#include <EcalUncalibRecHitRatioMethodAlgo.h>

Classes
struct	CalculatedRecHit

struct	Ratio

struct	Tmax

Public Member Functions
void	computeAmplitude (std::vector< double > &amplitudeFitParameters)

double	computeAmplitudeImpl (std::vector< double > &amplitudeFitParameters, double, double)

void	computeTime (std::vector< double > &timeFitParameters, std::pair< double, double > &timeFitLimits, std::vector< double > &amplitudeFitParameters)

bool	fixMGPAslew (const C &dataFrame)

CalculatedRecHit	getCalculatedRecHit ()

void	init (const C &dataFrame, const EcalSampleMask &sampleMask, const double pedestals, const double pedestalRMSes, const double *gainRatios)

EcalUncalibratedRecHit	makeRecHit (const C &dataFrame, const EcalSampleMask &sampleMask, const double pedestals, const double pedestalRMSes, const double *gainRatios, std::vector< double > &timeFitParameters, std::vector< double > &amplitudeFitParameters, std::pair< double, double > &timeFitLimits)

Protected Attributes
std::array< double, C::MAXSAMPLES >	amplitudeErrors_

std::array< double, C::MAXSAMPLES >	amplitudeIE2_

std::array< double, C::MAXSAMPLES >	amplitudes_

double	ampMaxError_

CalculatedRecHit	calculatedRechit_

int	num_

double	pedestal_

EcalSampleMask	sampleMask_

DetId	theDetId_

std::array< bool, C::MAXSAMPLES >	useless_

Detailed Description

template<class C>
class EcalUncalibRecHitRatioMethodAlgo< C >

Template used to compute amplitude, pedestal, time jitter, chi2 of a pulse using a ratio method

Author: A. Ledovskoy (Design) - M. Balazs (Implementation)

Definition at line 31 of file EcalUncalibRecHitRatioMethodAlgo.h.

Member Function Documentation

template<class C >

void EcalUncalibRecHitRatioMethodAlgo< C >::computeAmplitude ( std::vector< double > & amplitudeFitParameters )

Definition at line 560 of file EcalUncalibRecHitRatioMethodAlgo.h.

Referenced by EcalUncalibRecHitWorkerGlobal::run().

                                                {
 
   calculatedRechit_.amplitudeMax =
       computeAmplitudeImpl(amplitudeFitParameters, 1., 1.);
 
 }

template<class C >

double EcalUncalibRecHitRatioMethodAlgo< C >::computeAmplitudeImpl	(	std::vector< double > &	amplitudeFitParameters,
		double	corr4,
		double	corr6
	)

Definition at line 569 of file EcalUncalibRecHitRatioMethodAlgo.h.

References beta, alignCSCRings::e, f, myMath::fast_expf(), myMath::fast_logf(), and i.

                                                                            {
   //                                                            //
   //             CALCULATE AMPLITUDE                            //
   //                                                            //
 
   double alpha = amplitudeFitParameters[0];
   double beta = amplitudeFitParameters[1];
 
   // calculate pedestal, again
 
   double pedestalLimit = calculatedRechit_.timeMax - (alpha * beta) - 1.0;
   double sumA = 0;
   double sumF = 0;
   double sumAF = 0;
   double sumFF = 0;
   double sum1 = 0;
   for (unsigned int i = 0; i < amplitudes_.size(); i++) {
     if (useless_[i]) continue;
     double inverr2 = amplitudeIE2_[i];
     double f = 0;
     double termOne = 1 + (i - calculatedRechit_.timeMax) / (alpha * beta);
     if (termOne > 1.e-5)
       f = myMath::fast_expf(alpha * myMath::fast_logf(termOne) -
                             (i - calculatedRechit_.timeMax) / beta);
 
     // apply range of interesting samples
 
     if ((i < pedestalLimit) ||
         (f > 0.6 * corr6 && i <= calculatedRechit_.timeMax) ||
         (f > 0.4 * corr4 && i >= calculatedRechit_.timeMax)) {
       sum1 += inverr2;
       sumA += amplitudes_[i] * inverr2;
       sumF += f * inverr2;
       sumAF += (f * inverr2) * amplitudes_[i];
       sumFF += f * (f * inverr2);
     }
   }
 
   double amplitudeMax = 0;
   if (sum1 > 0) {
     double denom = sumFF * sum1 - sumF * sumF;
     if (fabs(denom) > 1.0e-20) {
       amplitudeMax = (sumAF * sum1 - sumA * sumF) / denom;
     }
   }
   return amplitudeMax;
 }

template<class C >

void EcalUncalibRecHitRatioMethodAlgo< C >::computeTime	(	std::vector< double > &	timeFitParameters,
		std::pair< double, double > &	timeFitLimits,
		std::vector< double > &	amplitudeFitParameters
	)

Definition at line 224 of file EcalUncalibRecHitRatioMethodAlgo.h.

References alpha, beta, EcalUncalibRecHitRatioMethodAlgo< C >::Tmax::chi2, alignCSCRings::e, f, myMath::fast_expf(), myMath::fast_logf(), i, EcalUncalibRecHitRatioMethodAlgo< C >::Tmax::index, cmsHarvester::index, j, gen::k, max(), evf::evtn::offset(), Gflash::Rmax, Gflash::Rmin, mathSSE::sqrt(), relval_parameters_module::step, tmax, and relativeConstraints::value.

Referenced by EcalUncalibRecHitWorkerGlobal::run().

                                                {
   //                                                          //
   //              RATIO METHOD FOR TIME STARTS HERE           //
   //                                                          //
   double ampMaxAlphaBeta = 0;
   double tMaxAlphaBeta = 5;
   double tMaxErrorAlphaBeta = 999;
   double tMaxRatio = 5;
   double tMaxErrorRatio = 999;
 
   double sumAA = 0;
   double sumA = 0;
   double sum1 = 0;
   double sum0 = 0;
   double sumAf = 0;
   double sumff = 0;
   double NullChi2 = 0;
 
   // null hypothesis = no pulse, pedestal only
   for (unsigned int i = 0; i < amplitudes_.size(); i++) {
     if (useless_[i]) continue;
     double inverr2 = amplitudeIE2_[i];
     sum0 += 1;
     sum1 += inverr2;
     sumA += amplitudes_[i] * inverr2;
     sumAA += amplitudes_[i] * (amplitudes_[i] * inverr2);
   }
   if (sum0 > 0) {
     NullChi2 = (sumAA - sumA * sumA / sum1) / sum0;
   } else {
     // not enough samples to reconstruct the pulse
     return;
   }
 
   // Make all possible Ratio's based on any pair of samples i and j
   // (j>i) with positive amplitudes_
   //
   //       Ratio[k] = Amp[i]/Amp[j]
   //       where Amp[i] is pedestal subtracted ADC value in a time sample [i]
   //
   double alphabeta = amplitudeFitParameters[0] * amplitudeFitParameters[1];
   double invalphabeta = 1. / alphabeta;
   double alpha = amplitudeFitParameters[0];
   double beta = amplitudeFitParameters[1];
 
   Ratio ratios_[C::MAXSAMPLES * (C::MAXSAMPLES - 1) / 2];
   unsigned int ratios_size = 0;
 
   double Rlim[amplitudes_.size()];
   for (unsigned int k = 1; k != amplitudes_.size(); ++k)
     Rlim[k] = myMath::fast_expf(double(k) / beta) - 0.001;
 
   double relErr2[amplitudes_.size()];
   double invampl[amplitudes_.size()];
   for (unsigned int i = 0; i < amplitudes_.size(); i++) {
     invampl[i] = (useless_[i]) ? 0 : 1. / amplitudes_[i];
     relErr2[i] = (useless_[i]) ? 0 : (amplitudeErrors_[i] * invampl[i]) *
                                          (amplitudeErrors_[i] * invampl[i]);
   }
 
   for (unsigned int i = 0; i < amplitudes_.size() - 1; i++) {
     if (useless_[i]) continue;
     for (unsigned int j = i + 1; j < amplitudes_.size(); j++) {
       if (useless_[j]) continue;
 
       if (amplitudes_[i] > 1 && amplitudes_[j] > 1) {
 
         // ratio
         double Rtmp = amplitudes_[i] / amplitudes_[j];
 
         // error^2 due to stat fluctuations of time samples
         // (uncorrelated for both samples)
 
         double err1 = Rtmp * Rtmp * (relErr2[i] + relErr2[j]);
 
         // error due to fluctuations of pedestal (common to both samples)
         double stat;
         if (num_ > 0)
           stat = num_;  // num presampeles used to compute pedestal
         else
           stat = 1;                               // pedestal from db
         double err2 = amplitudeErrors_[j] * (amplitudes_[i] - amplitudes_[j]) *
                       (invampl[j] * invampl[j]);  // /sqrt(stat);
         err2 *= err2 / stat;
 
         //error due to integer round-down. It is relevant to low
         //amplitudes_ in gainID=1 and negligible otherwise.
         double err3 = (0.289 * 0.289) * (invampl[j] * invampl[j]);
 
         double totalError = std::sqrt(err1 + err2 + err3);
 
         // don't include useless ratios
         if (totalError < 1.0 && Rtmp > 0.001 && Rtmp < Rlim[j - i]) {
           Ratio currentRatio = { i, (j - i), Rtmp, totalError };
           ratios_[ratios_size++] = currentRatio;
         }
       }
     }
   }
 
   // No useful ratios, return zero amplitude and no time measurement
   if (0 == ratios_size) return;
 
   //  std::array < Tmax, C::MAXSAMPLES*(C::MAXSAMPLES-1)/2 > times_;
   Tmax timesAB_[C::MAXSAMPLES * (C::MAXSAMPLES - 1) / 2];
   unsigned int timesAB_size = 0;
 
   // make a vector of Tmax measurements that correspond to each ratio
   // and based on Alpha-Beta parameterization of the pulse shape
 
   for (unsigned int i = 0; i < ratios_size; i++) {
 
     double stepOverBeta = double(ratios_[i].step) / beta;
     double offset = double(ratios_[i].index) + alphabeta;
 
     double Rmin = ratios_[i].value - ratios_[i].error;
     if (Rmin < 0.001) Rmin = 0.001;
 
     double Rmax = ratios_[i].value + ratios_[i].error;
     double RLimit = Rlim[ratios_[i].step];
     if (Rmax > RLimit) Rmax = RLimit;
 
     double time1 =
         offset -
         ratios_[i].step /
             (myMath::fast_expf((stepOverBeta - myMath::fast_logf(Rmin)) /
                                alpha) - 1.0);
     double time2 =
         offset -
         ratios_[i].step /
             (myMath::fast_expf((stepOverBeta - myMath::fast_logf(Rmax)) /
                                alpha) - 1.0);
 
     // this is the time measurement based on the ratios[i]
     double tmax = 0.5 * (time1 + time2);
     double tmaxerr = 0.5 * std::sqrt((time1 - time2) * (time1 - time2));
 
     // calculate chi2
     sumAf = 0;
     sumff = 0;
     int itmin = std::max(-1, int(std::floor(tmax - alphabeta)));
     double loffset = (double(itmin) - tmax) * invalphabeta;
     for (unsigned int it = itmin + 1; it < amplitudes_.size(); it++) {
       loffset += invalphabeta;
       if (useless_[it]) continue;
       double inverr2 = amplitudeIE2_[it];
       //      double offset = (double(it) - tmax)/alphabeta;
       double term1 = 1.0 + loffset;
       // assert(term1>1e-6);
       double f =
           (term1 > 1e-6)
               ? myMath::fast_expf(alpha * (myMath::fast_logf(term1) - loffset))
               : 0;
       sumAf += amplitudes_[it] * (f * inverr2);
       sumff += f * (f * inverr2);
     }
 
     double chi2 = sumAA;
     double amp = 0;
     if (sumff > 0) {
       chi2 = sumAA - sumAf * (sumAf / sumff);
       amp = (sumAf / sumff);
     }
     chi2 /= sum0;
 
     // choose reasonable measurements. One might argue what is
     // reasonable and what is not.
     if (chi2 > 0 && tmaxerr > 0 && tmax > 0) {
       Tmax currentTmax = { ratios_[i].index, ratios_[i].step, tmax, tmaxerr,
                            amp, chi2 };
       timesAB_[timesAB_size++] = currentTmax;
     }
   }
 
   // no reasonable time measurements!
   if (0 == timesAB_size) return;
 
   // find minimum chi2
   double chi2min = 1.0e+9;
   //double timeMinimum = 5;
   //double errorMinimum = 999;
   for (unsigned int i = 0; i < timesAB_size; i++) {
     if (timesAB_[i].chi2 < chi2min) {
       chi2min = timesAB_[i].chi2;
       //timeMinimum = timesAB_[i].value;
       //errorMinimum = timesAB_[i].error;
     }
   }
 
   // make a weighted average of tmax measurements with "small" chi2
   // (within 1 sigma of statistical uncertainty :-)
   double chi2Limit = chi2min + 1.0;
   double time_max = 0;
   double time_wgt = 0;
   for (unsigned int i = 0; i < timesAB_size; i++) {
     if (timesAB_[i].chi2 < chi2Limit) {
       double inverseSigmaSquared =
           1.0 / (timesAB_[i].error * timesAB_[i].error);
       time_wgt += inverseSigmaSquared;
       time_max += timesAB_[i].value * inverseSigmaSquared;
     }
   }
 
   tMaxAlphaBeta = time_max / time_wgt;
   tMaxErrorAlphaBeta = 1.0 / sqrt(time_wgt);
 
   // find amplitude and chi2
   sumAf = 0;
   sumff = 0;
   for (unsigned int i = 0; i < amplitudes_.size(); i++) {
     if (useless_[i]) continue;
     double inverr2 = amplitudeIE2_[i];
     double offset = (double(i) - tMaxAlphaBeta) * invalphabeta;
     double term1 = 1.0 + offset;
     if (term1 > 1e-6) {
       double f = myMath::fast_expf(alpha * (myMath::fast_logf(term1) - offset));
       sumAf += amplitudes_[i] * (f * inverr2);
       sumff += f * (f * inverr2);
     }
   }
 
   if (sumff > 0) {
     ampMaxAlphaBeta = sumAf / sumff;
     double chi2AlphaBeta = (sumAA - sumAf * sumAf / sumff) / sum0;
     if (chi2AlphaBeta > NullChi2) {
       // null hypothesis is better
       return;
     }
 
   } else {
     // no visible pulse here
     return;
   }
 
   // if we got to this point, we have a reconstructied Tmax
   // using RatioAlphaBeta Method. To summarize:
   //
   //     tMaxAlphaBeta      - Tmax value
   //     tMaxErrorAlphaBeta - error on Tmax, but I would not trust it
   //     ampMaxAlphaBeta    - amplitude of the pulse
   //     ampMaxError_        - uncertainty of the time sample with max amplitude
   //
 
   // Do Ratio's Method with "large" pulses
   if (ampMaxAlphaBeta / ampMaxError_ > 5.0) {
 
     // make a vector of Tmax measurements that correspond to each
     // ratio. Each measurement have it's value and the error
 
     double time_max = 0;
     double time_wgt = 0;
 
     for (unsigned int i = 0; i < ratios_size; i++) {
 
       if (ratios_[i].step == 1 && ratios_[i].value >= timeFitLimits.first &&
           ratios_[i].value <= timeFitLimits.second) {
 
         double time_max_i = ratios_[i].index;
 
         // calculate polynomial for Tmax
 
         double u = timeFitParameters[timeFitParameters.size() - 1];
         for (int k = timeFitParameters.size() - 2; k >= 0; k--) {
           u = u * ratios_[i].value + timeFitParameters[k];
         }
 
         // calculate derivative for Tmax error
         double du = (timeFitParameters.size() - 1) *
                     timeFitParameters[timeFitParameters.size() - 1];
         for (int k = timeFitParameters.size() - 2; k >= 1; k--) {
           du = du * ratios_[i].value + k * timeFitParameters[k];
         }
 
         // running sums for weighted average
         double errorsquared = ratios_[i].error * ratios_[i].error * du * du;
         if (errorsquared > 0) {
 
           time_max += (time_max_i - u) / errorsquared;
           time_wgt += 1.0 / errorsquared;
           //            Tmax currentTmax =
           //  { ratios_[i].index, 1, (time_max_i - u),
           //sqrt(errorsquared),0,1 };
           // times_.push_back(currentTmax);
 
         }
       }
     }
 
     // calculate weighted average of all Tmax measurements
     if (time_wgt > 0) {
       tMaxRatio = time_max / time_wgt;
       tMaxErrorRatio = 1.0 / sqrt(time_wgt);
 
       // combine RatioAlphaBeta and Ratio Methods
 
       if (ampMaxAlphaBeta / ampMaxError_ > 10.0) {
 
         // use pure Ratio Method
         calculatedRechit_.timeMax = tMaxRatio;
         calculatedRechit_.timeError = tMaxErrorRatio;
 
       } else {
 
         // combine two methods
         calculatedRechit_.timeMax =
             (tMaxAlphaBeta * (10.0 - ampMaxAlphaBeta / ampMaxError_) +
              tMaxRatio * (ampMaxAlphaBeta / ampMaxError_ - 5.0)) / 5.0;
         calculatedRechit_.timeError =
             (tMaxErrorAlphaBeta * (10.0 - ampMaxAlphaBeta / ampMaxError_) +
              tMaxErrorRatio * (ampMaxAlphaBeta / ampMaxError_ - 5.0)) / 5.0;
 
       }
 
     } else {
 
       // use RatioAlphaBeta Method
       calculatedRechit_.timeMax = tMaxAlphaBeta;
       calculatedRechit_.timeError = tMaxErrorAlphaBeta;
 
     }
 
   } else {
 
     // use RatioAlphaBeta Method
     calculatedRechit_.timeMax = tMaxAlphaBeta;
     calculatedRechit_.timeError = tMaxErrorAlphaBeta;
 
   }
 }

template<class C>

bool EcalUncalibRecHitRatioMethodAlgo< C >::fixMGPAslew ( const C & dataFrame )

Definition at line 189 of file EcalUncalibRecHitRatioMethodAlgo.h.

References alignCSCRings::e, and query::result.

Referenced by EcalUncalibRecHitWorkerRatio::run(), and EcalUncalibRecHitWorkerGlobal::run().

                                                                         {
 
   // This fuction finds sample(s) preceeding gain switching and
   // inflates errors on this sample, therefore, making this sample
   // invisible for Ratio Method. Only gain switching DOWN is
   // considered Only gainID=1,2,3 are considered. In case of the
   // saturation (gainID=0), we keep "distorted" sample because it is
   // the only chance to make time measurement; the qualilty of it will
   // be bad anyway.
 
   bool result = false;
 
   int GainIdPrev;
   int GainIdNext;
   for (int iSample = 1; iSample < C::MAXSAMPLES; iSample++) {
 
     // only use samples which are desired
     if (!sampleMask_.useSample(iSample, theDetId_)) continue;
 
     GainIdPrev = dataFrame.sample(iSample - 1).gainId();
     GainIdNext = dataFrame.sample(iSample).gainId();
     if (GainIdPrev >= 1 && GainIdPrev <= 3 && GainIdNext >= 1 &&
         GainIdNext <= 3 && GainIdPrev < GainIdNext) {
       amplitudes_[iSample - 1] = 0;
       amplitudeErrors_[iSample - 1] = 1e+9;
       amplitudeIE2_[iSample - 1] = 0;
       useless_[iSample - 1] = true;
       result = true;
     }
   }
   return result;
 
 }

template<class C>

CalculatedRecHit EcalUncalibRecHitRatioMethodAlgo< C >::getCalculatedRecHit ( )

inline

Definition at line 72 of file EcalUncalibRecHitRatioMethodAlgo.h.

Referenced by EcalUncalibRecHitWorkerRatio::run(), and EcalUncalibRecHitWorkerGlobal::run().

72 { return calculatedRechit_; }

EcalUncalibRecHitRatioMethodAlgo::calculatedRechit_

CalculatedRecHit calculatedRechit_

Definition: EcalUncalibRecHitRatioMethodAlgo.h:91

template<class C>

void EcalUncalibRecHitRatioMethodAlgo< C >::init	(	const C &	dataFrame,
		const EcalSampleMask &	sampleMask,
		const double *	pedestals,
		const double *	pedestalRMSes,
		const double *	gainRatios
	)

Definition at line 95 of file EcalUncalibRecHitRatioMethodAlgo.h.

References cond::ecalcond::bad(), alignCSCRings::e, and compare_using_db::sample.

Referenced by EcalUncalibRecHitWorkerGlobal::run().

                                                                          {
   sampleMask_ = sampleMask;
   theDetId_ = DetId(dataFrame.id().rawId());
 
   calculatedRechit_.timeMax = 5;
   calculatedRechit_.amplitudeMax = 0;
   calculatedRechit_.timeError = -999;
 
   // to obtain gain 12 pedestal:
   // -> if it's in gain 12, use first sample
   // --> average it with second sample if in gain 12 and 3-sigma-noise
   // compatible (better LF noise cancellation)
   // -> else use pedestal from database
   pedestal_ = 0;
   num_ = 0;
   if (dataFrame.sample(0).gainId() == 1 &&
       sampleMask_.useSample(0, theDetId_)) {
     pedestal_ += double(dataFrame.sample(0).adc());
     num_++;
   }
   if (num_ != 0 && dataFrame.sample(1).gainId() == 1 &&
       sampleMask_.useSample(1, theDetId_) &&
       fabs(dataFrame.sample(1).adc() - dataFrame.sample(0).adc()) <
           3 * pedestalRMSes[0]) {
     pedestal_ += double(dataFrame.sample(1).adc());
     num_++;
   }
   if (num_ != 0)
     pedestal_ /= num_;
   else
     pedestal_ = pedestals[0];
 
   // fill vector of amplitudes, pedestal subtracted and vector
   // of amplitude uncertainties Also, find the uncertainty of a
   // sample with max amplitude. We will use it later.
 
   ampMaxError_ = 0;
   double ampMaxValue = -1000;
 
   // ped-subtracted and gain-renormalized samples. It is VERY
   // IMPORTANT to have samples one clock apart which means to
   // have vector size equal to MAXSAMPLES
   double sample;
   double sampleError;
   int GainId;
   for (int iSample = 0; iSample < C::MAXSAMPLES; iSample++) {
 
     GainId = dataFrame.sample(iSample).gainId();
 
     bool bad = false;
     // only use normally samples which are desired; if sample not to be used
     // inflate error so won't generate ratio considered for the measurement
     if (!sampleMask_.useSample(iSample, theDetId_)) {
       sample = 0;
       sampleError = 0;
       bad = true;
     } else if (GainId == 1) {
       sample = double(dataFrame.sample(iSample).adc() - pedestal_);
       sampleError = pedestalRMSes[0];
     } else if (GainId == 2 || GainId == 3) {
       sample =
           (double(dataFrame.sample(iSample).adc() - pedestals[GainId - 1])) *
           gainRatios[GainId - 1];
       sampleError = pedestalRMSes[GainId - 1] * gainRatios[GainId - 1];
     } else {
       sample = 0;  // GainId=0 case falls here, from saturation
       sampleError = 0;  // inflate error so won't generate ratio considered for
                         // the measurement
       bad = true;
     }
 
     useless_[iSample] = (sampleError <= 0) | bad;
     amplitudes_[iSample] = sample;
     // inflate error for useless samples
     amplitudeErrors_[iSample] = useless_[iSample] ? 1e+9 : sampleError;
     amplitudeIE2_[iSample] =
         useless_[iSample]
             ? 0
             : 1 / (amplitudeErrors_[iSample] * amplitudeErrors_[iSample]);
     if (sampleError > 0) {
       if (ampMaxValue < sample) {
         ampMaxValue = sample;
         ampMaxError_ = sampleError;
       }
     }
 
   }
 
 }

template<class C>

EcalUncalibratedRecHit EcalUncalibRecHitRatioMethodAlgo< C >::makeRecHit	(	const C &	dataFrame,
		const EcalSampleMask &	sampleMask,
		const double *	pedestals,
		const double *	pedestalRMSes,
		const double *	gainRatios,
		std::vector< double > &	timeFitParameters,
		std::vector< double > &	amplitudeFitParameters,
		std::pair< double, double > &	timeFitLimits
	)

Definition at line 621 of file EcalUncalibRecHitRatioMethodAlgo.h.

References init.

Referenced by EcalUncalibRecHitWorkerRatio::run().

                                             {
 
   init(dataFrame, sampleMask, pedestals, pedestalRMSes, gainRatios);
   computeTime(timeFitParameters, timeFitLimits, amplitudeFitParameters);
   computeAmplitude(amplitudeFitParameters);
 
   // 1st parameters is id
   //
   // 2nd parameters is amplitude. It is calculated by this method.
   //
   // 3rd parameter is pedestal. It is not calculated. This method
   // relies on input parameters for pedestals and gain ratio. Return
   // zero.
   //
   // 4th parameter is jitter which is a bad choice to call Tmax. It is
   // calculated by this method (in 25 nsec clock units)
   //
   // GF subtract 5 so that jitter==0 corresponds to synchronous hit
   //
   //
   // 5th parameter is chi2. It is possible to calculate chi2 for
   // Tmax. It is possible to calculate chi2 for Amax. However, these
   // values are not very useful without TmaxErr and AmaxErr. This
   // method can return one value for chi2 but there are 4 different
   // parameters that have useful information about the quality of Amax
   // ans Tmax. For now we can return TmaxErr. The quality of Tmax and
   // Amax can be judged from the magnitude of TmaxErr
 
   return EcalUncalibratedRecHit(dataFrame.id(), calculatedRechit_.amplitudeMax,
                                 pedestal_, calculatedRechit_.timeMax - 5,
                                 calculatedRechit_.timeError);
 }