#define GainMatchSX3_cxx #include "GainMatchSX3.h" #include #include #include #include #include #include #include #include #include #include #include "Armory/ClassSX3.h" #include "TGraphErrors.h" #include "TMultiDimFit.h" #include "TVector3.h" TH2F *hSX3FvsB; TH2F *hSX3FvsB_g; TH2F *hsx3IndexVE; TH2F *hsx3IndexVE_g; TH2F *hSX3; TH2F *hsx3Coin; int padID = 0; SX3 sx3_contr; TCutG *cut; TCutG *cut1; std::map, std::vector>> dataPoints; void GainMatchSX3::Begin(TTree * /*tree*/) { TString option = GetOption(); hSX3FvsB = new TH2F("hSX3FvsB", "SX3 Front vs Back; Front E; Back E", 400, 0, 16000, 400, 0, 16000); hSX3FvsB_g = new TH2F("hSX3FvsB_g", "SX3 Front vs Back; Front E; Back E", 400, 0, 16000, 400, 0, 16000); hsx3IndexVE = new TH2F("hsx3IndexVE", "SX3 index vs Energy; sx3 index ; Energy", 24 * 12, 0, 24 * 12, 400, 0, 5000); hsx3IndexVE_g = new TH2F("hsx3IndexVE_g", "SX3 index vs Energy; sx3 index ; Energy", 24 * 12, 0, 24 * 12, 400, 0, 5000); hSX3 = new TH2F("hSX3", "SX3 Front v Back; Fronts; Backs", 8, 0, 8, 4, 0, 4); hsx3Coin = new TH2F("hsx3Coin", "SX3 Coincident", 24 * 12, 0, 24 * 12, 24 * 12, 0, 24 * 12); sx3_contr.ConstructGeo(); // Load the TCutG object TFile *cutFile = TFile::Open("sx3cut.root"); if (!cutFile || cutFile->IsZombie()) { std::cerr << "Error: Could not open sx3cut.root" << std::endl; return; } cut = dynamic_cast(cutFile->Get("sx3cut")); if (!cut) { std::cerr << "Error: Could not find TCutG named 'sx3cut' in sx3cut.root" << std::endl; return; } cut->SetName("sx3cut"); // Ensure the cut has the correct name // Load the TCutG object TFile *cutFile1 = TFile::Open("UvD.root"); if (!cutFile1 || cutFile1->IsZombie()) { std::cerr << "Error: Could not open UvD.root" << std::endl; return; } cut1 = dynamic_cast(cutFile1->Get("UvD")); if (!cut1) { std::cerr << "Error: Could not find TCutG named 'UvD' in UvD.root" << std::endl; return; } cut1->SetName("UvD"); } Bool_t GainMatchSX3::Process(Long64_t entry) { b_sx3Multi->GetEntry(entry); b_sx3ID->GetEntry(entry); b_sx3Ch->GetEntry(entry); b_sx3E->GetEntry(entry); b_sx3T->GetEntry(entry); b_qqqMulti->GetEntry(entry); b_qqqID->GetEntry(entry); b_qqqCh->GetEntry(entry); b_qqqE->GetEntry(entry); b_qqqT->GetEntry(entry); b_pcMulti->GetEntry(entry); b_pcID->GetEntry(entry); b_pcCh->GetEntry(entry); b_pcE->GetEntry(entry); b_pcT->GetEntry(entry); sx3.CalIndex(); qqq.CalIndex(); pc.CalIndex(); std::vector> ID; for (int i = 0; i < sx3.multi; i++) { for (int j = i + 1; j < sx3.multi; j++) { if (sx3.id[i] == 3) hsx3Coin->Fill(sx3.index[i], sx3.index[j]); } if (sx3.e[i] > 100) { ID.push_back(std::pair(sx3.id[i], i)); hsx3IndexVE->Fill(sx3.index[i], sx3.e[i]); } } if (ID.size() > 0) { std::sort(ID.begin(), ID.end(), [](const std::pair &a, const std::pair &b) { return a.first < b.first; }); // start with the first entry in the sorted array: channels that belong to the same detector are together in sequenmce std::vector> sx3ID; sx3ID.push_back(ID[0]); bool found = false; for (size_t i = 1; i < ID.size(); i++) { // Check if id of i belongs to the same detector and then add it to the detector ID vector if (ID[i].first == sx3ID.back().first) { // count the nunmber of hits that belong to the same detector sx3ID.push_back(ID[i]); if (sx3ID.size() >= 3) { found = true; } } else { // the next event does not belong to the same detector, abandon the first event and continue with the next one if (!found) { sx3ID.clear(); sx3ID.push_back(ID[i]); } } } if (found) { int sx3ChUp = -1, sx3ChDn = -1, sx3ChBk = -1; float sx3EUp = 0.0, sx3EDn = 0.0, sx3EBk = 0.0; for (size_t i = 0; i < sx3ID.size(); i++) { int index = sx3ID[i].second; // Check the channel number and assign it to the appropriate channel type if (sx3.ch[index] < 8) { if (sx3.ch[index] % 2 == 0) { sx3ChDn = sx3.ch[index]; sx3EDn = sx3.e[index]; } else { sx3ChUp = sx3.ch[index]; sx3EUp = sx3.e[index]; } } else { sx3ChBk = sx3.ch[index] - 8; // if (sx3ChBk == 2) // printf("Found back channel Det %d Back %d \n", sx3.id[index], sx3ChBk); sx3EBk = sx3.e[index]; } } // If we have a valid front and back channel, fill the histograms hSX3->Fill(sx3ChDn, sx3ChBk); hSX3->Fill(sx3ChUp, sx3ChBk); // Fill the histogram for the front vs back hSX3FvsB->Fill(sx3EUp + sx3EDn, sx3EBk); for (int i = 0; i < sx3.multi; i++) { if (sx3.id[i] == 3 && sx3.e[i] > 100) { // Fill the histogram for the front vs back with gain correction hSX3FvsB_g->Fill(sx3EUp + sx3EDn, sx3EBk); // Fill the index vs energy histogram hsx3IndexVE_g->Fill(sx3.index[i], sx3.e[i]); // } // { TString histName = Form("hSX3FVB_id%d_U%d_D%d_B%d", sx3.id[i], sx3ChUp, sx3ChDn, sx3ChBk); TH2F *hist2d = (TH2F *)gDirectory->Get(histName); if (!hist2d) { hist2d = new TH2F(histName, Form("hSX3FVB_id%d_U%d_D%d_B%d", sx3.id[i], sx3ChUp, sx3ChDn, sx3ChBk), 400, 0, 16000, 400, 0, 16000); } // if (sx3ChBk == 2) // printf("Found back channel Det %d Back %d \n", sx3.id[i], sx3ChBk); // hsx3IndexVE_g->Fill(sx3.index[i], sx3.e[i]); // hSX3FvsB_g->Fill(sx3EUp + sx3EDn, sx3EBk); hist2d->Fill(sx3EUp + sx3EDn, sx3EBk); if (cut && cut->IsInside(sx3EUp + sx3EDn, sx3EBk)) // if (sx3.id[i] < 24 && sx3ChUp < 4 && sx3ChBk < 4 && std::isfinite(sx3EUp) && std::isfinite(sx3EDn) && std::isfinite(sx3EBk)) { // Accumulate data for gain matching dataPoints[{sx3.id[i], sx3ChBk, sx3ChUp, sx3ChDn}].emplace_back(sx3EBk, sx3EUp, sx3EDn); } } } } } return kTRUE; } void GainMatchSX3::Terminate() { // --- Store fit coefficients in memory --- std::map, TVectorD> fitCoefficients; const int MAX_DET = 24; const int MAX_UP = 4; const int MAX_DOWN = 4; const int MAX_BK = 4; double gainArray[MAX_DET][MAX_BK][MAX_UP][MAX_DOWN] = {{{{0}}}}; bool gainValid[MAX_DET][MAX_BK][MAX_UP][MAX_DOWN] = {{{{false}}}}; std::ofstream outFile("sx3_MultiDimFit_results.txt"); if (!outFile.is_open()) { std::cerr << "Error opening output file!" << std::endl; return; } // === Loop over all (id, bk, up, dn) combinations === for (const auto &kv : dataPoints) { auto [id, bk, u, d] = kv.first; const auto &pts = kv.second; if (pts.size() < 20) continue; std::vector x_bk, x_up, y_fsum; for (const auto &pr : pts) { double eBk, eUp, eDn; std::tie(eBk, eUp, eDn) = pr; if (eBk > 0 && eUp > 0 && eDn > 0) { x_bk.push_back(eBk); x_up.push_back(eUp); y_fsum.push_back(eUp + eDn); } } int nPoints = y_fsum.size(); if (nPoints < 20) continue; TMultiDimFit *mdf = new TMultiDimFit(2, TMultiDimFit::kMonomials); mdf->SetMaxPowers(new Int_t[2]{1, 1}); mdf->SetMinAngle(10); mdf->SetMinRelativeError(1e-4); double *x_row = new double[2]; for (int i = 0; i < nPoints; ++i) { x_row[0] = x_bk[i]; x_row[1] = x_up[i]; mdf->AddRow(x_row, y_fsum[i]); } delete[] x_row; mdf->Fit(); const TVectorD *coeffs = mdf->GetCoefficients(); if (!coeffs || coeffs->GetNoElements() == 0 || !TMath::Finite((*coeffs)(0))) { std::cerr << "Fit failed for Det" << id << " B" << bk << " U" << u << " D" << d << std::endl; delete mdf; continue; } // Store coefficients in the map and write to file fitCoefficients[kv.first] = *coeffs; int nCoeffs = mdf->GetNCoefficients(); outFile << id << " " << bk << " " << u << " " << d; printf("Fit for Det%d B%d U%d D%d -> ", id, bk, u, d); for (int i = 0; i < nCoeffs; ++i) { outFile << " " << (*coeffs)(i); printf("p%d: %.4f ", i, (*coeffs)(i)); } outFile << std::endl; printf("\n"); delete mdf; } outFile.close(); std::cout << "Multi-dimensional gain matching complete. Results saved." << std::endl; // --- Stage 2: Apply corrections and create new histograms --- std::cout << "--- Stage 2: Applying Corrections and Visualizing Results ---" << std::endl; TH2F *hCorrectedFvB = new TH2F("hCorrectedFvB", "Gain Corrected Data;Predicted Front Sum (from fit);Measured Front Sum", 400, 0, 16000, 400, 0, 16000); for (const auto &kv : dataPoints) { // Find the coefficients for this segment if (fitCoefficients.find(kv.first) == fitCoefficients.end()) { continue; // Skip if no valid fit was found } const TVectorD& coeffs = fitCoefficients[kv.first]; double p0 = coeffs(0); double p1 = coeffs(1); double p2 = coeffs(2); // Loop over the data points for this segment and apply the correction const auto &pts = kv.second; for (const auto &pr : pts) { double eBk, eUp, eDn; std::tie(eBk, eUp, eDn) = pr; // Calculate the predicted front sum using the fit parameters double predicted_front_sum = p0 + p1 * eBk + p2 * eUp; // The measured front sum is just the raw sum double measured_front_sum = eUp + eDn; // Fill the corrected histogram hCorrectedFvB->Fill(predicted_front_sum, measured_front_sum); } } // --- Stage 3: Draw the comparison canvases --- gStyle->SetOptStat(1110); TCanvas *c1 = new TCanvas("c1", "Gain Correction Results", 1200, 600); c1->Divide(2, 1); c1->cd(1); hSX3FvsB_g->SetTitle("Before Correction (Gated)"); hSX3FvsB_g->GetXaxis()->SetTitle("Measured Front Sum (E_Up + E_Dn)"); hSX3FvsB_g->GetYaxis()->SetTitle("Measured Back E"); hSX3FvsB_g->Draw("colz"); c1->cd(2); hCorrectedFvB->SetTitle("After Correction"); hCorrectedFvB->Draw("colz"); // Draw a perfect y=x line for comparison TF1 *diag = new TF1("diag", "x", 0, 16000); diag->SetLineColor(kRed); diag->SetLineWidth(2); diag->Draw("same"); }