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Optional use of Max-Sample algorithm for gain-switch cases #17279

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merged 2 commits into from Jan 30, 2017
Merged

Optional use of Max-Sample algorithm for gain-switch cases #17279

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ffc4d7d
Merged refs/pull/17205/head from repository cms-sw
emanueledimarco Jan 24, 2017
455267f
optional use of max-sample algo for gain-switch hits
emanueledimarco Jan 25, 2017
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2 changes: 2 additions & 0 deletions RecoLocalCalo/EcalRecAlgos/interface/EcalUncalibRecHitMultiFitAlgo.h
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Expand Up @@ -34,6 +34,7 @@ class EcalUncalibRecHitMultiFitAlgo
void setSelectiveBadSampleCriteria(bool b) { _selectiveBadSampleCriteria = b; }
void setAddPedestalUncertainty(double x) { _addPedestalUncertainty = x; }
void setSimplifiedNoiseModelForGainSwitch(bool b) { _simplifiedNoiseModelForGainSwitch = b; }
void setGainSwitchUseMaxSample(bool b) { _gainSwitchUseMaxSample = b; }

private:
PulseChiSqSNNLS _pulsefunc;
Expand All @@ -46,6 +47,7 @@ class EcalUncalibRecHitMultiFitAlgo
bool _selectiveBadSampleCriteria;
double _addPedestalUncertainty;
bool _simplifiedNoiseModelForGainSwitch;
bool _gainSwitchUseMaxSample;
BXVector _singlebx;

};
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26 changes: 20 additions & 6 deletions RecoLocalCalo/EcalRecAlgos/src/EcalUncalibRecHitMultiFitAlgo.cc
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Expand Up @@ -13,7 +13,8 @@ EcalUncalibRecHitMultiFitAlgo::EcalUncalibRecHitMultiFitAlgo() :
_mitigateBadSamples(false),
_selectiveBadSampleCriteria(false),
_addPedestalUncertainty(0.),
_simplifiedNoiseModelForGainSwitch(true) {
_simplifiedNoiseModelForGainSwitch(true),
_gainSwitchUseMaxSample(false){

_singlebx.resize(1);
_singlebx << 0;
Expand Down Expand Up @@ -105,20 +106,33 @@ EcalUncalibratedRecHit EcalUncalibRecHitMultiFitAlgo::makeRecHit(const EcalDataF
}

}


double amplitude, amperr, chisq;
bool status = false;

//special handling for gain switch, where sample before maximum is potentially affected by slew rate limitation
//optionally apply a stricter criteria, assuming slew rate limit is only reached in case where maximum sample has gain switched but previous sample has not
//A floating negative single-sample offset is added to the fit
//option 1: use simple max-sample algorithm
if (hasGainSwitch && _gainSwitchUseMaxSample) {
EcalUncalibratedRecHit rh( dataFrame.id(), maxamplitude, pedval, 0., 0., flags );
rh.setAmplitudeError(0.);
for (unsigned int ipulse=0; ipulse<_pulsefunc.BXs().rows(); ++ipulse) {
int bx = _pulsefunc.BXs().coeff(ipulse);
if (bx!=0) {
rh.setOutOfTimeAmplitude(bx+5, 0.0);
}
}
return rh;
}

//option2: A floating negative single-sample offset is added to the fit
//such that the affected sample is treated only as a lower limit for the true amplitude
bool mitigateBadSample = _mitigateBadSamples && hasGainSwitch && iSampleMax>0;
mitigateBadSample &= (!_selectiveBadSampleCriteria || (gainsNoise.coeff(iSampleMax-1)!=gainsNoise.coeff(iSampleMax)) );
if (mitigateBadSample) {
badSamples[iSampleMax-1] = 1;
}

double amplitude, amperr, chisq;
bool status = false;

//compute noise covariance matrix, which depends on the sample gains
SampleMatrix noisecov;
if (hasGainSwitch) {
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8 changes: 7 additions & 1 deletion RecoLocalCalo/EcalRecProducers/plugins/EcalUncalibRecHitWorkerMultiFit.cc
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Expand Up @@ -54,6 +54,8 @@ EcalUncalibRecHitWorkerMultiFit::EcalUncalibRecHitWorkerMultiFit(const edm::Para
dynamicPedestalsEE_ = ps.getParameter<bool>("dynamicPedestalsEE");
mitigateBadSamplesEB_ = ps.getParameter<bool>("mitigateBadSamplesEB");
mitigateBadSamplesEE_ = ps.getParameter<bool>("mitigateBadSamplesEE");
gainSwitchUseMaxSampleEB_ = ps.getParameter<bool>("gainSwitchUseMaxSampleEB");
gainSwitchUseMaxSampleEE_ = ps.getParameter<bool>("gainSwitchUseMaxSampleEE");
selectiveBadSampleCriteriaEB_ = ps.getParameter<bool>("selectiveBadSampleCriteriaEB");
selectiveBadSampleCriteriaEE_ = ps.getParameter<bool>("selectiveBadSampleCriteriaEE");
addPedestalUncertaintyEB_ = ps.getParameter<double>("addPedestalUncertaintyEB");
Expand Down Expand Up @@ -281,6 +283,7 @@ EcalUncalibRecHitWorkerMultiFit::run( const edm::Event & evt,
multiFitMethod_.setPrefitMaxChiSq(prefitMaxChiSqEE_);
multiFitMethod_.setDynamicPedestals(dynamicPedestalsEE_);
multiFitMethod_.setMitigateBadSamples(mitigateBadSamplesEE_);
multiFitMethod_.setGainSwitchUseMaxSample(gainSwitchUseMaxSampleEE_);
multiFitMethod_.setSelectiveBadSampleCriteria(selectiveBadSampleCriteriaEE_);
multiFitMethod_.setAddPedestalUncertainty(addPedestalUncertaintyEE_);
offsetTime = offtime->getEEValue();
Expand All @@ -293,11 +296,12 @@ EcalUncalibRecHitWorkerMultiFit::run( const edm::Event & evt,
aPulseCov = &pulsecovariances->barrel(hashedIndex);
multiFitMethod_.setDoPrefit(doPrefitEB_);
multiFitMethod_.setPrefitMaxChiSq(prefitMaxChiSqEB_);
offsetTime = offtime->getEBValue();
multiFitMethod_.setDynamicPedestals(dynamicPedestalsEB_);
multiFitMethod_.setMitigateBadSamples(mitigateBadSamplesEB_);
multiFitMethod_.setGainSwitchUseMaxSample(gainSwitchUseMaxSampleEB_);
multiFitMethod_.setSelectiveBadSampleCriteria(selectiveBadSampleCriteriaEB_);
multiFitMethod_.setAddPedestalUncertainty(addPedestalUncertaintyEB_);
offsetTime = offtime->getEBValue();
}

double pedVec[3] = { aped->mean_x12, aped->mean_x6, aped->mean_x1 };
Expand Down Expand Up @@ -598,6 +602,8 @@ EcalUncalibRecHitWorkerMultiFit::getAlgoDescription() {
edm::ParameterDescription<bool>("dynamicPedestalsEE", false, true) and
edm::ParameterDescription<bool>("mitigateBadSamplesEB", false, true) and
edm::ParameterDescription<bool>("mitigateBadSamplesEE", false, true) and
edm::ParameterDescription<bool>("gainSwitchUseMaxSampleEB", false, true) and
edm::ParameterDescription<bool>("gainSwitchUseMaxSampleEE", false, true) and
edm::ParameterDescription<bool>("selectiveBadSampleCriteriaEB", false, true) and
edm::ParameterDescription<bool>("selectiveBadSampleCriteriaEE", false, true) and
edm::ParameterDescription<double>("addPedestalUncertaintyEB", 0., true) and
Expand Down
2 changes: 2 additions & 0 deletions RecoLocalCalo/EcalRecProducers/plugins/EcalUncalibRecHitWorkerMultiFit.h
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Expand Up @@ -94,6 +94,8 @@ class EcalUncalibRecHitWorkerMultiFit final : public EcalUncalibRecHitWorkerBase
bool dynamicPedestalsEE_;
bool mitigateBadSamplesEB_;
bool mitigateBadSamplesEE_;
bool gainSwitchUseMaxSampleEB_;
bool gainSwitchUseMaxSampleEE_;
bool selectiveBadSampleCriteriaEB_;
bool selectiveBadSampleCriteriaEE_;
double addPedestalUncertaintyEB_;
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2 changes: 2 additions & 0 deletions RecoLocalCalo/EcalRecProducers/python/ecalMultiFitUncalibRecHit_cfi.py
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Expand Up @@ -24,6 +24,8 @@
dynamicPedestalsEE = cms.bool(False),
mitigateBadSamplesEB = cms.bool(False),
mitigateBadSamplesEE = cms.bool(False),
gainSwitchUseMaxSampleEB = cms.bool(False),
gainSwitchUseMaxSampleEE = cms.bool(False),
selectiveBadSampleCriteriaEB = cms.bool(False),
selectiveBadSampleCriteriaEE = cms.bool(False),
simplifiedNoiseModelForGainSwitch = cms.bool(True),
Expand Down