#include #include #include #include #include #include #include #include #include #include #include #include #include #include #include using namespace std; #include "StandardLabels.C" #include "tdiff_res.cc" #include "tdiff.cc" #include "E_calibrate.cc" #include "Angle.h" #include "Geom.h" void GetPoints(TH2D *h, TGraphErrors* &gres, TGraphErrors* &gmean); //------------------------------------ // Copied from JEventProcessor_bcal_timing.cc typedef struct{ int event; int layer; int sector; int fADC_up; int fADC_dn; float Etot; float geometric_mean; float tup; float tdn; float tup_corrected; float tdn_corrected; float theta_thrown; float E_thrown; }HIT_t; //------------------------------------ //----------------- // Thetares_vs_E //----------------- void Thetares_vs_E(void) { TFile *f = new TFile("hd_root.root"); f->cd(); TTree *tree = (TTree*)gROOT->FindObject("tree"); HIT_t hit; HIT_t *hitptr = &hit; TBranch *branch = tree->GetBranch("T"); branch->SetAddress(hitptr); TH2D *h = new TH2D("h", "", 200, 0.03, 2.0, 200, -0.5, 0.5); // Loop over all events and fill histogram. We do this // rather than TTree::Project since we need to call the // BCAL_tdiff_res for each entry int Nentries = branch->GetEntries(); double t_tot = 0.0; double A_tot = 0.0; double E_thrown = 0.0; double E_tot = 0.0; int last_event=1; for(int i=1; i<=Nentries; i++){ tree->GetEntry(i); // Fill histogram on event boundaries and reset for next event if(hit.event!=last_event){ t_tot /= A_tot; E_tot = BCAL_fADC2E(E_tot); // convert to GeV h->Fill(E_thrown, E_tot - E_thrown); t_tot = 0.0; A_tot = 0.0; E_thrown = 0.0; E_tot = 0.0; last_event = hit.event; } if(hit.layer<1 || hit.layer>MaxSummedLayers())continue; // if(hit.tup_corrected<-100)continue; if(hit.tdn_corrected<-100)continue; // Accumulate info for this event double geomn = hit.geometric_mean; double E = geomn; E_tot += E; E_thrown = hit.E_thrown; if(!IsOuter(hit.layer)){ double weight = E; double tdiff_corrected = (hit.tup_corrected - hit.tdn_corrected)/2.0 - BCAL_tdiff(geomn, hit.layer); t_tot += weight*1000.0*tdiff_corrected; A_tot += weight; } } TGraphErrors *gres; TGraphErrors *gmean; GetPoints(h, gres, gmean); // Fit to find sigma of delta E TF1 *fun = new TF1("fun", "sqrt(pow([0]*sqrt(x),2.0) + pow([1]*x,2.0) + pow([2],2.0))"); fun->SetParameter(0, 0.05); fun->SetParameter(1, 0.03); fun->SetParameter(2, 0.0); gres->Fit(fun, "0"); // Now, convert function and data to DeltaE/E fo plotting // I'm not sure if this is necessary, but it seems most // resolution plots are of sigmaE/E. The fitting to find // sigmaE though seems like it should be done to DeltaE for(int i=0; iGetN(); i++){ double E, DeltaE; gres->GetPoint(i, E, DeltaE); DeltaE /= E; gres->SetPoint(i, E, DeltaE); } TF1 *fun2 = new TF1("fun2", "sqrt(pow([0]/sqrt(x),2.0) + pow([1],2.0) + pow([2]/x,2.0))", 0.0, 2.0); fun2->SetParameter(0, fun->GetParameter(0)); fun2->SetParameter(1, fun->GetParameter(1)); fun2->SetParameter(2, fun->GetParameter(2)); //gres->Fit(fun2); TCanvas *c1 = new TCanvas("c1"); c1->SetTicks(); c1->SetGrid(); TH2D *axes = new TH2D("axes","", 100, 0.0, 2.0, 100, 0.0, 1.0); axes->SetStats(0); axes->SetYTitle("#sigma_{E}/E"); axes->SetXTitle("Generated Energy (GeV)"); axes->Draw(); gres->Draw("Psame"); fun2->Draw("same"); char str[256]; sprintf(str, "#frac{#sigma_{E}}{E} = #frac{%3.1f%%}{#sqrt{E}} #oplus %3.1f%% #oplus #frac{%3.1f%%}{E}", fun2->GetParameter(0)*100.0, fun2->GetParameter(1)*100.0, fun2->GetParameter(2)*100.0); TLatex *lab = new TLatex(1.2, 0.7, str); lab->SetTextSize(0.05); lab->SetTextAlign(22); lab->Draw(); StandardLabels(axes, Scheme(), "", AngleStr("#theta_{#gamma}=")); c1->SaveAs("Thetares_vs_E.pdf"); c1->SaveAs("Thetares_vs_E.png"); } //------------------ // GetPoints //------------------ void GetPoints(TH2D *h, TGraphErrors* &gres, TGraphErrors* &gmean) { int min_entries = 300; // Project onto the x-axis so we can find the limits for // for the projection on the y-axis based on number of events TH1D *h_px = h->ProjectionX("_px", 1); // Loop over (uneven) bins int Npoints = 0; vector x; vector y; vector y_mean; vector xerr; vector yerr; vector y_mean_err; int Nbins = h->GetNbinsX(); for(int start_bin=1; start_bin<=Nbins; ){ // Find limits to give us min_entries entries int end_bin = start_bin; while(h_px->Integral(start_bin, end_bin)Integral(end_bin, Nbins)Integral()>=20){ // Fit to Gaussian h_py->Fit("gaus","0Q"); //c1->Update(); // Get fit results double mean = h_py->GetFunction("gaus")->GetParameter(1); double sigma = h_py->GetFunction("gaus")->GetParameter(2); double mean_err = h_py->GetFunction("gaus")->GetParError(1); double sigma_err = h_py->GetFunction("gaus")->GetParError(2); // Find average fADC value for hits in this bin range double fADC = 0.0; double norm = 0.0; for(int bin=start_bin; bin<=end_bin; bin++){ double weight = h_px->GetBinContent(bin); fADC += h_px->GetBinCenter(bin)*weight; norm += weight; } fADC /= norm; // Add floor term to error obtained from Gaussian fit double epsilon = 0.010; // GeV mean_err = sqrt(mean_err*mean_err + epsilon*epsilon); sigma_err = sqrt(sigma_err*sigma_err + epsilon*epsilon); // Error on reconstructed energy is difficult to estimate here. // It is definitely worse than the final algorithm will yield. // The fact that the "reconstructed" energy extends out to 2.5GeV // when the generated data set only went to 2GeV says it is // considerably worse than 5.5%/sqrt(E). For lack of a better // idea, I use the RMS of the fADC values about the mean // in the current range. double fADC_rms = 0.0; double norm_rms = 0.0; for(int bin=start_bin; bin<=end_bin; bin++){ double weight = h_px->GetBinContent(bin); fADC_rms += pow(h_px->GetBinCenter(bin)-fADC, 2.0)*weight; norm_rms += weight; } fADC_rms /= norm_rms; fADC_rms = sqrt(fADC_rms); x.push_back(fADC); y.push_back(sigma); y_mean.push_back(mean); xerr.push_back(fADC_rms); yerr.push_back(sigma_err); y_mean_err.push_back(sigma_err); Npoints++; } // Increment for next iteration start_bin=end_bin+1; } gres = new TGraphErrors(Npoints, &x[0], &y[0], &xerr[0], &yerr[0]); gres->SetMarkerColor(kMagenta); gres->SetLineColor(kMagenta); gres->SetLineWidth(2); gmean = new TGraphErrors(Npoints, &x[0], &y_mean[0], &xerr[0], &y_mean_err[0]); gmean->SetMarkerColor(kRed); gmean->SetMarkerStyle(22); gmean->SetLineColor(kRed); }