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#include <PedsFullNoiseSummaryFactory.h>
Protected Member Functions | |
| void | extract (Iterator) |
| void | format () |
Definition at line 6 of file PedsFullNoiseSummaryFactory.h.
| void PedsFullNoiseSummaryFactory::extract | ( | Iterator | iter | ) | [protected, virtual] |
Reimplemented from SummaryPlotFactory< CommissioningAnalysis * >.
Definition at line 12 of file PedsFullNoiseSummaryFactory.cc.
References PedsFullNoiseAnalysis::chi2Prob(), PedsFullNoiseAnalysis::dead(), SummaryGenerator::fillMap(), SummaryPlotFactoryBase::generator_, SummaryPlotFactoryBase::gran_, sistrip::invalid_, PedsFullNoiseAnalysis::ksProb(), SummaryPlotFactoryBase::level_, sistrip::mlSummaryPlots_, SummaryPlotFactoryBase::mon_, SiStripEnumsAndStrings::monitorable(), PedsFullNoiseAnalysis::noise(), sistrip::NOISE_ALL_STRIPS, sistrip::NOISE_BIN_84_ALL_STRIPS, sistrip::NOISE_CHI2_ALL_STRIPS, sistrip::NOISE_GAUS_ALL_STRIPS, sistrip::NOISE_KS_ALL_STRIPS, sistrip::NOISE_MAX, sistrip::NOISE_MEAN, sistrip::NOISE_MIN, sistrip::NOISE_RMS_ALL_STRIPS, sistrip::NOISE_SIGNIF_ALL_STRIPS, sistrip::NOISE_SPREAD, PedsFullNoiseAnalysis::noiseBin84(), PedsFullNoiseAnalysis::noiseGaus(), PedsFullNoiseAnalysis::noiseMax(), PedsFullNoiseAnalysis::noiseMean(), PedsFullNoiseAnalysis::noiseMin(), PedsFullNoiseAnalysis::noiseRMS(), PedsFullNoiseAnalysis::noiseSignif(), PedsFullNoiseAnalysis::noiseSpread(), PedsFullNoiseAnalysis::noisy(), sistrip::NUM_OF_DEAD, sistrip::NUM_OF_NOISY, sistrip::PEDESTALS_ALL_STRIPS, sistrip::PEDESTALS_MAX, sistrip::PEDESTALS_MEAN, sistrip::PEDESTALS_MIN, sistrip::PEDESTALS_SPREAD, PedsFullNoiseAnalysis::peds(), PedsFullNoiseAnalysis::pedsMax(), PedsFullNoiseAnalysis::pedsMean(), PedsFullNoiseAnalysis::pedsMin(), PedsFullNoiseAnalysis::pedsSpread(), plotscripts::rms(), findQualityFiles::size, groupFilesInBlocks::temp, and relativeConstraints::value.
{
PedsFullNoiseAnalysis* anal = dynamic_cast<PedsFullNoiseAnalysis*>( iter->second );
if ( !anal ) { return; }
std::vector< float > temp(128, 1. * sistrip::invalid_ );
std::vector< std::vector<float> > value( 2, temp );
std::vector< std::vector<float> > peds( 2, temp );
std::vector< std::vector<float> > noise( 2, temp );
std::vector< std::vector<float> > ks( 2, temp );
std::vector< std::vector<float> > noiseG( 2, temp );
std::vector< std::vector<float> > bin84( 2, temp );
std::vector< std::vector<float> > chi2( 2, temp );
std::vector< std::vector<float> > signif( 2, temp );
std::vector< std::vector<float> > rms( 2, temp );
peds[0] = anal->peds()[0];
peds[1] = anal->peds()[1];
noise[0] = anal->noise()[0];
noise[1] = anal->noise()[1];
ks[0] = anal->ksProb()[0]; // dummy values //replaced with ksProb now, wing
ks[1] = anal->ksProb()[1]; // dummy values
noiseG[0] = anal->noiseGaus()[0];
noiseG[1] = anal->noiseGaus()[1];
bin84[0] = anal->noiseBin84()[0];
bin84[1] = anal->noiseBin84()[1];
rms[0] = anal->noiseRMS()[0];
rms[1] = anal->noiseRMS()[1];
chi2[0] = anal->chi2Prob()[0];
chi2[1] = anal->chi2Prob()[1];
signif[0] = anal->noiseSignif()[0];
signif[1] = anal->noiseSignif()[1];
bool all_strips = false;
if ( mon_ == sistrip::PEDESTALS_ALL_STRIPS ) {
all_strips = true;
uint16_t bins = peds[0].size();
if ( peds[0].size() < peds[1].size() ) { bins = peds[1].size(); }
for ( uint16_t iped = 0; iped < bins; iped++ ) {
value[0][iped] = peds[0][iped];
value[1][iped] = peds[1][iped];
}
} else if ( mon_ == sistrip::PEDESTALS_MEAN ) {
value[0][0] = anal->pedsMean()[0];
value[1][0] = anal->pedsMean()[1];
} else if ( mon_ == sistrip::PEDESTALS_SPREAD ) {
value[0][0] = anal->pedsSpread()[0];
value[1][0] = anal->pedsSpread()[1];
} else if ( mon_ == sistrip::PEDESTALS_MAX ) {
value[0][0] = anal->pedsMax()[0];
value[1][0] = anal->pedsMax()[1];
} else if ( mon_ == sistrip::PEDESTALS_MIN ) {
value[0][0] = anal->pedsMin()[0];
value[1][0] = anal->pedsMin()[1];
} else if ( mon_ == sistrip::NOISE_ALL_STRIPS ) {
all_strips = true;
uint16_t bins = noise[0].size();
if ( noise[0].size() < noise[1].size() ) { bins = noise[1].size(); }
for ( uint16_t inoise = 0; inoise < bins; inoise++ ) {
value[0][inoise] = noise[0][inoise];
value[1][inoise] = noise[1][inoise];
}
} else if ( mon_ == sistrip::NOISE_KS_ALL_STRIPS ) {
all_strips = true;
uint16_t bins = ks[0].size();
if ( ks[0].size() < ks[1].size() ) { bins = ks[1].size(); }
for ( uint16_t iks = 0; iks < bins; iks++ ) {
value[0][iks] = ks[0][iks];
value[1][iks] = ks[1][iks];
}
} else if ( mon_ == sistrip::NOISE_CHI2_ALL_STRIPS ) {
all_strips = true;
uint16_t bins = chi2[0].size();
if ( ks[0].size() < chi2[1].size() ) { bins = chi2[1].size(); }
for ( uint16_t iks = 0; iks < bins; iks++ ) {
value[0][iks] = chi2[0][iks];
value[1][iks] = chi2[1][iks];
}
} else if ( mon_ == sistrip::NOISE_GAUS_ALL_STRIPS ) {
all_strips = true;
uint16_t bins = noiseG[0].size();
if ( noiseG[0].size() < noiseG[1].size() ) { bins = noiseG[1].size(); }
for ( uint16_t iks = 0; iks < bins; iks++ ) {
value[0][iks] = noiseG[0][iks];
value[1][iks] = noiseG[1][iks];
}
} else if ( mon_ == sistrip::NOISE_BIN_84_ALL_STRIPS ) {
all_strips = true;
uint16_t bins = bin84[0].size();
if ( bin84[0].size() < bin84[1].size() ) { bins = bin84[1].size(); }
for ( uint16_t iks = 0; iks < bins; iks++ ) {
value[0][iks] = bin84[0][iks];
value[1][iks] = bin84[1][iks];
}
} else if ( mon_ == sistrip::NOISE_RMS_ALL_STRIPS ) {
all_strips = true;
uint16_t bins = rms[0].size();
if ( rms[0].size() < rms[1].size() ) { bins = rms[1].size(); }
for ( uint16_t iks = 0; iks < bins; iks++ ) {
value[0][iks] = rms[0][iks];
value[1][iks] = rms[1][iks];
}
} else if ( mon_ == sistrip::NOISE_SIGNIF_ALL_STRIPS ) {
all_strips = true;
uint16_t bins = signif[0].size();
if ( signif[0].size() < signif[1].size() ) { bins = signif[1].size(); }
for ( uint16_t iks = 0; iks < bins; iks++ ) {
value[0][iks] = signif[0][iks];
value[1][iks] = signif[1][iks];
}
} else if ( mon_ == sistrip::NOISE_MEAN ) {
value[0][0] = anal->noiseMean()[0];
value[1][0] = anal->noiseMean()[1];
} else if ( mon_ == sistrip::NOISE_SPREAD ) {
value[0][0] = anal->noiseSpread()[0];
value[1][0] = anal->noiseSpread()[1];
} else if ( mon_ == sistrip::NOISE_MAX ) {
value[0][0] = anal->noiseMax()[0];
value[1][0] = anal->noiseMax()[1];
} else if ( mon_ == sistrip::NOISE_MIN ) {
value[0][0] = anal->noiseMin()[0];
value[1][0] = anal->noiseMin()[1];
} else if ( mon_ == sistrip::NUM_OF_DEAD ) {
value[0][0] = 1. * anal->dead()[0].size();
value[1][0] = 1. * anal->dead()[1].size();
} else if ( mon_ == sistrip::NUM_OF_NOISY ) {
value[0][0] = 1. * anal->noisy()[0].size();
value[1][0] = 1. * anal->noisy()[1].size();
} else {
edm::LogWarning(mlSummaryPlots_)
<< "[SummaryPlotFactory::" << __func__ << "]"
<< " Unexpected monitorable: "
<< SiStripEnumsAndStrings::monitorable( SummaryPlotFactoryBase::mon_ );
return;
}
if ( !all_strips ) {
SummaryPlotFactoryBase::generator_->fillMap( SummaryPlotFactoryBase::level_,
SummaryPlotFactoryBase::gran_,
iter->first,
value[0][0] );
SummaryPlotFactoryBase::generator_->fillMap( SummaryPlotFactoryBase::level_,
SummaryPlotFactoryBase::gran_,
iter->first,
value[1][0] );
}
else {
for ( uint16_t istr = 0; istr < value[0].size(); istr++ ) {
SummaryPlotFactoryBase::generator_->fillMap( SummaryPlotFactoryBase::level_,
SummaryPlotFactoryBase::gran_,
iter->first,
value[0][istr] );
}
for ( uint16_t istr = 0; istr < value[1].size(); istr++ ) {
SummaryPlotFactoryBase::generator_->fillMap( SummaryPlotFactoryBase::level_,
SummaryPlotFactoryBase::gran_,
iter->first,
value[1][istr] );
}
}
}
| void PedsFullNoiseSummaryFactory::format | ( | ) | [protected, virtual] |
Reimplemented from SummaryPlotFactory< CommissioningAnalysis * >.
Definition at line 179 of file PedsFullNoiseSummaryFactory.cc.
References sistrip::mlSummaryPlots_, SummaryPlotFactoryBase::mon_, SiStripEnumsAndStrings::monitorable(), sistrip::NOISE_ALL_STRIPS, sistrip::NOISE_BIN_84_ALL_STRIPS, sistrip::NOISE_CHI2_ALL_STRIPS, sistrip::NOISE_GAUS_ALL_STRIPS, sistrip::NOISE_KS_ALL_STRIPS, sistrip::NOISE_MAX, sistrip::NOISE_MEAN, sistrip::NOISE_MIN, sistrip::NOISE_RMS_ALL_STRIPS, sistrip::NOISE_SPREAD, sistrip::NUM_OF_DEAD, sistrip::NUM_OF_NOISY, sistrip::PEDESTALS_ALL_STRIPS, sistrip::PEDESTALS_MAX, sistrip::PEDESTALS_MEAN, sistrip::PEDESTALS_MIN, and sistrip::PEDESTALS_SPREAD.
{
if ( mon_ == sistrip::PEDESTALS_ALL_STRIPS ) {
generator_->axisLabel( "Pedestal value [adc]" );
} else if ( mon_ == sistrip::PEDESTALS_MEAN ) {
} else if ( mon_ == sistrip::PEDESTALS_SPREAD ) {
} else if ( mon_ == sistrip::PEDESTALS_MAX ) {
} else if ( mon_ == sistrip::PEDESTALS_MIN ) {
} else if ( mon_ == sistrip::NOISE_ALL_STRIPS ) {
generator_->axisLabel( "Noise [adc]" );
} else if ( mon_ == sistrip::NOISE_MEAN ) {
} else if ( mon_ == sistrip::NOISE_SPREAD ) {
} else if ( mon_ == sistrip::NOISE_MAX ) {
} else if ( mon_ == sistrip::NOISE_MIN ) {
} else if ( mon_ == sistrip::NUM_OF_DEAD ) {
} else if ( mon_ == sistrip::NUM_OF_NOISY ) {
} else if ( mon_ == sistrip::NOISE_KS_ALL_STRIPS ) {
generator_->axisLabel( "KS Prob." );
} else if ( mon_ == sistrip::NOISE_GAUS_ALL_STRIPS ) {
generator_->axisLabel( "Noise Gaus." );
} else if ( mon_ == sistrip::NOISE_BIN_84_ALL_STRIPS ) {
generator_->axisLabel( "Noise Bin 84." );
} else if ( mon_ == sistrip::NOISE_RMS_ALL_STRIPS ) {
generator_->axisLabel( "Noise RMS." );
} else if ( mon_ == sistrip::NOISE_CHI2_ALL_STRIPS ) {
generator_->axisLabel( "Chi2 Prob." );
} else {
edm::LogWarning(mlSummaryPlots_)
<< "[SummaryPlotFactory::" << __func__ << "]"
<< " Unexpected SummaryHisto value:"
<< SiStripEnumsAndStrings::monitorable( SummaryPlotFactoryBase::mon_ );
}
}
1.7.3