functional fit option for waveform processing

offline/packages/CaloReco/CaloTowerBuilder.cc

@@ -75,6 +75,14 @@ int CaloTowerBuilder::InitRun(PHCompositeNode *topNode)
     WaveformProcessing->set_bitFlipRecovery(m_dobitfliprecovery);
   }
 
+  // Set functional fit parameters
+  if (_processingtype == CaloWaveformProcessing::FUNCFIT)
+  {
+    WaveformProcessing->set_funcfit_type(m_funcfit_type);
+    WaveformProcessing->set_powerlaw_params(m_powerlaw_power, m_powerlaw_decay);
+    WaveformProcessing->set_doubleexp_params(m_doubleexp_power, m_doubleexp_peaktime1, m_doubleexp_peaktime2, m_doubleexp_ratio);
+  }
+
   if (m_dettype == CaloTowerDefs::CEMC)
   {
     m_detector = "CEMC";
@@ -476,6 +484,7 @@ int CaloTowerBuilder::process_event(PHCompositeNode *topNode)
     towerinfo->set_pedestal(processed_waveforms.at(idx).at(2));
     towerinfo->set_chi2(processed_waveforms.at(idx).at(3));
     bool SZS = isSZS(processed_waveforms.at(idx).at(1), processed_waveforms.at(idx).at(3));
+
     if (processed_waveforms.at(idx).at(4) == 0)
     {
       towerinfo->set_isRecovered(false);

offline/packages/CaloReco/CaloTowerBuilder.h

@@ -94,6 +94,26 @@ class CaloTowerBuilder : public SubsysReco
     m_dobitfliprecovery = dobitfliprecovery;
   }
 
+  // Functional fit options: 0 = PowerLawExp, 1 = PowerLawDoubleExp
+  void set_funcfit_type(int type)
+  {
+    m_funcfit_type = type;
+  }
+
+  void set_powerlaw_params(double power, double decay)
+  {
+    m_powerlaw_power = power;
+    m_powerlaw_decay = decay;
+  }
+
+  void set_doubleexp_params(double power, double peaktime1, double peaktime2, double ratio)
+  {
+    m_doubleexp_power = power;
+    m_doubleexp_peaktime1 = peaktime1;
+    m_doubleexp_peaktime2 = peaktime2;
+    m_doubleexp_ratio = ratio;
+  }
+
   void set_tbt_softwarezerosuppression(const std::string &url)
   {
     m_zsURL = url;
@@ -150,6 +170,15 @@ class CaloTowerBuilder : public SubsysReco
   std::string m_directURL;
   std::string m_zsURL;
   std::string m_zs_fieldname{"zs_threshold"};
+
+  // Functional fit parameters
+  int m_funcfit_type{1};  // 0 = PowerLawExp, 1 = PowerLawDoubleExp
+  double m_powerlaw_power{4.0};
+  double m_powerlaw_decay{1.5};
+  double m_doubleexp_power{2.0};
+  double m_doubleexp_peaktime1{5.0};
+  double m_doubleexp_peaktime2{5.0};
+  double m_doubleexp_ratio{0.3};
 };
 
 #endif  // CALOTOWERBUILDER_H

offline/packages/CaloReco/CaloWaveformFitting.cc

@@ -2,6 +2,7 @@
 
 #include <TF1.h>
 #include <TFile.h>
+#include <TH1F.h>
 #include <TProfile.h>
 #include <TSpline.h>
 
@@ -619,3 +620,254 @@ float CaloWaveformFitting::psinc(float time, std::vector<float> &vec_signal_samp
 
   return sum;
 }
+
+double CaloWaveformFitting::SignalShape_PowerLawExp(double *x, double *par)
+{
+  // par[0]: Amplitude
+  // par[1]: Sample Start (t0)
+  // par[2]: Power
+  // par[3]: Decay
+  // par[4]: Pedestal
+  double pedestal = par[4];
+  if (x[0] < par[1])
+  {
+    return pedestal;
+  }
+  double signal = par[0] * pow((x[0] - par[1]), par[2]) * exp(-(x[0] - par[1]) * par[3]);
+  return pedestal + signal;
+}
+
+double CaloWaveformFitting::SignalShape_PowerLawDoubleExp(double *x, double *par)
+{
+  // par[0]: Amplitude
+  // par[1]: Sample Start (t0)
+  // par[2]: Power
+  // par[3]: Peak Time 1
+  // par[4]: Pedestal
+  // par[5]: Amplitude ratio
+  // par[6]: Peak Time 2
+  double pedestal = par[4];
+  if (x[0] < par[1])
+  {
+    return pedestal;
+  }
+  double signal = par[0] * pow((x[0] - par[1]), par[2]) *
+                  (((1.0 - par[5]) / pow(par[3], par[2]) * exp(par[2])) *
+                       exp(-(x[0] - par[1]) * (par[2] / par[3])) +
+                   (par[5] / pow(par[6], par[2]) * exp(par[2])) *
+                       exp(-(x[0] - par[1]) * (par[2] / par[6])));
+  return pedestal + signal;
+}
+
+std::vector<std::vector<float>> CaloWaveformFitting::calo_processing_funcfit(const std::vector<std::vector<float>> &chnlvector)
+{
+  std::vector<std::vector<float>> fit_values;
+  int nchnls = chnlvector.size();
+
+  for (int m = 0; m < nchnls; m++)
+  {
+    const std::vector<float> &v = chnlvector.at(m);
+    int nsamples = v.size();
+
+    float amp = 0;
+    float time = 0;
+    float ped = 0;
+    float chi2 = std::numeric_limits<float>::quiet_NaN();
+
+    // Handle zero-suppressed samples (2-sample case)
+    if (nsamples == _nzerosuppresssamples)
+    {
+      amp = v.at(1) - v.at(0);
+      time = std::numeric_limits<float>::quiet_NaN();
+      ped = v.at(0);
+      if (v.at(0) != 0 && v.at(1) == 0)
+      {
+        chi2 = 1000000;
+      }
+      fit_values.push_back({amp, time, ped, chi2, 0});
+      continue;
+    }
+
+    // Find peak position and estimate pedestal
+    float maxheight = 0;
+    int maxbin = 0;
+    for (int i = 0; i < nsamples; i++)
+    {
+      if (v.at(i) > maxheight)
+      {
+        maxheight = v.at(i);
+        maxbin = i;
+      }
+    }
+
+    float pedestal = 1500;
+    if (maxbin > 4)
+    {
+      pedestal = 0.5 * (v.at(maxbin - 4) + v.at(maxbin - 5));
+    }
+    else if (maxbin > 3)
+    {
+      pedestal = v.at(maxbin - 4);
+    }
+    else
+    {
+      pedestal = 0.5 * (v.at(nsamples - 3) + v.at(nsamples - 2));
+    }
+
+    // Software zero suppression check
+    if ((_bdosoftwarezerosuppression && v.at(6) - v.at(0) < _nsoftwarezerosuppression) ||
+        (_maxsoftwarezerosuppression && maxheight - pedestal < _nsoftwarezerosuppression))
+    {
+      amp = v.at(6) - v.at(0);
+      time = std::numeric_limits<float>::quiet_NaN();
+      ped = v.at(0);
+      if (v.at(0) != 0 && v.at(1) == 0)
+      {
+        chi2 = 1000000;
+      }
+      fit_values.push_back({amp, time, ped, chi2, 0});
+      continue;
+    }
+
+    // Create histogram for fitting
+    TH1F h("h_funcfit", "", nsamples, -0.5, nsamples - 0.5);
+    int ndata = 0;
+    for (int i = 0; i < nsamples; ++i)
+    {
+      if ((v.at(i) == 16383) && _handleSaturation)
+      {
+        continue;
+      }
+      h.SetBinContent(i + 1, v.at(i));
+      h.SetBinError(i + 1, 1);
+      ndata++;
+    }
+
+    // If too many saturated, use all data
+    if (ndata < (nsamples - 4))
+    {
+      ndata = nsamples;
+      for (int i = 0; i < nsamples; ++i)
+      {
+        h.SetBinContent(i + 1, v.at(i));
+        h.SetBinError(i + 1, 1);
+      }
+    }
+
+    double fit_amp = 0;
+    double fit_time = 0;
+    double fit_ped = 0;
+    double chi2val = 0;
+    int npar = 0;
+
+    if (m_funcfit_type == POWERLAWEXP)
+    {
+      // Create fit function with 5 parameters
+      TF1 f("f_powerlaw", SignalShape_PowerLawExp, 0, nsamples, 5);
+      npar = 5;
+
+      // Set initial parameters
+      double risetime = m_powerlaw_power / m_powerlaw_decay;
+      double par[5];
+      par[0] = maxheight - pedestal;  // Amplitude
+      par[1] = maxbin - risetime;     // t0
+      if (par[1] < 0)
+      {
+        par[1] = 0;
+      }
+      par[2] = m_powerlaw_power;  // Power
+      par[3] = m_powerlaw_decay;  // Decay
+      par[4] = pedestal;          // Pedestal
+
+      f.SetParameters(par);
+      f.SetParLimits(0, (maxheight - pedestal) * 0.5, (maxheight - pedestal) * 10);
+      f.SetParLimits(1, 0, nsamples);
+      f.SetParLimits(2, 0, 10.0);
+      f.SetParLimits(3, 0, 10.0);
+      f.SetParLimits(4, pedestal - std::abs(maxheight - pedestal), pedestal + std::abs(maxheight - pedestal));
+
+      // Perform fit
+      h.Fit(&f, "QRN0W", "", 0, nsamples);
+
+      // Calculate peak amplitude and time from fit parameters
+      // Peak height is (p0 * Power(p2/p3, p2)) / exp(p2)
+      fit_amp = (f.GetParameter(0) * pow(f.GetParameter(2) / f.GetParameter(3), f.GetParameter(2))) / exp(f.GetParameter(2));
+      // Peak time is t0 + power/decay
+      fit_time = f.GetParameter(1) + f.GetParameter(2) / f.GetParameter(3);
+      fit_ped = f.GetParameter(4);
+
+      // Calculate chi2
+      for (int i = 0; i < nsamples; i++)
+      {
+        if (h.GetBinContent(i + 1) > 0)
+        {
+          double diff = h.GetBinContent(i + 1) - f.Eval(i);
+          chi2val += diff * diff;
+        }
+      }
+    }
+    else  // POWERLAWDOUBLEEXP
+    {
+      // Create fit function with 7 parameters
+      TF1 f("f_doubleexp", SignalShape_PowerLawDoubleExp, 0, nsamples, 7);
+      npar = 7;
+
+      // Set initial parameters
+      double risetime = 2.0;
+      double par[7];
+      par[0] = (maxheight - pedestal) * 0.7;  // Amplitude
+      par[1] = maxbin - risetime;              // t0
+      if (par[1] < 0)
+      {
+        par[1] = 0;
+      }
+      par[2] = m_doubleexp_power;      // Power
+      par[3] = m_doubleexp_peaktime1;  // Peak Time 1
+      par[4] = pedestal;               // Pedestal
+      par[5] = m_doubleexp_ratio;      // Amplitude ratio
+      par[6] = m_doubleexp_peaktime2;  // Peak Time 2
+
+      f.SetParameters(par);
+      f.SetParLimits(0, (maxheight - pedestal) * -1.5, (maxheight - pedestal) * 1.5);
+      f.SetParLimits(1, maxbin - 3 * risetime, maxbin + risetime);
+      f.SetParLimits(2, 1, 5.0);
+      f.SetParLimits(3, risetime * 0.5, risetime * 4);
+      f.SetParLimits(4, pedestal - std::abs(maxheight - pedestal), pedestal + std::abs(maxheight - pedestal));
+      f.SetParLimits(5, 0, 1);
+      f.SetParLimits(6, risetime * 0.5, risetime * 4);
+
+      // Perform fit
+      h.Fit(&f, "QRN0W", "", 0, nsamples);
+
+      // Find peak by evaluating the function
+      double peakpos1 = f.GetParameter(3);
+      double peakpos2 = f.GetParameter(6);
+      double max_peakpos = f.GetParameter(1) + (peakpos1 > peakpos2 ? peakpos1 : peakpos2);
+      if (max_peakpos > nsamples - 1)
+      {
+        max_peakpos = nsamples - 1;
+      }
+
+      fit_time = f.GetMaximumX(f.GetParameter(1), max_peakpos);
+      fit_amp = f.Eval(fit_time) - f.GetParameter(4);
+      fit_ped = f.GetParameter(4);
+
+      // Calculate chi2
+      for (int i = 0; i < nsamples; i++)
+      {
+        if (h.GetBinContent(i + 1) > 0)
+        {
+          double diff = h.GetBinContent(i + 1) - f.Eval(i);
+          chi2val += diff * diff;
+        }
+      }
+    }
+
+    chi2val /= (ndata - npar);  // divide by ndf
+
+    fit_values.push_back({static_cast<float>(fit_amp), static_cast<float>(fit_time),
+                          static_cast<float>(fit_ped), static_cast<float>(chi2val), 0});
+  }
+
+  return fit_values;
+}

offline/packages/CaloReco/CaloWaveformFitting.h

@@ -9,6 +9,12 @@ class TProfile;
 class CaloWaveformFitting
 {
  public:
+  enum FuncFitType
+  {
+    POWERLAWEXP = 0,
+    POWERLAWDOUBLEEXP = 1,
+  };
+
   CaloWaveformFitting() = default;
   ~CaloWaveformFitting();
 
@@ -61,9 +67,34 @@ class CaloWaveformFitting
   std::vector<std::vector<float>> calo_processing_templatefit(std::vector<std::vector<float>> chnlvector);
   static std::vector<std::vector<float>> calo_processing_fast(const std::vector<std::vector<float>> &chnlvector);
   std::vector<std::vector<float>> calo_processing_nyquist(const std::vector<std::vector<float>> &chnlvector);
+  std::vector<std::vector<float>> calo_processing_funcfit(const std::vector<std::vector<float>> &chnlvector);
 
   void initialize_processing(const std::string &templatefile);
 
+  // Power-law fit function: amplitude * (x-t0)^power * exp(-(x-t0)*decay) + pedestal
+  static double SignalShape_PowerLawExp(double *x, double *par);
+  // Double exponential power-law fit function
+  static double SignalShape_PowerLawDoubleExp(double *x, double *par);
+
+  void set_funcfit_type(FuncFitType type)
+  {
+    m_funcfit_type = type;
+  }
+
+  void set_powerlaw_params(double power, double decay)
+  {
+    m_powerlaw_power = power;
+    m_powerlaw_decay = decay;
+  }
+
+  void set_doubleexp_params(double power, double peaktime1, double peaktime2, double ratio)
+  {
+    m_doubleexp_power = power;
+    m_doubleexp_peaktime1 = peaktime1;
+    m_doubleexp_peaktime2 = peaktime2;
+    m_doubleexp_ratio = ratio;
+  }
+
  private:
   static void FastMax(float x0, float x1, float x2, float y0, float y1, float y2, float &xmax, float &ymax);
   std::vector<float> NyquistInterpolation(std::vector<float> &vec_signal_samples);
@@ -97,5 +128,18 @@ class CaloWaveformFitting
   std::string url_template;
   std::string url_onnx;
   std::string m_model_name;
+
+  // Functional fit type selector
+  FuncFitType m_funcfit_type{POWERLAWEXP};
+
+  // Power-law fit parameters
+  double m_powerlaw_power{4.0};
+  double m_powerlaw_decay{1.5};
+
+  // Double exponential fit parameters
+  double m_doubleexp_power{2.0};
+  double m_doubleexp_peaktime1{5.0};
+  double m_doubleexp_peaktime2{5.0};
+  double m_doubleexp_ratio{0.3};
 };
 #endif