JetFitAnalyzer/src/jetfit.cpp

/* jetfit.cpp - Package to fit multi-Gaussian distributions to histograms
 * rewrite after accidental deletion 07-24-09
 * Author: David Nisson
 */

#include <cstdlib>
#include <cmath>
#include <ctime>
#include <cstdio>
#include <cstring>
#include <cctype>
#include <iostream>
#include <fstream>
#include <sstream>
#include <string>
#include <vector>
#include <set>
#include <map>
#include <limits>
#include <exception>

#include <TMinuit.h>
#include <TH1.h>
#include <TH2.h>
#include <TF2.h>
#include <TRandom3.h>
#include <Rtypes.h>
#include <TFormula.h>
#include <TSystem.h>

#include "UserCode/JetFitAnalyzer/interface/jetfit.h"

#define PI 3.141592653

#define MAX_GAUSS 3

using namespace std;

namespace jetfit {
  // configurable options
  bool ignorezero = false; // ignore zero bins when fitting
  
  struct histo {
    vector< vector<double> > bins;
    double Xlo, Xhi, Ylo, Yhi;
  } energy;


  model_def *mdef;

  model_def& curr_model_def() {
    return *mdef;
  }

  void set_model_def(model_def *_mdef) {
    mdef = _mdef;
  }

  int model_def::get_ngauss() {
    return ngauss;
  }
  
  void model_def::set_ngauss(int _ngauss) {
    ngauss = _ngauss;
  }

  // fit function
  double model_def::fit_fcn(double x, double y, double *xval) {
    int npar_indiv = get_formula()->GetNpar();
    double val = 0.0;
    for (int i = 0; i < ngauss; i++) {
      get_formula()->SetParameters(xval + i*npar_indiv);
      val += mdef->get_formula()->Eval(x, y);
    }
    return val;
  }

  // TF2-compatible fit function
  double fit_fcn_TF2(double *x, double *pval) {
    double val = mdef->fit_fcn(x[0], x[1], pval);
    return val;
  }

  // Integral of (model formula)^2 / chisquare sigma
  double model_def::formula_int(double xlo, double xhi, double ylo, double yhi,
                     double *pval, double XbinSize, double YbinSize,
                     double *xval) {
    double xstep = (xhi - xlo) / static_cast<double>(20);
    double ystep = (yhi - ylo) / static_cast<double>(20);

    double fsum = 0.0;
    double pval_old[256];
    int npar = get_formula()->GetNpar();
    if (npar > 256) {
      cerr << "Parameter overload" << endl;
      return 0.0;
    }
    get_formula()->GetParameters(pval_old);
    get_formula()->SetParameters(pval);

    for (int i = 0; i < 20; i++) {
      for (int j = 0; j < 20; j++) {
        double x = (static_cast<double>(i) + 0.5)*xstep + xlo;
        double y = (static_cast<double>(j) + 0.5)*ystep + ylo;
        double sig_cut = 1.0e-5;
        double nu = XbinSize * YbinSize * fit_fcn(x, y, xval);
        double sigma = fabs(chisquare_error(0.0)) < sig_cut
          ? sig_cut : chisquare_error(0.0);

        fsum += pow(xstep * ystep * get_formula()->Eval(x, y), 2.0)
          / sigma / sigma;
      }
    }

    get_formula()->SetParameters(pval_old);
    return fsum;
  }

  // MINUIT objective function 
  void fcn(int &npar, double *grad, double &fcnval, double *xval, int iflag)
  {
    double chisquare = 0.0;
    double XbinSize = (energy.Xhi - energy.Xlo)
      / static_cast<double>(energy.bins.size());
    double YbinSize = (energy.Yhi - energy.Ylo)
      / static_cast<double>(energy.bins.at(0).size());
    try {
      // add errors in data points in histogram
      for (int i = 0; i < energy.bins.size(); i++) {
        for (int j = 0; j < energy.bins.at(i).size(); j++) {
          double x = (static_cast<double>(i) + 0.5) * (energy.Xhi - energy.Xlo)
            / static_cast<double>(energy.bins.size()) + energy.Xlo;
          double y = (static_cast<double>(j) + 0.5) * (energy.Yhi - energy.Ylo)
            / static_cast<double>(energy.bins.at(i).size()) + energy.Ylo;
          double nu = mdef->fit_fcn(x, y, xval) * XbinSize * YbinSize;
          double sig_cut = 1.0e-5;
          if (fabs(mdef->chisquare_error(energy.bins.at(i).at(j))) > sig_cut || !ignorezero) {
            chisquare += pow(energy.bins.at(i).at(j) - nu, 2.0) 
              / pow(mdef->chisquare_error(energy.bins.at(i).at(j)), 2.0);
          }
          else {
            chisquare += pow(energy.bins.at(i).at(j) - nu, 2.0) 
              / pow(sig_cut, 2.0);
          }
        }
      }
      
      // add errors due to Gaussians outside histogram
      double eps = 0.01; // accuracy set for this function
      for (int i = 0; i < mdef->get_ngauss(); i++) {
        double *pval = xval+i*(mdef->get_formula()->GetNpar());
        double par_x = pval[mdef->get_indiv_max_x()];
        double par_y = pval[mdef->get_indiv_max_y()];
        double par_sig = pval[3];
        double cutoff_rad = sqrt(-log(eps * 2.0 * PI * par_sig * par_sig
          / pval[0]) * 2.0 * par_sig * par_sig);

        bool left = par_x < energy.Xlo + cutoff_rad;
        bool right = par_x > energy.Xhi - cutoff_rad;
        bool top = par_y > energy.Yhi - cutoff_rad;
        bool bottom = par_y < energy.Ylo + cutoff_rad;

        if (left) {
          double xlo = par_x - cutoff_rad;
          double xhi = energy.Xlo;
          double ylo = energy.Ylo;
          double yhi = energy.Yhi;
          chisquare += 2.0*mdef->formula_int(xlo, xhi, ylo, yhi, pval,
                                   XbinSize, YbinSize, xval);
        }
        if (right) {
          double xlo = energy.Xhi;
          double xhi = par_x + cutoff_rad;
          double ylo = energy.Ylo;
          double yhi = energy.Yhi;
          chisquare += 2.0*mdef->formula_int(xlo, xhi, ylo, yhi, pval,
                                   XbinSize, YbinSize, xval);
        }
        if (top) {
          double xlo = left ? par_x - cutoff_rad : energy.Xlo;
          double xhi = right ? par_x + cutoff_rad : energy.Xhi;
          double ylo = energy.Yhi;
          double yhi = par_y + cutoff_rad;
          chisquare += 2.0*mdef->formula_int(xlo, xhi, ylo, yhi, pval,
                                   XbinSize, YbinSize, xval);
        }
        if (bottom) {
          double xlo = left ? par_x - cutoff_rad : energy.Xlo;
          double xhi = right ? par_x + cutoff_rad : energy.Xhi;
          double ylo = par_y - cutoff_rad;
          double yhi = energy.Ylo;
          chisquare += 2.0*mdef->formula_int(xlo, xhi, ylo, yhi, pval,
                                   XbinSize, YbinSize, xval);
        }
      }
      
      fcnval = chisquare;
    }
    catch (exception ex) {
      cerr << "Exception in jetfit::fcn" << endl;
    }
  }

  bool get_ignorezero() {
    return ignorezero;
  }

  void set_ignorezero(bool _iz) {
    ignorezero = _iz;
  }

  TFormula * model_def::get_formula() {
    return indiv_formula;
  }

  void model_def::set_formula(TFormula *new_formula) {
    indiv_formula = new_formula;
  }

  void model_def::get_indiv_par(int i, string &name, double &start, double &step,
                     double &lo, double &hi) {
    try {
      name = indiv_par_names.at(i);
      start = indiv_par_starts.at(i);
      step = indiv_par_start_steps.at(i);
      lo = indiv_par_lo.at(i);
      hi = indiv_par_hi.at(i);
    } catch (exception ex) {
      cerr << "exception in jetfit::model_def::get_indiv_par" << endl;
    }
  }

  void model_def::set_indiv_par(int i, string name, double start, double step,
                     double lo, double hi) {
    if (indiv_par_names.size() < i+1) {
      indiv_par_names.resize(i+1);
      indiv_par_starts.resize(i+1);
      indiv_par_start_steps.resize(i+1);
      indiv_par_lo.resize(i+1);
      indiv_par_hi.resize(i+1);
    }
    try {
      indiv_par_names.at(i) = name;
      indiv_par_starts.at(i) = start;
      indiv_par_start_steps.at(i) = step;
      indiv_par_lo.at(i) = lo;
      indiv_par_hi.at(i) = hi;
    }
    catch (exception ex) {
      cerr << "exception in jetfit::model_def::set_indiv_par" << endl;
    }
  }

  int model_def::get_indiv_max_E() {
    return indiv_max_E;
  }

  void model_def::set_indiv_max_E(int _new_max_E) {
    indiv_max_E = _new_max_E;
  }

  int model_def::get_indiv_max_x() {
    return indiv_max_x;
  }

  void model_def::set_indiv_max_x(int new_max_x) {
    indiv_max_x = new_max_x;
  }

  int model_def::get_indiv_max_y() {
    return indiv_max_y;
  }

  void model_def::set_indiv_max_y(int new_max_y) {
    indiv_max_y = new_max_y;
  }

  unsigned model_def::get_n_special_par_sets() {
    return special_par_starts.size();
  }

  void model_def::get_special_par(int g, int i, double &pstart,
                                  double &perr, double &plo, double &phi) {
    try {
      pstart = special_par_starts.at(g).at(i);
      perr = special_par_start_steps.at(g).at(i);
      plo = special_par_lo.at(g).at(i);
      phi = special_par_hi.at(g).at(i);
    } catch (exception ex) {
      cerr << "Exception in model_def::get_special_par" << endl;
    }
  }

  void model_def::set_special_par(int g, int i, double pstart,
                                  double perr, double plo, double phi) {
    if (g+1 > special_par_starts.size()) {
      special_par_starts.resize(g+1);
      special_par_start_steps.resize(g+1);
      special_par_lo.resize(g+1);
      special_par_hi.resize(g+1);
    }

    try {
      if (i+1 > special_par_starts.at(g).size()) {
        special_par_starts.at(g).resize(i+1);
        special_par_start_steps.at(g).resize(i+1);
        special_par_lo.at(g).resize(i+1);
        special_par_hi.at(g).resize(i+1);
      }

      special_par_starts.at(g).at(i) = pstart;
      special_par_start_steps.at(g).at(i) = perr;
      special_par_lo.at(g).at(i) = plo;
      special_par_hi.at(g).at(i) = phi;
    }
    catch (exception ex) {
      cerr << "exception in jetfit::model_def::set_special_par" << endl;
    }
  }

  // translation of CERN's ERFC function
  double erfc(double x) {
    bool lef = false;
    double p2[5], q2[5];

    const double z1 = 1.0, hf = z1/2.0, c1 = 0.56418958;
    const double vmax = 7.0;
    const double switch_ = 4.0;

    double p10 = 3.6767877, q10 = 3.2584593, p11 = -9.7970465e-2;
    p2[0] = 7.3738883;
    q2[0] = 7.3739609;
    p2[1] = 6.8650185;
    q2[1] = 1.5184908e1;
    p2[2] = 3.0317993;
    q2[2] = 1.2795530e1;
    p2[3] = 5.6316962e-1;
    q2[3] = 5.3542168;
    p2[4] = 4.3187787e-5;
    q2[4] = 1.0;

    double p30 = -1.2436854e-1, q30 = 4.4091706e-1, p31 = -9.6821036e-2;

    double v = fabs(x);
    double y, h, hc, ap, aq;
    if (v < hf) {
      y = v*v;
      h = x*(p10 + p11*y)/(q10 + y);
      hc = 1.0 - h;
    }
    else {
      if (v < switch_) {
        ap = p2[4];
        aq = q2[4];
        for (int i = 3; i >= 0; i--) {
          ap = p2[i] + v*ap;
          aq = q2[i] + v*aq;
        }
        hc = exp(-v*v)*ap/aq;
        h = 1.0 - hc;
      }
      else if (v < vmax) {
        y = 1/v/v;
        hc = exp(-v*v)*(c1 + y*(p30 + p31*y)/(q30 + y))/v;
        h = 1.0 - hc;
      }
      // for very big values we can save us any calculation
      // and the FP-exceptions from exp
      else {
        h = 1.0;
        hc = 0.0;
      }
      if (x < 0) {
        h = -h;
        hc = 2.0 - hc;
      }
    }
    if (lef) {
      return h;
    }
    else {
      return hc;
    }
  }

  // translation of CERN's PROB function
  double prob(double x, int n) {
    const char *name = "PROB";
    char errtxt[80];

    const double r1 = 1.0,
      hf = r1/2.0, th = r1/3.0, f1 = 2.0*r1/9.0;
    const double c1 = 1.128379167095513;
    const int nmax = 300;
    // maximum chi2 per df for df >= 2., if chi2/df > chipdf prob=0
    const double chipdf = 100.0;
    const double xmax = 174.673, xmax2 = 2.0*xmax;
    const double xlim = 24.0;
    const double eps = 1e-30;

    double y = x;
    double u = hf*y;
    double h, w, s, t, fi, e;
    int m;
    if (n < 0) {
      h = 0.0;
      sprintf(errtxt, "n = %d < 1", n);
      cerr << "PROB: G100.1: "<<errtxt;
    }
    else if (y < 0.0) {
      h = 0.0;
      sprintf(errtxt, "x = %f < 0", n);
      cerr << "PROB: G100.2: "<<errtxt;
    }
    else if (y == 0.0 || n/20 > y) {
      h = 1.0;
    }
    else if (n == 1) {
      w = sqrt(u);
      if (w < xlim) {
        h = erfc(w);
      }
      else {
        h = 0.0;
      }
    }
    else if (n > nmax) {
      s = r1 / ((double)n);
      t = f1 * s;
      w = (pow(y*s, th) - (1.0 - t)) / sqrt(2.0*t);
      if (w < -xlim) {
        h = 1.0;
      }
      else if (w < xlim) {
        h = hf * erfc(w);
      }
      else {
        h = 0.0;
      }
    }
    else {
      m = n/2;
      if (u < xmax2 && (y/n) <= chipdf) {
        s = exp(-hf*u);
        t = s;
        e = s;
        if (2*m == n) {
          fi = 0.0;
          for (int i = 1; i < m; i++) {
            fi += 1.0;
            t = u*t/fi;
            s += t;
          }
          h = s*e;
        }
        else {
          fi = 1.0;
          for (int i = 1; i < m; i++) {
            fi += 2.0;
            t = t*y/fi;
            s += t;
          }
          w = sqrt(u);
          if (w < xlim) {
            h = c1*w*s*e + erfc(w);
          }
          else {
            h = 0.0;
          }
        }
      }
      else {
        h = 0.0;
      }
    }
    if (h > eps) {
      return h;
    }
    else {
      return 0.0;
    }
  }
 
  void fill_histo_with_vec(TH2 *hist, vector< vector<double> > &vec) {
    for (int i = 0; i < vec.size(); i++) {
      for (int j = 0; j < vec[i].size(); j++) {
        hist->SetBinContent(i+1, j+1, vec[i][j]);
      }
    }
  }

  void model_def::par_init(TH2 *hist, TMinuit *gMinuit, vector<TString> &pars,
                double *pval, double *perr, double *plo, double *phi,
                int npar, results r) {
    int npar1 = npar - get_formula()->GetNpar();
    bool init_spec_pars = false;
    if (ngauss <= get_n_special_par_sets()) {
      init_spec_pars = true;
      for (int k = 0; k < ngauss; k++) {
        int ipar0 = k*get_formula()->GetNpar(); // index of indiv par 0
        for (int l = 0; l < get_formula()->GetNpar(); l++) {
          int ipar = ipar0 + l;
          if (ipar < npar)
            get_special_par(k, l, pval[ipar], perr[ipar], plo[ipar],
                                 phi[ipar]);
          else
            cerr << "WARNING: Attempt to set parameter out of index range!"
                 << endl;
        }
      }
    }
    else {
      double XbinSize = (energy.Xhi - energy.Xlo)
        / static_cast<double>(energy.bins.size());
      double YbinSize = (energy.Xhi - energy.Xlo)
        / static_cast<double>(energy.bins.at(0).size());
      vector< vector<double> > sub_energy(energy.bins.size());
      double max_sub, max_x = 0.0, max_y = 0.0;
      double pval_other[256];
      max_sub = -(numeric_limits<double>::max());
      for (int i = 0; i < energy.bins.size(); i++) {
        sub_energy[i].resize(energy.bins[i].size());
        for (int j = 0; j < energy.bins[i].size(); j++) {
          double x = static_cast<double>(i)*(energy.Xhi - energy.Xlo)
            / static_cast<double>(energy.bins.size()) + energy.Xlo;
          double y = static_cast<double>(j)*(energy.Yhi - energy.Ylo)
            / static_cast<double>(energy.bins[i].size()) + energy.Ylo;
          if (ngauss > 1) {
            // subtract integral of fit function
            try {
              int npval_other = r.pval.at(r.pval.size()-1).size();
              if (npval_other > 256) {
                cerr << "Parameter overload" << endl;
                return;
              }
              for (int k = 0; k < npval_other; k++) {
                pval_other[k] = r.pval[r.pval.size()-1][k];
              }
              ngauss--;
              double nu = fit_fcn(x, y, pval_other) * XbinSize * YbinSize;
              ngauss++;
              sub_energy[i][j] = energy.bins[i][j] - nu;
            }
            catch (exception ex) {
              cerr << "Exception in par_init" << endl;
            }
          }
          else {
            sub_energy[i][j] = energy.bins[i][j];
          }
        }
      }
      TH2D *hist_sub = new TH2D("hist_sub", "Subtracted histo",
                                sub_energy.size(), energy.Xlo,
                                energy.Xhi,
                                sub_energy[0].size(), energy.Ylo,
                                energy.Yhi);
      fill_histo_with_vec(hist_sub, sub_energy);
      max_sub = 0.0;
      max_x = 0.0;
      max_y = 0.0;
      for (int i = 1; i <= hist_sub->GetXaxis()->GetNbins(); i++) {
        for (int j = 1; j <= hist_sub->GetYaxis()->GetNbins(); j++) {
          double nu = energy.bins[i-1][j-1] - sub_energy[i-1][j-1];
          if (hist_sub->GetBinContent(i, j) 
              - 3.0*pow(chisquare_error(nu), 2.0) > max_sub) {
            max_sub = hist_sub->GetBinContent(i, j);
            max_x = static_cast<double>(i-1)*XbinSize
              + hist_sub->GetXaxis()->GetXmin();
            max_y = static_cast<double>(j-1)*YbinSize
              + hist_sub->GetYaxis()->GetXmin();
          }
        }
      }  

      for (int i = npar1; i < npar; i++) {
        if (get_indiv_max_E() == i - npar1) {
          pval[i] = max_sub / XbinSize / YbinSize;
          perr[i] = mdef->chisquare_error(pval[i])*0.5;
          plo[i] = 0.0;
          phi[i] = 1.0e6;
        }
        else if (get_indiv_max_x() == i - npar1) {
          pval[i] = max_x;
          perr[i] = (energy.Xhi - energy.Xlo) / static_cast<double>(hist->GetXaxis()->GetNbins());
          plo[i] = 0.0;
          phi[i] = 0.0;
        }
        else if (get_indiv_max_y() == i - npar1) {
          pval[i] = max_y;
          perr[i] = (energy.Yhi - energy.Ylo) / static_cast<double>(hist->GetYaxis()->GetNbins());
          plo[i] = 0.0;
          phi[i] = 0.0;
        }
        else {
          string dummy;
          get_indiv_par(i-npar1, dummy, pval[i], perr[i], plo[i], phi[i]);
        }
      }
    }
    int n_pars_to_set = init_spec_pars ? ngauss*get_formula()->GetNpar()
      : npar - npar1;
    int init_par_to_set = init_spec_pars ? 0 : npar1;
    for (int i = 0; i < n_pars_to_set; i++) {
      double dummy;
      string s;
      int ipar = i + init_par_to_set;
      get_indiv_par(i % get_formula()->GetNpar(), s,
                         dummy, dummy, dummy, dummy);
      ostringstream par_oss;
      par_oss << s << ipar / (get_formula()->GetNpar()) << flush;
      try {
        pars.at(ipar) = TString(par_oss.str());
      }
      catch (exception ex) {
        cerr << "exception 2 in par_init" << endl;
      }
      int error_flag;
      try {
        gMinuit->mnparm(ipar, pars.at(ipar),
                        pval[ipar], perr[ipar], plo[ipar], phi[ipar], error_flag);
      } catch (exception ex) {
        cerr << "exception 3 in par_init" << endl;
      }
    }
  }

  results model_def::fit_histo(TH2 *hist, vector<trouble> &t_vec,
                               void (*cc_minuit)(TMinuit *, TH2 *, int),
                               int start_ngauss,
                               int rebinX, int rebinY,
                               double P_cutoff_val) {
    set_model_def(this);
    TMinuit *gMinuit = new TMinuit();
    int npar_indiv = mdef->get_formula()->GetNpar();
    int istat, erflg;
    results r;
    r.moddef = this;

    gMinuit->SetFCN(fcn);
    gMinuit->mninit(5, 6, 7);

    // set error def and machine accuracy
    double cs_err_def = 1.0;
    double fcn_eps = 0.2;
    gMinuit->mnexcm("SET ERR", &cs_err_def, 1, erflg);
    gMinuit->mnexcm("SET EPS", &fcn_eps, 1, erflg);

    // rebin histogram
    TH2 *hist_rebinned;
    if (rebinX > 1 && rebinY > 1)
      hist_rebinned = hist->Rebin2D(rebinX, rebinY);
    else
      hist_rebinned = hist;

    r.hist_rebinned = hist_rebinned;
    // load histogram into energies vector
    energy.bins.resize(hist_rebinned->GetXaxis()->GetNbins());
    for (int i = 0; i < energy.bins.size(); i++) {
      energy.bins[i].resize(hist_rebinned->GetYaxis()->GetNbins());
      for (int j = 0; j < energy.bins[i].size(); j++) {
        energy.bins[i][j] = hist_rebinned->GetBinContent(i+1, j+1);
      }
    }

    energy.Xlo = hist->GetXaxis()->GetXmin();
    energy.Xhi = hist->GetXaxis()->GetXmax();
    energy.Ylo = hist->GetYaxis()->GetXmin();
    energy.Yhi = hist->GetYaxis()->GetXmax();
    
    if (start_ngauss < 1) {
      start_ngauss = 1;
    }

    for (ngauss = start_ngauss;
         ngauss <= (MAX_GAUSS > start_ngauss ? MAX_GAUSS : start_ngauss);
         ngauss++) {
      
      t_vec.resize(t_vec.size() + 1);
      int npar = npar_indiv*ngauss;
      double pval[256], perr[256], plo[256], phi[256];
      if (npar > 256) {
        cerr << "Parameter overload" << endl;
        return r;
      }
      vector<TString> pars(npar);

      // initialize parameters
      par_init(hist, gMinuit, pars, pval, perr, plo, phi, npar, r);

      // minimize
      double chisquare, edm, errdef;
      int nvpar, nparx;
      trouble t;
      t.occ = T_NULL;
      t.istat = 3;
      // fix sigmas of the Gaussians
      for (int i = 0; i < ngauss; i++) {
        double parno[2];
        parno[0] = i*npar_indiv + 4;
        gMinuit->mnexcm("FIX", parno, 1, erflg);
      }
      gMinuit->mnexcm("SIMPLEX", 0, 0, erflg);
      gMinuit->mnexcm("MIGRAD", 0, 0, erflg);
      gMinuit->mnstat(chisquare, edm, errdef, nvpar, nparx, istat);
      if (istat == 3) {
        /* we're not concerned about MINOS errors right now
        gMinuit->mnexcm("MINOS", 0, 0, erflg);
        gMinuit->mnstat(chisquare, edm, errdef, nvpar, nparx, istat);
        if (istat != 3) {
          t.occ = T_MINOS;
          t.istat = istat;
        }
        */
      }
      else {
        t.occ = T_MIGRAD;
        t.istat = istat;
      }

      try {
        if (t_vec.size() < ngauss) {
          t_vec.resize(ngauss);
        }
        t_vec.at(ngauss-1) = t;
      }
      catch (exception ex) {
        cerr << "exception in fit_histo" << endl;
      }

      // put parameters in map
      for (int i = 0; i < npar && i < 256; i++) {
        int iuint; // internal parameter number
        gMinuit->mnpout(i, pars[i], pval[i], perr[i], plo[i], phi[i], iuint);
      }
      vector<double> pval_copy(npar);
      vector<double> perr_copy(npar);
      vector<double> plo_copy(npar);
      vector<double> phi_copy(npar);
      for (int i = 0; i < npar && i < 256; i++) {
        pval_copy[i] = pval[i];
        perr_copy[i] = perr[i];
        plo_copy[i] = plo[i];
        phi_copy[i] = phi[i];
      }
      r.pars.push_back(pars);
      r.pval.push_back(pval_copy);
      r.perr.push_back(perr_copy);
      r.plo.push_back(plo_copy);
      r.phi.push_back(phi_copy);

      // execute user minuit code
      if (cc_minuit != 0)
        (*cc_minuit)(gMinuit, hist_rebinned, ngauss);

      int ndof = 0;
      if (!ignorezero)
        ndof = energy.bins.size() * energy.bins[0].size();
      else {
        for (int i = 0; i < energy.bins.size(); i++) {
          for (int j = 0; j < energy.bins[i].size(); j++) {
            if (energy.bins[i][j] > 1.0e-30)
              ndof++;
          }
        }
      }
      ndof -= npar;

      r.chisquare.push_back(chisquare);
      double P = prob(chisquare, ndof);
      if (P > P_cutoff_val) {
        break;
      }
    }

    delete gMinuit;
    return r;
  }
}
Revision:	1.10
Committed:	Wed Nov 11 01:46:56 2009 UTC (15 years, 5 months ago) by dnisson
Branch:	MAIN
Changes since 1.9:	+42 -41 lines
Log Message:	Encapsulated functions into class model_def, as appropriate.