modified: GainMatchSX3.C multidimfit now runs but does not work as expected,
the fit curve is empty.
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GainMatchSX3.C
176
GainMatchSX3.C
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@ -224,6 +224,9 @@ Bool_t GainMatchSX3::Process(Long64_t entry)
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void GainMatchSX3::Terminate()
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{
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// --- Store fit coefficients in memory ---
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std::map<std::tuple<int, int, int, int>, TVectorD> fitCoefficients;
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const int MAX_DET = 24;
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const int MAX_UP = 4;
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const int MAX_DOWN = 4;
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@ -240,112 +243,115 @@ void GainMatchSX3::Terminate()
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}
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// === Loop over all (id, bk, up, dn) combinations ===
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for (const auto &kv : dataPoints)
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{
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for (const auto &kv : dataPoints) {
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auto [id, bk, u, d] = kv.first;
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const auto &pts = kv.second;
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if (pts.size() < 5)
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continue;
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if (pts.size() < 20) continue;
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int N = pts.size();
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double *x0 = new double[N];
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double *x1 = new double[N];
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double *x2 = new double[N];
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double *y = new double[N];
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int mPowers[] = {1,1,1};
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// Fill arrays
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for (int i = 0; i < N; ++i)
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{
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std::vector<double> x_bk, x_up, y_fsum;
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for (const auto &pr : pts) {
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double eBk, eUp, eDn;
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std::tie(eBk, eUp, eDn) = pts[i];
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x0[i] = eBk;
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x1[i] = eUp;
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x2[i] = eDn;
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y[i] = eUp + eDn; // Target is front sum
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std::tie(eBk, eUp, eDn) = pr;
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if (eBk > 0 && eUp > 0 && eDn > 0) {
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x_bk.push_back(eBk);
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x_up.push_back(eUp);
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y_fsum.push_back(eUp + eDn);
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}
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}
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// Build MultiDim Fit
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TMultiDimFit *mdf = new TMultiDimFit(3, TMultiDimFit::kMonomials, "v");
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mdf->SetMaxPowers(mPowers); // Up to quadratic terms
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mdf->SetMaxTerms(3); // Limit number of terms kept
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int nPoints = y_fsum.size();
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if (nPoints < 20) continue;
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// Add points
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for (int i = 0; i < N; ++i)
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{
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double vars[3] = {x0[i], x1[i], x2[i]};
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mdf->AddRow(vars, y[i]);
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TMultiDimFit *mdf = new TMultiDimFit(2, TMultiDimFit::kMonomials);
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mdf->SetMaxPowers(new Int_t[2]{1, 1});
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mdf->SetMinAngle(10);
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mdf->SetMinRelativeError(1e-4);
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double *x_row = new double[2];
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for (int i = 0; i < nPoints; ++i) {
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x_row[0] = x_bk[i];
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x_row[1] = x_up[i];
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mdf->AddRow(x_row, y_fsum[i]);
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}
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delete[] x_row;
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mdf->Fit();
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const TVectorD *coeffs = mdf->GetCoefficients();
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if (!coeffs || coeffs->GetNoElements() == 0 || !TMath::Finite((*coeffs)(0))) {
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std::cerr << "Fit failed for Det" << id << " B" << bk << " U" << u << " D" << d << std::endl;
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delete mdf;
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continue;
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}
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mdf->MakeHistograms();
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mdf->FindParameterization();
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mdf->Print("a"); // Print coefficients
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mdf->
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// Save result string
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TString formula;
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mdf->GetFunctions(formula);
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outFile << id << " " << bk << " " << u << " " << d << " " << formula.Data() << std::endl;
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printf("Det %d Bk %d Up %d Dn %d — MultiDimFit formula: %s\n", id, bk, u, d, formula.Data());
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// Store coefficients in the map and write to file
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fitCoefficients[kv.first] = *coeffs;
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int nCoeffs = mdf->GetNCoefficients();
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outFile << id << " " << bk << " " << u << " " << d;
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printf("Fit for Det%d B%d U%d D%d -> ", id, bk, u, d);
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for (int i = 0; i < nCoeffs; ++i) {
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outFile << " " << (*coeffs)(i);
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printf("p%d: %.4f ", i, (*coeffs)(i));
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}
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outFile << std::endl;
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printf("\n");
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gainValid[id][bk][u][d] = true; // Save as "valid" so we can use it
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// Clean up
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delete[] x0;
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delete[] x1;
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delete[] x2;
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delete[] y;
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delete mdf;
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}
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outFile.close();
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std::cout << "MultiDim fits complete.\n";
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std::cout << "Multi-dimensional gain matching complete. Results saved." << std::endl;
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// === Example histogram after correction ===
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TH2F *hFVB = new TH2F("hFVB", "Corrected Up+Dn vs Back;Back E;Corrected Up+Dn E",
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400, 0, 16000, 400, 0, 16000);
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// --- Stage 2: Apply corrections and create new histograms ---
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std::cout << "--- Stage 2: Applying Corrections and Visualizing Results ---" << std::endl;
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TH2F *hCorrectedFvB = new TH2F("hCorrectedFvB", "Gain Corrected Data;Predicted Front Sum (from fit);Measured Front Sum", 400, 0, 16000, 400, 0, 16000);
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for (const auto &kv : dataPoints)
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{
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auto [id, bk, u, d] = kv.first;
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if (!gainValid[id][bk][u][d])
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continue;
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for (const auto &kv : dataPoints) {
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// Find the coefficients for this segment
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if (fitCoefficients.find(kv.first) == fitCoefficients.end()) {
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continue; // Skip if no valid fit was found
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}
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const TVectorD& coeffs = fitCoefficients[kv.first];
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double p0 = coeffs(0);
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double p1 = coeffs(1);
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double p2 = coeffs(2);
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// Recreate the fitted model to evaluate
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TMultiDimFit *mdf = new TMultiDimFit(3, TMultiDimFit::kMonomials, "v");
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mdf->SetMaxPowers(2);
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mdf->SetMaxTerms(10);
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// Re-fill points to refit (if needed — or you can serialize coefficients instead)
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// Loop over the data points for this segment and apply the correction
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const auto &pts = kv.second;
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for (const auto &pr : pts)
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{
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for (const auto &pr : pts) {
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double eBk, eUp, eDn;
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std::tie(eBk, eUp, eDn) = pr;
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double vars[3] = {eBk, eUp, eDn};
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double y = eUp + eDn;
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mdf->AddRow(vars, y);
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// Calculate the predicted front sum using the fit parameters
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double predicted_front_sum = p0 + p1 * eBk + p2 * eUp;
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// The measured front sum is just the raw sum
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double measured_front_sum = eUp + eDn;
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// Fill the corrected histogram
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hCorrectedFvB->Fill(predicted_front_sum, measured_front_sum);
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}
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mdf->FindParameterization();
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// Fill histogram with corrected "front" from model
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for (const auto &pr : kv.second)
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{
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double eBk, eUp, eDn;
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std::tie(eBk, eUp, eDn) = pr;
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double vars[3] = {eBk, eUp, eDn};
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double correctedFront = mdf->Eval(vars);
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if (eBk == 0 || correctedFront == 0)
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continue;
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hFVB->Fill(eBk, correctedFront);
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}
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delete mdf;
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}
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// Save histogram if needed
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// TFile *outHist = new TFile("sx3_multidimfit_hists.root", "RECREATE");
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// hFVB->Write();
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// outHist->Close();
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}
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// --- Stage 3: Draw the comparison canvases ---
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gStyle->SetOptStat(1110);
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TCanvas *c1 = new TCanvas("c1", "Gain Correction Results", 1200, 600);
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c1->Divide(2, 1);
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c1->cd(1);
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hSX3FvsB_g->SetTitle("Before Correction (Gated)");
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hSX3FvsB_g->GetXaxis()->SetTitle("Measured Front Sum (E_Up + E_Dn)");
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hSX3FvsB_g->GetYaxis()->SetTitle("Measured Back E");
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hSX3FvsB_g->Draw("colz");
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c1->cd(2);
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hCorrectedFvB->SetTitle("After Correction");
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hCorrectedFvB->Draw("colz");
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// Draw a perfect y=x line for comparison
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TF1 *diag = new TF1("diag", "x", 0, 16000);
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diag->SetLineColor(kRed);
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diag->SetLineWidth(2);
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diag->Draw("same");
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}
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