PulseFitWithShape Class Reference

#include <PulseFitWithShape.h>

Inheritance diagram for PulseFitWithShape:

Public Member Functions
virtual double	doFit (double *, double *cova=nullptr)
double	getAmpl ()
double	getTime ()
virtual void	init (int, int, int, int, int, const std::vector< double > &, double)
	PulseFitWithShape ()
	~PulseFitWithShape () override

Public Attributes
double	fAmp_fitted_max
double	fTim_fitted_max

Private Attributes
std::vector< double >	dshape
int	fNb_iter
double	fNoise
int	fNsamples
int	fNsamplesShape
int	fNum_samp_after_max
int	fNum_samp_bef_max
std::vector< double >	pshape

Detailed Description

Definition at line 10 of file PulseFitWithShape.h.

Constructor & Destructor Documentation

PulseFitWithShape()

PulseFitWithShape::PulseFitWithShape

(

)

Definition at line 18 of file PulseFitWithShape.cc.

                                     {
  fNsamples = 0;
  fNsamplesShape = 0;
  fNum_samp_bef_max = 0;
  fNum_samp_after_max = 0;
  fNoise = 0.0;
}

References fNoise, fNsamples, fNsamplesShape, fNum_samp_after_max, and fNum_samp_bef_max.

~PulseFitWithShape()

PulseFitWithShape::~PulseFitWithShape ( )

override

Definition at line 27 of file PulseFitWithShape.cc.

{}

Member Function Documentation

doFit()

double PulseFitWithShape::doFit ( double *  adc, double *  cova = nullptr  )

virtual

Definition at line 60 of file PulseFitWithShape.cc.

                                                         {
  // xpar = fit paramaters
  //     [0] = signal amplitude
  //     [1] = residual pedestal
  //     [2] = clock phase
 
  bool useCova = true;
  if (cova == nullptr)
    useCova = false;
 
  double xpar[3];
  double chi2;
 
  fAmp_fitted_max = 0.;
  fTim_fitted_max = 0.;
 
  // for now don't fit pedestal
 
  xpar[1] = 0.0;
 
  // Sample noise. If the cova matrix is defined, use it :
 
  double noise = fNoise;
  //if(cova[0] > 0.) noise=1./sqrt(cova[0]);
 
  xpar[0] = 0.;
  xpar[2] = 0.;
 
  // first locate max:
 
  int imax = 0;
  double amax = 0.0;
  for (int i = 0; i < fNsamples; i++) {
    if (adc[i] > amax) {
      amax = adc[i];
      imax = i;
    }
  }
 
  // Shift pulse shape and calculate its derivative:
 
  double qms = 0.;
  int ims = 0;
 
  // 1) search for maximum
 
  for (int is = 0; is < fNsamplesShape; is++) {
    if (pshape[is] > qms) {
      qms = pshape[is];
      ims = is;
    }
 
    // 2) compute shape derivative :
 
    if (is < fNsamplesShape - 2)
      dshape[is] = (pshape[is + 2] - pshape[is]) * 12.5;
    else
      dshape[is] = dshape[is - 1];
  }
 
  // 3) compute pol2 max
 
  double sq1 = pshape[ims - 1];
  double sq2 = pshape[ims];
  double sq3 = pshape[ims + 1];
 
  double a2 = (sq3 + sq1) / 2.0 - sq2;
  double a1 = sq2 - sq1 + a2 * (1 - 2 * ims);
 
  double t_ims = 0;
  if (a2 != 0)
    t_ims = -a1 / (2.0 * a2);
 
  // Starting point of the fit : qmax and tmax given by a
  // P2 fit on 3 max samples.
 
  double qm = 0.;
  int im = 0;
 
  int nsamplef = fNum_samp_bef_max + fNum_samp_after_max + 1;  // number of samples used in the fit
  int nsampleo = imax - fNum_samp_bef_max;                     // first sample number = sample max-fNum_samp_bef_max
 
  for (int is = 0; is < nsamplef; is++) {
    if (adc[is + nsampleo] > qm) {
      qm = adc[is + nsampleo];
      im = nsampleo + is;
    }
  }
 
  double tm;
  if (qm > 5. * noise) {
    if (im >= nsamplef + nsampleo)
      im = nsampleo + nsamplef - 1;
    double q1 = adc[im - 1];
    double q2 = adc[im];
    double q3 = adc[im + 1];
    double y2 = (q1 + q3) / 2. - q2;
    double y1 = q2 - q1 + y2 * (1 - 2 * im);
    double y0 = q2 - y1 * (double)im - y2 * (double)(im * im);
    tm = -y1 / 2. / y2;
    xpar[0] = y0 + y1 * tm + y2 * tm * tm;
    xpar[2] = (double)ims / 25. - tm;
  }
 
  double chi2old = 999999.;
  chi2 = 99999.;
  int nsfit = nsamplef;
  int iloop = 0;
  int nloop = fNb_iter;
  if (qm <= 5 * noise)
    nloop = 1;  // Just one iteration for very low signal
 
  std::vector<double> resi(fNsamples, 0.0);
 
  while (std::fabs(chi2old - chi2) > 0.1 && iloop < nloop) {
    iloop++;
    chi2old = chi2;
 
    double c = 0.;
    double y1 = 0.;
    double s1 = 0.;
    double s2 = 0.;
    double ys1 = 0.;
    double sp1 = 0.;
    double sp2 = 0.;
    double ssp = 0.;
    double ysp = 0.;
 
    for (int is = 0; is < nsfit; is++) {
      int iis = is;
      iis = is + nsampleo;
 
      double t1 = (double)iis + xpar[2];
      double xbin = t1 * 25.;
      int ibin1 = (int)xbin;
 
      if (ibin1 < 0)
        ibin1 = 0;
 
      double amp1, amp11, amp12, der1, der11, der12;
 
      if (ibin1 <= fNsamplesShape - 2) {  // Interpolate shape values to get the right number :
 
        int ibin2 = ibin1 + 1;
        double xfrac = xbin - ibin1;
        amp11 = pshape[ibin1];
        amp12 = pshape[ibin2];
        amp1 = (1. - xfrac) * amp11 + xfrac * amp12;
        der11 = dshape[ibin1];
        der12 = dshape[ibin2];
        der1 = (1. - xfrac) * der11 + xfrac * der12;
 
      } else {  // Or extraoplate if we are outside the array :
 
        amp1 = pshape[fNsamplesShape - 1] + dshape[fNsamplesShape - 1] * (xbin - double(fNsamplesShape - 1)) / 25.;
        der1 = dshape[fNsamplesShape - 1];
      }
 
      if (useCova) {  // Use covariance matrix:
        for (int js = 0; js < nsfit; js++) {
          int jjs = js;
          jjs += nsampleo;
 
          t1 = (double)jjs + xpar[2];
          xbin = t1 * 25.;
          ibin1 = (int)xbin;
          if (ibin1 < 0)
            ibin1 = 0;
          if (ibin1 > fNsamplesShape - 2)
            ibin1 = fNsamplesShape - 2;
          int ibin2 = ibin1 + 1;
          double xfrac = xbin - ibin1;
          amp11 = pshape[ibin1];
          amp12 = pshape[ibin2];
          double amp2 = (1. - xfrac) * amp11 + xfrac * amp12;
          der11 = dshape[ibin1];
          der12 = dshape[ibin2];
          double der2 = (1. - xfrac) * der11 + xfrac * der12;
          c = c + cova[js * fNsamples + is];
          y1 = y1 + adc[iis] * cova[js * fNsamples + is];
          s1 = s1 + amp1 * cova[js * fNsamples + is];
          s2 = s2 + amp1 * amp2 * cova[js * fNsamples + is];
          ys1 = ys1 + adc[iis] * amp2 * cova[js * fNsamples + is];
          sp1 = sp1 + der1 * cova[is * fNsamples + js];
          sp2 = sp2 + der1 * der2 * cova[js * fNsamples + is];
          ssp = ssp + amp1 * der2 * cova[js * fNsamples + is];
          ysp = ysp + adc[iis] * der2 * cova[js * fNsamples + is];
        }
      } else {  // Don't use covariance matrix:
        c++;
        y1 = y1 + adc[iis];
        s1 = s1 + amp1;
        s2 = s2 + amp1 * amp1;
        ys1 = ys1 + amp1 * adc[iis];
        sp1 = sp1 + der1;
        sp2 = sp2 + der1 * der1;
        ssp = ssp + der1 * amp1;
        ysp = ysp + der1 * adc[iis];
      }
    }
    xpar[0] = (ysp * ssp - ys1 * sp2) / (ssp * ssp - s2 * sp2);
    xpar[2] += (ysp / xpar[0] / sp2 - ssp / sp2);
 
    for (int is = 0; is < nsfit; is++) {
      int iis = is;
      iis = is + nsampleo;
 
      double t1 = (double)iis + xpar[2];
      double xbin = t1 * 25.;
      int ibin1 = (int)xbin;
      if (ibin1 < 0)
        ibin1 = 0;
 
      if (ibin1 < 0)
        ibin1 = 0;
      if (ibin1 > fNsamplesShape - 2)
        ibin1 = fNsamplesShape - 2;
      int ibin2 = ibin1 + 1;
      double xfrac = xbin - ibin1;
      double amp11 = xpar[0] * pshape[ibin1];
      double amp12 = xpar[0] * pshape[ibin2];
      double amp1 = xpar[1] + (1. - xfrac) * amp11 + xfrac * amp12;
      resi[iis] = adc[iis] - amp1;
    }
 
    chi2 = 0.;
    for (int is = 0; is < nsfit; is++) {
      int iis = is;
      iis += nsampleo;
 
      if (useCova) {
        for (int js = 0; js < nsfit; js++) {
          int jjs = js;
          jjs += nsampleo;
          chi2 += resi[iis] * resi[jjs] * cova[js * fNsamples + is];
        }
 
      } else
        chi2 += resi[iis] * resi[iis];
    }
  }
 
  fAmp_fitted_max = xpar[0];
  fTim_fitted_max = (double)t_ims / 25. - xpar[2];
 
  return chi2;
}

References testProducerWithPsetDescEmpty_cfi::a2, gpuClustering::adc, c, hltPixelTracks_cff::chi2, dshape, fAmp_fitted_max, fNb_iter, fNoise, fNsamples, fNsamplesShape, fNum_samp_after_max, fNum_samp_bef_max, fTim_fitted_max, mps_fire::i, createfilelist::int, gpuVertexFinder::noise, pshape, q1, q2, indexGen::s2, RandomServiceHelper::t1, testProducerWithPsetDescEmpty_cfi::y1, and testProducerWithPsetDescEmpty_cfi::y2.

Referenced by EcalLaserAnalyzer2::endJob().

getAmpl()

double PulseFitWithShape::getAmpl ( )

inline

Definition at line 28 of file PulseFitWithShape.h.

{ return fAmp_fitted_max; }

References fAmp_fitted_max.

Referenced by EcalLaserAnalyzer2::endJob().

getTime()

double PulseFitWithShape::getTime ( )

inline

Definition at line 29 of file PulseFitWithShape.h.

{ return fTim_fitted_max; }

References fTim_fitted_max.

Referenced by EcalLaserAnalyzer2::endJob().

init()

void PulseFitWithShape::init ( int  n_samples, int  samplb, int  sampla, int  niter, int  n_samplesShape, const std::vector< double > &  shape, double  nois  )

virtual

Definition at line 31 of file PulseFitWithShape.cc.

                                          {
  fNsamples = n_samples;
  fNsamplesShape = n_samplesShape;
  fNb_iter = niter;
  fNum_samp_bef_max = samplb;
  fNum_samp_after_max = sampla;
 
  if (fNsamplesShape < fNum_samp_bef_max + fNum_samp_after_max + 1) {
    std::cout << "PulseFitWithShape::init: Error! Configuration samples in fit greater than total number of samples!"
              << std::endl;
  }
 
  for (int i = 0; i < fNsamplesShape; i++) {
    pshape.push_back(shape[i]);
    dshape.push_back(0.0);
  }
 
  fNoise = nois;
  return;
}

References gather_cfg::cout, dshape, fNb_iter, fNoise, fNsamples, fNsamplesShape, fNum_samp_after_max, fNum_samp_bef_max, mps_fire::i, and pshape.

Referenced by EcalLaserAnalyzer2::endJob().

Member Data Documentation

dshape

std::vector<double> PulseFitWithShape::dshape

private

Definition at line 37 of file PulseFitWithShape.h.

Referenced by doFit(), and init().

fAmp_fitted_max

double PulseFitWithShape::fAmp_fitted_max

Definition at line 25 of file PulseFitWithShape.h.

Referenced by doFit(), and getAmpl().

fNb_iter

int PulseFitWithShape::fNb_iter

private

Definition at line 39 of file PulseFitWithShape.h.

Referenced by doFit(), and init().

fNoise

double PulseFitWithShape::fNoise

private

Definition at line 34 of file PulseFitWithShape.h.

Referenced by doFit(), init(), and PulseFitWithShape().

fNsamples

int PulseFitWithShape::fNsamples

private

Definition at line 32 of file PulseFitWithShape.h.

Referenced by doFit(), init(), and PulseFitWithShape().

fNsamplesShape

int PulseFitWithShape::fNsamplesShape

private

Definition at line 33 of file PulseFitWithShape.h.

Referenced by doFit(), init(), and PulseFitWithShape().

fNum_samp_after_max

int PulseFitWithShape::fNum_samp_after_max

private

Definition at line 41 of file PulseFitWithShape.h.

Referenced by doFit(), init(), and PulseFitWithShape().

fNum_samp_bef_max

int PulseFitWithShape::fNum_samp_bef_max

private

Definition at line 40 of file PulseFitWithShape.h.

Referenced by doFit(), init(), and PulseFitWithShape().

fTim_fitted_max

double PulseFitWithShape::fTim_fitted_max

Definition at line 26 of file PulseFitWithShape.h.

Referenced by doFit(), and getTime().

pshape

std::vector<double> PulseFitWithShape::pshape

private

Definition at line 36 of file PulseFitWithShape.h.

Referenced by doFit(), and init().