += d_abcd; sum_d_abcd_err += d_abcd_err*d_abcd_err; sum_b_fit += fit_integral[0][1]; sum_b_fit_err += fit_integral_error[0][1]*fit_integral_error[0][1]; sum_d_fit += fit_integral[1][1]; sum_d_fit_err += fit_integral_error[1][1]*fit_integral_error[1][1]; sum_d_fit_comb += d_fit_comb; sum_d_fit_comb_err += d_fit_comb_err*d_fit_comb_err; sum_d_nevt += d_nevt; //printf(" %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |\n", d_fit_comb, d_fit_comb_err, d_abcd, d_abcd_err, d, d_err, d_ratio, d_ratio_err); } if (latex) { printf("%s & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ &", samples[iMethod][iSample].c_str(), a, a_err, b, b_err, c, c_err); printf(" $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & %.2f & %.2f \\\\\n", d_abcd, d_abcd_err, d, d_err, d_ratio, d_ratio_err, d_pull, ks_test); } else { printf("| %s | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |", samples[iMethod][iSample].c_str(), a, a_err, b, b_err, c, c_err); printf(" %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f | %.2f |\n", d_abcd, d_abcd_err, d, d_err, d_ratio, d_ratio_err, d_pull, ks_test); } // Combining best methods if ((iMethod==0&&iSample==0)||(iMethod==1&&iSample!=0)) { comb_d_abcd += d_abcd; comb_d += d; comb_d_abcd_err += d_abcd_err*d_abcd_err; comb_d_err += d_err*d_err; } } if (iMethod==1) { sum_a_err = sqrt(sum_a_err); sum_b_err = sqrt(sum_b_err); sum_c_err = sqrt(sum_c_err); sum_d_err = sqrt(sum_d_err); sum_b_fit_err = sqrt(sum_b_fit_err); sum_d_fit_err = sqrt(sum_d_fit_err); sum_d_fit_comb_err = sqrt(sum_d_fit_comb_err); double sum_d_ratio = sum_d_abcd / sum_d; double sum_d_ratio_err = sqrt((sum_d_err/sum_d)*(sum_d_err/sum_d) + (sum_d_abcd_err/sum_d_abcd)*(sum_d_abcd_err/sum_d_abcd))*sum_d_ratio; double sum_d_pull = (sum_d_abcd-sum_d)/sqrt(sum_d_abcd_err*sum_d_abcd_err + sum_d_err*sum_d_err); if (latex) { printf("\\hline\n"); printf("Sum Bkg. & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ &", sum_a, sum_a_err, sum_b, sum_b_err, sum_c, sum_c_err); printf(" $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & %.2f & \\\\\n", sum_d_abcd, sum_d_abcd_err, sum_d, sum_d_err, sum_d_ratio, sum_d_ratio_err, sum_d_pull); } else { //printf("| Sum Bkg.| %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |", sum_a, sum_a_err, sum_b_fit, sum_b_fit_err, sum_b, sum_b_err, sum_c, sum_c_err); printf("| Sum Bkg.| %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |", sum_a, sum_a_err, sum_b, sum_b_err, sum_c, sum_c_err); //printf(" %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |\n", sum_d_fit_comb, sum_d_fit_comb_err, sum_d_abcd, sum_d_abcd_err, sum_d, sum_d_err, sum_d_ratio, sum_d_ratio_err); printf(" %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f | - |\n", sum_d_abcd, sum_d_abcd_err, sum_d, sum_d_err, sum_d_ratio, sum_d_ratio_err, sum_d_pull); } } else if (iMethod==2&&samples[0].size()) { double comb_d_ratio = comb_d_abcd / comb_d; double comb_d_ratio_err = sqrt((comb_d_err/comb_d)*(comb_d_err/comb_d) + (comb_d_abcd_err/comb_d_abcd)*(comb_d_abcd_err/comb_d_abcd))*comb_d_ratio; double comb_d_pull = (comb_d_abcd-comb_d)/sqrt(comb_d_abcd_err*comb_d_abcd_err + comb_d_err*comb_d_err); if (latex) { printf("\\hline\n"); printf("\\hline\n"); printf("Combined Bkg. & & & & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & %.2f & \\\\\n", comb_d_abcd, comb_d_abcd_err, comb_d, comb_d_err, comb_d_ratio, comb_d_ratio_err, comb_d_pull); printf("\\hline\n"); } else { printf("| Combined Bkg.| | | | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f | - |\n", comb_d_abcd, comb_d_abcd_err, comb_d, comb_d_err, comb_d_ratio, comb_d_ratio_err, comb_d_pull); } } } if (latex) { printf("\\hline\n"); printf("\\end{tabular}\n"); printf("\\end{center}\n"); printf("\\end{table*}\n"); } if (save) gApplication->Terminate(); }