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SBSGEMModule.cxx
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SBSGEMModule.cxx
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#include <iostream>
#include "SBSGEMModule.h"
#include "TDatime.h"
#include "THaEvData.h"
#include "THaApparatus.h"
#include "THaRun.h"
#include "TRotation.h"
#include "TH1D.h"
#include "TH2D.h"
#include "TF1.h"
#include "TGraphErrors.h"
#include "TClonesArray.h"
#include <algorithm>
#include <iomanip>
using namespace std;
//using namespace SBSGEMModule;
//This should not be hard-coded, I think, but read in from the database (or perhaps not, if it never changes? For now we keep it hard-coded)
// const int APVMAP[128] = {1, 33, 65, 97, 9, 41, 73, 105, 17, 49, 81, 113, 25, 57, 89, 121, 3, 35, 67, 99, 11, 43, 75, 107, 19, 51, 83, 115, 27, 59, 91, 123, 5, 37, 69, 101, 13, 45, 77, 109, 21, 53, 85, 117, 29, 61, 93, 125, 7, 39, 71, 103, 15, 47, 79, 111, 23, 55, 87, 119, 31, 63, 95, 127, 0, 32, 64, 96, 8, 40, 72, 104, 16, 48, 80, 112, 24, 56, 88, 120, 2, 34, 66, 98, 10, 42, 74, 106, 18, 50, 82, 114, 26, 58, 90, 122, 4, 36, 68, 100, 12, 44, 76, 108, 20, 52, 84, 116, 28, 60, 92, 124, 6, 38, 70, 102, 14, 46, 78, 110, 22, 54, 86, 118, 30, 62, 94, 126};
SBSGEMModule::SBSGEMModule( const char *name, const char *description,
THaDetectorBase* parent ):
THaSubDetector(name,description,parent)
{
// FIXME: To database
//Set Default values for fZeroSuppress and fZeroSuppressRMS:
fZeroSuppress = kTRUE;
fZeroSuppressRMS = 5.0; //threshold in units of RMS:
fNegSignalStudy = kFALSE;
fPedestalMode = kFALSE;
fPedHistosInitialized = kFALSE;
fSubtractPedBeforeCommonMode = false; //only affects the pedestal-mode analysis
//Default online zero suppression to FALSE: actually I wonder if it would be better to use this in
// Moved this to MPDModule, since this should be done during the decoding of the raw APV data:
fOnlineZeroSuppression = kFALSE;
fCommonModeFlag = 0; //"sorting" method
fCommonModeOnlFlag = 3; // 3 = Danning method during GMn, 4 = Danning method during GEn
//Default: discard highest and lowest 28 strips for "sorting method" common-mode calculation:
fCommonModeNstripRejectHigh = 28;
fCommonModeNstripRejectLow = 28;
fCommonModeNumIterations = 3;
fCommonModeMinStripsInRange = 10;
fMakeCommonModePlots = false;
fCommonModePlotsInitialized = false;
fCommonModePlots_DBoverride = false;
fMakeEventInfoPlots = false;
fEventInfoPlotsInitialized = false;
fPedSubFlag = 1; //default to online ped subtraction, as that is the mode we will run in most of the time
fTrigTime = 0.0;
fMaxTrigTimeCorrection = 25.0;
fTrigTimeSlope = 1.0; //slope of GEM time versus trig time correlation
//Set default values for decode map parameters:
fN_APV25_CHAN = 128;
fN_MPD_TIME_SAMP = 6;
fMPDMAP_ROW_SIZE = 9;
//We should probably get rid of this as it's not used, only leads to confusion:
fNumberOfChannelInFrame = 129;
fSamplePeriod = 24.0; //nanoseconds:
fSigma_hitshape = 0.0004; //0.4 mm; controls cluster-splitting algorithm
// for( Int_t i = 0; i < N_MPD_TIME_SAMP; i++ ){
// fadc[i] = NULL;
// }
//Default clustering parameters:
fThresholdSample = 50.0;
fThresholdStripSum = 250.0;
fThresholdClusterSum = 500.0;
fThresholdSampleDeconv = 50.0;
fThresholdDeconvADCMaxCombo = 75.0;
fThresholdClusterSumDeconv = 150.0;
fADCasymCut = 1.1;
fTimeCutUVdiff = 30.0;
fCorrCoeffCut = -1.1;
fCorrCoeffCutDeconv = -1.1;
fADCasymSigma = 0.06;
fADCratioSigma = 0.1;
fTimeCutUVsigma = 3.0; //ns
fTimeCutUVdiffDeconv = 40.0; //ns
fTimeCutUVsigmaDeconv = 7.0;
fTimeCutUVdiffFit = 30.0;
fTimeCutUVsigmaFit = 3.0;
fFiltering_flag1D = 0; //"soft" cuts
fFiltering_flag2D = 0; //"soft" cuts
// default these offsets to zero:
fUStripOffset = 0.0;
fVStripOffset = 0.0;
fMakeEfficiencyPlots = true;
fEfficiencyInitialized = false;
// We want to change the default values for these dummy channels to accommodate up to 40 MPDs per VTP:
// fChan_CM_flags = 512; //default to 512:
// fChan_TimeStamp_low = 513;
// fChan_TimeStamp_high = 514;
// fChan_MPD_EventCount = 515;
// fChan_MPD_Debug = 516;
//Start dummy channels at 640 by default, to accommodate up to 40 MPDs per VTP crate
fChan_CM_flags = 640; //default to 640 (so as not to step on up to 40 MPDs per VTP crate):
fChan_TimeStamp_low = 641;
fChan_TimeStamp_high = 642;
fChan_MPD_EventCount = 643;
fChan_MPD_Debug = 644;
UInt_t MAXNSAMP_PER_APV = fN_APV25_CHAN * fN_MPD_TIME_SAMP;
//arrays to hold raw data from one APV card:
fStripAPV.resize( MAXNSAMP_PER_APV );
fRawStripAPV.resize( MAXNSAMP_PER_APV );
fRawADC_APV.resize( MAXNSAMP_PER_APV );
fPedSubADC_APV.resize( MAXNSAMP_PER_APV );
fCommonModeSubtractedADC_APV.resize( MAXNSAMP_PER_APV );
fCM_online.resize( fN_MPD_TIME_SAMP );
//default to
//fMAX2DHITS = 250000;
fMAX2DHITS = 10000;
fRMS_ConversionFactor = sqrt(fN_MPD_TIME_SAMP); //=2.45
fIsMC = false; //need to set default value!
fAPVmapping = SBSGEM::kUVA_XY; //default to UVA X/Y style APV mapping, but require this in the database::
InitAPVMAP();
fModuleGain = 1.0;
// std::cout << "SBSGEMModule constructor invoked, name = " << name << std::endl;
//Number of sigmas for defining common-mode max for online zero suppression
fCommonModeRange_nsigma = 5.0;
fSuppressFirstLast = 0; // suppress strips peaking in first or last time sample by default:
//fUseStripTimingCuts = false;
fStripTau = 56.0; //ns, default value. Eventually load this from DB. This is not actually used as of yet.
fUseStripTimingCuts = 0;
fUseTSchi2cut = false;
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_central[axis] = 87.0; //ns
fStripMaxTcut_width[axis] = 4.5; //sigmas
fStripMaxTcut_sigma[axis] = 7.0; //ns, for purpose of "hit quality chi2" calculation
fStripMaxTcut_central_deconv[axis] = 50.0; //ns
fStripMaxTcut_width_deconv[axis] = 4.5; //number of sigmas
fStripMaxTcut_sigma_deconv[axis] = 15.0; //ns
fStripMaxTcut_central_fit[axis] = 20.0; //ns
fStripMaxTcut_width_fit[axis] = 4.5; //sigmas
fStripMaxTcut_sigma_fit[axis] = 10.0; //ns
fHitTimeMean[axis] = 87.0;
fHitTimeSigma[axis] = 7.0;
fHitTimeMeanDeconv[axis] = 50.0;
fHitTimeSigmaDeconv[axis] = 15.0;
fHitTimeMeanFit[axis] = 20.0;
fHitTimeSigmaFit[axis] = 10.0;
}
fSigmaHitTimeAverageCorrected = 5.0; //ns
fStripAddTcut_width = 50.0; //this one we keep in ns
fStripAddCorrCoeffCut = 0.25;
fStripTSchi2Cut = 10.0; //not yet clear what is a good value for this.
fGoodStrip_TSfrac_mean.resize( fN_MPD_TIME_SAMP );
fGoodStrip_TSfrac_sigma.resize( fN_MPD_TIME_SAMP );
//Define some defaults for these:
double fracmean_default[6] = {0.055, 0.135, 0.203, 0.224, 0.208, 0.174};
double fracsigma_default[6] = {0.034, 0.039, 0.019, 0.021, 0.032, 0.035};
for( int isamp=0; isamp<fN_MPD_TIME_SAMP; isamp++ ){
if( isamp < fN_MPD_TIME_SAMP && isamp < 6 ){
fGoodStrip_TSfrac_mean[isamp] = fracmean_default[isamp];
fGoodStrip_TSfrac_sigma[isamp] = fracsigma_default[isamp];
}
}
fPulseShapeInitialized = false;
fMeasureCommonMode = true;
fNeventsCommonModeLookBack = 15;
fCorrectCommonMode = false;
fCorrectCommonModeMinStrips = 20;
fCorrectCommonMode_Nsigma = 5.0;
fCommonModeBinWidth_Nsigma = 1.0; //Bin width +/- 1 sigma by default
fCommonModeScanRange_Nsigma = 4.0; //Scan window +/- 4 sigma
fCommonModeStepSize_Nsigma = 0.2; //sigma/5 for step size:
fCommonModeDanningMethod_NsigmaCut = 3.0; //Default to 3 sigma
fClusteringFlag = 0; //"standard" clustering based on sum of six time samples on a strip
//fDeconvolutionFlag = 1; //Set "keep strip" flag based on deconvoluted ADC samples
fDeconvolutionFlag = 0; //Default should be zero
fStoreAll1Dclusters = false;
return;
}
SBSGEMModule::~SBSGEMModule() {
// if( fStrip ){
// fadc0 = NULL;
// fadc1 = NULL;
// fadc2 = NULL;
// fadc3 = NULL;
// fadc4 = NULL;
// fadc5 = NULL;
// for( Int_t i = 0; i < N_MPD_TIME_SAMP; i++ ){
// delete fadc[i];
// fadc[i] = NULL;
// }
// delete fPedestal;
// fPedestal = NULL;
// delete fStrip;
// fStrip = NULL;
// }
delete fStripTimeFunc;
}
Int_t SBSGEMModule::ReadDatabase( const TDatime& date ){
std::cout << "[SBSGEMModule::ReadDatabase]" << std::endl;
Int_t status;
FILE* file = OpenFile( date );
if( !file ) return kFileError;
std::vector<Double_t> rawpedu,rawpedv;
std::vector<Double_t> rawrmsu,rawrmsv;
//UShort_t layer;
//I think we can set up the entire database parsing in one shot here (AJRP). Together with the call to ReadGeometry, this should define basically everything we need.
//After loading, we will run some checks on the loaded information:
//copying commented structure of DBRequest here for reference (see VarDef.h):
// struct DBRequest {
// const char* name; // Key name
// void* var; // Pointer to data (default to Double*)
// VarType type; // (opt) data type (see VarType.h, default Double_t)
// UInt_t nelem; // (opt) number of array elements (0/1 = 1 or auto)
// Bool_t optional; // (opt) If true, missing key is ok
// Int_t search; // (opt) Search for key along name tree
// const char* descript; // (opt) Key description (if 0, same as name)
// };
// default these offsets to zero:
fUStripOffset = 0.0;
fVStripOffset = 0.0;
//std::cout << "Before loadDB, fCommonModePlotsInitialized = " << fCommonModePlotsInitialized << std::endl;
int cmplots_flag = fMakeCommonModePlots ? 1 : 0;
int zerosuppress_flag = fZeroSuppress ? 1 : 0;
int negsignalstudy_flag = fNegSignalStudy ? 1 : 0;
int onlinezerosuppress_flag = fOnlineZeroSuppression ? 1 : 0;
int eventinfoplots_flag = fMakeEventInfoPlots ? 1 : 0;
int usestriptimingcuts = fUseStripTimingCuts;
int useTSchi2cut = fUseTSchi2cut ? 1 : 0;
int suppressfirstlast = fSuppressFirstLast;
int usecommonmoderollingaverage = fMeasureCommonMode ? 1 : 0;
int correctcommonmode = fCorrectCommonMode ? 1 : 0;
std::vector<double> TSfrac_mean_temp;
std::vector<double> TSfrac_sigma_temp;
//For parsing "strip" timing cuts:
std::vector<double> t0_temp, tsigma_temp, tcut_temp;
std::vector<double> t0_deconv_temp, tsigma_deconv_temp, tcut_deconv_temp;
std::vector<double> t0_fit_temp, tsigma_fit_temp, tcut_fit_temp;
//For parsing "hit" timing cuts:
std::vector<double> t0hit_temp, tsigmahit_temp;
std::vector<double> t0hit_deconv_temp, tsigmahit_deconv_temp;
std::vector<double> t0hit_fit_temp, tsigmahit_fit_temp;
const DBRequest request[] = {
{ "chanmap", &fChanMapData, kIntV, 0, 0, 0}, // mandatory: decode map info
{ "apvmap", &fAPVmapping, kUInt, 0, 1, 1}, //optional, allow search up the tree if all modules in a setup have the same APV mapping
{ "pedu", &rawpedu, kDoubleV, 0, 1, 0}, // optional raw pedestal info (u strips)
{ "pedv", &rawpedv, kDoubleV, 0, 1, 0}, // optional raw pedestal info (v strips)
{ "rmsu", &rawrmsu, kDoubleV, 0, 1, 0}, // optional pedestal rms info (u strips)
{ "rmsv", &rawrmsv, kDoubleV, 0, 1, 0}, // optional pedestal rms info (v strips)
{ "layer", &fLayer, kUShort, 0, 0, 0}, // mandatory: logical tracking layer must be specified for every module:
{ "nstripsu", &fNstripsU, kUInt, 0, 0, 1}, //mandatory: number of strips in module along U axis
{ "nstripsv", &fNstripsV, kUInt, 0, 0, 1}, //mandatory: number of strips in module along V axis
{ "uangle", &fUAngle, kDouble, 0, 0, 1}, //mandatory: Angle of "U" strips wrt X axis
{ "vangle", &fVAngle, kDouble, 0, 0, 1}, //mandatory: Angle of "V" strips wrt X axis
{ "uoffset", &fUStripOffset, kDouble, 0, 1, 1}, //optional: position of first U strip
{ "voffset", &fVStripOffset, kDouble, 0, 1, 1}, //optional: position of first V strip
{ "upitch", &fUStripPitch, kDouble, 0, 0, 1}, //mandatory: Pitch of U strips
{ "vpitch", &fVStripPitch, kDouble, 0, 0, 1}, //mandatory: Pitch of V strips
{ "ugain", &fUgain, kDoubleV, 0, 1, 0}, //(optional): Gain of U strips by APV card (ordered by strip position, NOT by order of appearance in decode map)
{ "vgain", &fVgain, kDoubleV, 0, 1, 0}, //(optional): Gain of V strips by APV card (ordered by strip position, NOT by order of appearance in decode map)
{ "modulegain", &fModuleGain, kDouble, 0, 1, 1},
{ "threshold_sample", &fThresholdSample, kDouble, 0, 1, 1}, //(optional): threshold on max. ADC sample to keep strip (baseline-subtracted)
{ "threshold_stripsum", &fThresholdStripSum, kDouble, 0, 1, 1}, //(optional): threshold on sum of ADC samples on a strip (baseline-subtracted)
{ "threshold_clustersum", &fThresholdClusterSum, kDouble, 0, 1, 1}, //(optional): threshold on sum of all ADCs over all strips in a cluster (baseline-subtracted)
{ "threshold_sample_deconv", &fThresholdSampleDeconv, kDouble, 0, 1, 1 },
{ "threshold_maxcombo_deconv", &fThresholdDeconvADCMaxCombo, kDouble, 0, 1, 1 },
{ "threshold_clustersum_deconv", &fThresholdClusterSumDeconv, kDouble, 0, 1, 1 },
{ "ADCasym_cut", &fADCasymCut, kDouble, 0, 1, 1}, //(optional): filter 2D hits by ADC asymmetry, |Asym| < cut
{ "deltat_cut", &fTimeCutUVdiff, kDouble, 0, 1, 1}, //(optional): filter 2D hits by U/V time difference
{ "corrcoeff_cut", &fCorrCoeffCut, kDouble, 0, 1, 1},
{ "filterflag1D", &fFiltering_flag1D, kInt, 0, 1, 1},
{ "filterflag2D", &fFiltering_flag2D, kInt, 0, 1, 1},
{ "peakprominence_minsigma", &fThresh_2ndMax_nsigma, kDouble, 0, 1, 1}, //(optional): reject overlapping clusters with peak prominence less than this number of sigmas
{ "peakprominence_minfraction", &fThresh_2ndMax_fraction, kDouble, 0, 1, 1}, //(optional): reject overlapping clusters with peak prominence less than this fraction of height of nearby higher peak
{ "maxnu_charge", &fMaxNeighborsU_totalcharge, kUShort, 0, 1, 1}, //(optional): cluster size restriction along U for total charge calculation
{ "maxnv_charge", &fMaxNeighborsV_totalcharge, kUShort, 0, 1, 1}, //(optional): cluster size restriction along V for total charge calculation
{ "maxnu_pos", &fMaxNeighborsU_hitpos, kUShort, 0, 1, 1}, //(optional): cluster size restriction for position reconstruction
{ "maxnv_pos", &fMaxNeighborsV_hitpos, kUShort, 0, 1, 1}, //(optional): cluster size restriction for position reconstruction
{ "sigmahitshape", &fSigma_hitshape, kDouble, 0, 1, 1}, //(optional): width parameter for cluster-splitting algorithm
{ "zerosuppress", &zerosuppress_flag, kUInt, 0, 1, 1}, //(optional, search): toggle offline zero suppression (default = true).
{ "zerosuppress_nsigma", &fZeroSuppressRMS, kDouble, 0, 1, 1}, //(optional, search):
{ "do_neg_signal_study", &negsignalstudy_flag, kUInt, 0, 1, 1}, //(optional, search): toggle doing negative signal analysis
{ "onlinezerosuppress", &onlinezerosuppress_flag, kUInt, 0, 1, 1}, //(optional, search)
{ "commonmode_meanU", &fCommonModeMeanU, kDoubleV, 0, 1, 0}, //(optional, don't search)
{ "commonmode_meanV", &fCommonModeMeanV, kDoubleV, 0, 1, 0}, //(optional, don't search)
{ "commonmode_rmsU", &fCommonModeRMSU, kDoubleV, 0, 1, 0}, //(optional, don't search)
{ "commonmode_rmsV", &fCommonModeRMSV, kDoubleV, 0, 1, 0}, //(optional, don't search)
{ "commonmode_flag", &fCommonModeFlag, kInt, 0, 1, 1}, //optional, search up the tree
{ "commonmode_online_flag", &fCommonModeOnlFlag, kInt, 0, 1, 1}, //optional, search up the tree
{ "commonmode_nstriplo", &fCommonModeNstripRejectLow, kInt, 0, 1, 1}, //optional, search up the tree:
{ "commonmode_nstriphi", &fCommonModeNstripRejectHigh, kInt, 0, 1, 1}, //optional, search:
{ "commonmode_niter", &fCommonModeNumIterations, kInt, 0, 1, 1},
{ "commonmode_minstrips", &fCommonModeMinStripsInRange, kInt, 0, 1, 1},
{ "commonmode_range_nsigma", &fCommonModeRange_nsigma, kDouble, 0, 1, 1},
{ "commonmode_danning_nsigma_cut", &fCommonModeDanningMethod_NsigmaCut, kDouble, 0, 1, 1 },
{ "plot_common_mode", &cmplots_flag, kInt, 0, 1, 1},
{ "plot_event_info", &eventinfoplots_flag, kInt, 0, 1, 1},
{ "chan_cm_flags", &fChan_CM_flags, kUInt, 0, 1, 1}, //optional, search up the tree: must match the value in crate map!
{ "chan_timestamp_low", &fChan_TimeStamp_low, kUInt, 0, 1, 1},
{ "chan_timestamp_high", &fChan_TimeStamp_high, kUInt, 0, 1, 1},
{ "chan_event_count", &fChan_MPD_EventCount, kUInt, 0, 1, 1},
{ "pedsub_online", &fPedSubFlag, kInt, 0, 1, 1},
{ "max2Dhits", &fMAX2DHITS, kUInt, 0, 1, 1}, //optional, search up tree
{ "usestriptimingcut", &fUseStripTimingCuts, kInt, 0, 1, 1 },
{ "useTSchi2cut", &useTSchi2cut, kInt, 0, 1, 1 },
{ "maxstrip_t0", &t0_temp, kDoubleV, 0, 1, 1 },
{ "maxstrip_t0_deconv", &t0_deconv_temp, kDoubleV, 0, 1, 1 },
{ "maxstrip_t0_fit", &t0_fit_temp, kDoubleV, 0, 1, 1 },
{ "maxstrip_tcut", &tcut_temp, kDoubleV, 0, 1, 1 },
{ "maxstrip_tcut_deconv", &tcut_deconv_temp, kDoubleV, 0, 1, 1 },
{ "maxstrip_tcut_fit", &tcut_fit_temp, kDoubleV, 0, 1, 1 },
{ "maxstrip_tsigma", &tsigma_temp, kDoubleV, 0, 1, 1 },
{ "maxstrip_tsigma_deconv", &tsigma_deconv_temp, kDoubleV, 0, 1, 1 },
{ "maxstrip_tsigma_fit", &tsigma_fit_temp, kDoubleV, 0, 1, 1 },
{ "addstrip_tcut", &fStripAddTcut_width, kDouble, 0, 1, 1 },
{ "addstrip_ccor_cut", &fStripAddCorrCoeffCut, kDouble, 0, 1, 1 },
{ "goodstrip_TSfrac_mean", &TSfrac_mean_temp, kDoubleV, 0, 1, 1 },
{ "goodstrip_TSfrac_sigma", &TSfrac_sigma_temp, kDoubleV, 0, 1, 1 },
{ "suppressfirstlast", &suppressfirstlast, kInt, 0, 1, 1 },
{ "use_commonmode_rolling_average", &usecommonmoderollingaverage, kInt, 0, 1, 1 },
{ "commonmode_nevents_lookback", &fNeventsCommonModeLookBack, kUInt, 0, 1, 1 },
{ "correct_common_mode", &correctcommonmode, kInt, 0, 1, 1 },
{ "correct_common_mode_minstrips", &fCorrectCommonModeMinStrips, kUInt, 0, 1, 1 },
{ "correct_common_mode_nsigma", &fCorrectCommonMode_Nsigma, kDouble, 0, 1, 1 },
{ "commonmode_binwidth_nsigma", &fCommonModeBinWidth_Nsigma, kDouble, 0, 1, 1 },
{ "commonmode_scanrange_nsigma", &fCommonModeScanRange_Nsigma, kDouble, 0, 1, 1 },
{ "commonmode_stepsize_nsigma", &fCommonModeStepSize_Nsigma, kDouble, 0, 1, 1 },
{ "deconvolution_tau", &fStripTau, kDouble, 0, 1, 1 },
{ "CMbiasU", &fCMbiasU, kDoubleV, 0, 1, 1 },
{ "CMbiasV", &fCMbiasV, kDoubleV, 0, 1, 1 },
{ "clustering_flag", &fClusteringFlag, kInt, 0, 1, 1 },
{ "deconvolution_flag", &fDeconvolutionFlag, kInt, 0, 1, 1 },
{ "maxtrigtime_correction", &fMaxTrigTimeCorrection, kDouble, 0, 1, 1 },
{ "trigtime_slope", &fTrigTimeSlope, kDouble, 0, 1, 1 },
{ "ADCasym_sigma", &fADCasymSigma, kDouble, 0, 1, 1 },
{ "deltat_sigma", &fTimeCutUVsigma, kDouble, 0, 1, 1 },
{ "deltat_cut_deconv", &fTimeCutUVdiffDeconv, kDouble, 0, 1, 1 },
{ "deltat_sigma_deconv", &fTimeCutUVsigmaDeconv, kDouble, 0, 1, 1 },
{ "deltat_cut_fit", &fTimeCutUVdiffFit, kDouble, 0, 1, 1 },
{ "deltat_sigma_fit", &fTimeCutUVsigmaFit, kDouble, 0, 1, 1 },
{ "corrcoeff_cut_deconv", &fCorrCoeffCutDeconv, kDouble, 0, 1, 1 },
{ "ADCratio_sigma", &fADCratioSigma, kDouble, 0, 1, 1 },
{ "HitTimeMean", &t0hit_temp, kDoubleV, 0, 1, 1 },
{ "HitTimeSigma", &tsigmahit_temp, kDoubleV, 0, 1, 1 },
{ "HitTimeMeanDeconv", &t0hit_deconv_temp, kDoubleV, 0, 1, 1 },
{ "HitTimeSigmaDeconv", &tsigmahit_deconv_temp, kDoubleV, 0, 1, 1 },
{ "HitTimeMeanFit", &t0hit_fit_temp, kDoubleV, 0, 1, 1 },
{ "HitTimeSigmaFit", &tsigmahit_fit_temp, kDoubleV, 0, 1, 1 },
{ "sigma_tcorr", &fSigmaHitTimeAverageCorrected, kDouble, 0, 1, 1 },
{0}
};
status = LoadDB( file, date, request, fPrefix, 1 ); //The "1" after fPrefix means search up the tree
if( status != 0 ){
fclose(file);
return status;
}
if( !fCommonModePlots_DBoverride ) fMakeCommonModePlots = cmplots_flag != 0;
fZeroSuppress = zerosuppress_flag != 0;
fOnlineZeroSuppression = onlinezerosuppress_flag != 0;
fNegSignalStudy = negsignalstudy_flag != 0;
fMakeEventInfoPlots = eventinfoplots_flag != 0;
//fUseStripTimingCuts = usestriptimingcuts != 0;
fUseTSchi2cut = useTSchi2cut != 0;
fSuppressFirstLast = suppressfirstlast;
//fMeasureCommonMode = usecommonmoderollingaverage != 0;
fMeasureCommonMode = true; //we're not turning this off
fCorrectCommonMode = correctcommonmode != 0;
if( fUseTSchi2cut && TSfrac_mean_temp.size() == fN_MPD_TIME_SAMP && TSfrac_sigma_temp.size() == fN_MPD_TIME_SAMP ){
fGoodStrip_TSfrac_mean = TSfrac_mean_temp;
fGoodStrip_TSfrac_sigma = TSfrac_sigma_temp;
}
// std::cout << "After loadDB, fCommonModePlotsInitialized = " << fCommonModePlotsInitialized << std::endl;
if( /*fAPVmapping < SBSGEM::kINFN ||*/ fAPVmapping > SBSGEM::kMC ) {
std::cout << "Warning in SBSGEMModule::Decode for module " << GetParent()->GetName() << "." << GetName() << ": invalid APV mapping choice, defaulting to UVA X/Y." << std::endl
<< " Analysis results may be incorrect" << std::endl;
fAPVmapping = SBSGEM::kUVA_XY;
}
//prevent the user from defining something silly for the common-mode stuff:
fCommonModeNstripRejectLow = std::min( 50, std::max( 0, fCommonModeNstripRejectLow ) );
fCommonModeNstripRejectHigh = std::min( 50, std::max( 0, fCommonModeNstripRejectHigh ) );
fCommonModeNumIterations = std::min( 10, std::max( 2, fCommonModeNumIterations ) );
fCommonModeMinStripsInRange = std::min( fN_APV25_CHAN-25, std::max(1, fCommonModeMinStripsInRange ) );
double x = fSamplePeriod/fStripTau;
fDeconv_weights[0] = exp( x - 1.0 )/x; //~1.32
fDeconv_weights[1] = -2.0*exp(-1.0)/x; //~ -1.72
fDeconv_weights[2] = exp(-1.0-x)/x; //0.56
//std::cout << GetName() << " fThresholdStripSum " << fThresholdStripSum
//<< " fThresholdSample " << fThresholdSample << std::endl;
if( fIsMC ){
fCommonModeFlag = -1;
fPedestalMode = false;
fOnlineZeroSuppression = true;
fAPVmapping = SBSGEM::kMC;
}
fPxU = cos( fUAngle * TMath::DegToRad() );
fPyU = sin( fUAngle * TMath::DegToRad() );
fPxV = cos( fVAngle * TMath::DegToRad() );
fPyV = sin( fVAngle * TMath::DegToRad() );
fAPVch_by_Ustrip.clear();
fAPVch_by_Vstrip.clear();
fMPDID_by_Ustrip.clear();
fMPDID_by_Vstrip.clear();
fADCch_by_Ustrip.clear();
fADCch_by_Vstrip.clear();
//Count APV cards by axis. Each APV card must have one decode map entry:
fNAPVs_U = 0;
fNAPVs_V = 0;
fMPDmap.clear();
Int_t nentry = fChanMapData.size()/fMPDMAP_ROW_SIZE;
fCommonModeResultContainer_by_APV.resize( nentry );
fCommonModeRollingAverage_by_APV.resize( nentry );
fCommonModeRollingRMS_by_APV.resize( nentry );
fNeventsRollingAverage_by_APV.resize( nentry );
fCMbiasResultContainer_by_APV.resize( nentry );
fCommonModeOnlineBiasRollingAverage_by_APV.resize( nentry );
fCommonModeOnlineBiasRollingRMS_by_APV.resize( nentry );
fNeventsOnlineBias_by_APV.resize( nentry );
for( Int_t mapline = 0; mapline < nentry; mapline++ ){
mpdmap_t thisdata;
thisdata.crate = fChanMapData[0+mapline*fMPDMAP_ROW_SIZE];
thisdata.slot = fChanMapData[1+mapline*fMPDMAP_ROW_SIZE];
thisdata.mpd_id = fChanMapData[2+mapline*fMPDMAP_ROW_SIZE];
thisdata.gem_id = fChanMapData[3+mapline*fMPDMAP_ROW_SIZE];
thisdata.adc_id = fChanMapData[4+mapline*fMPDMAP_ROW_SIZE];
thisdata.i2c = fChanMapData[5+mapline*fMPDMAP_ROW_SIZE];
thisdata.pos = fChanMapData[6+mapline*fMPDMAP_ROW_SIZE];
thisdata.invert = fChanMapData[7+mapline*fMPDMAP_ROW_SIZE];
thisdata.axis = fChanMapData[8+mapline*fMPDMAP_ROW_SIZE];
thisdata.index = mapline;
//Populate relevant quantities mapped by strip index:
for( int ich=0; ich<fN_APV25_CHAN; ich++ ){
int strip = GetStripNumber( ich, thisdata.pos, thisdata.invert );
if( thisdata.axis == SBSGEM::kUaxis ){
fAPVch_by_Ustrip[strip] = ich;
fMPDID_by_Ustrip[strip] = thisdata.mpd_id;
fADCch_by_Ustrip[strip] = thisdata.adc_id;
} else {
fAPVch_by_Vstrip[strip] = ich;
fMPDID_by_Vstrip[strip] = thisdata.mpd_id;
fADCch_by_Vstrip[strip] = thisdata.adc_id;
}
}
if( thisdata.axis == SBSGEM::kUaxis ){
fNAPVs_U++;
} else {
fNAPVs_V++;
}
fMPDmap.push_back(thisdata);
fEventCount_by_APV.push_back( 0 );
fT0_by_APV.push_back( 0 );
fTcoarse_by_APV.push_back( 0 );
fTfine_by_APV.push_back( 0 );
fTimeStamp_ns_by_APV.push_back( 0 );
//fCommonModeRollingFirstEvent_by_APV[mapline] = 0.0;
fCommonModeResultContainer_by_APV[mapline].resize( fNeventsCommonModeLookBack*fN_MPD_TIME_SAMP );
fCommonModeRollingAverage_by_APV[mapline] = 0.0;
fCommonModeRollingRMS_by_APV[mapline] = 10.0;
fNeventsRollingAverage_by_APV[mapline] = 0; //Really will be the number of time samples = 6 * number of events
fCMbiasResultContainer_by_APV[mapline].resize( fNeventsCommonModeLookBack*fN_MPD_TIME_SAMP );
fCommonModeOnlineBiasRollingAverage_by_APV[mapline] = 0.0;
fCommonModeOnlineBiasRollingRMS_by_APV[mapline] = 10.0;
fNeventsOnlineBias_by_APV[mapline] = 0;
}
//if a different number of decode map entries is counted than the expectation based on the number of strips,
//e.g., because we commented out one or more decode map entries, then we go with the larger of the two numbers.
//This isn't perfectly idiot-proof, but prevents the kind of undefined behavior we want to avoid:
//if( fNAPVs_U != fNstripsU/fN_APV25_CHAN ){
fNAPVs_U = std::max( fNAPVs_U, fNstripsU/fN_APV25_CHAN );
//}
fNAPVs_V = std::max( fNAPVs_V, fNstripsV/fN_APV25_CHAN );
//resize vectors that hold APV-card specific parameters:
// fUgain.resize( fNAPVs_U );
// fVgain.resize( fNAPVs_V );
// fCommonModeMeanU.resize( fNAPVs_U );
// fCommonModeMeanV.resize( fNAPVs_V );
// fCommonModeRMSU.resize( fNAPVs_U );
// fCommonModeRMSV.resize( fNAPVs_V );
std::cout << fName << " mapped to " << nentry << " APV25 chips, module gain = " << fModuleGain << std::endl;
//Geometry info is required to be present in the database for each module:
Int_t err = ReadGeometry( file, date, true );
if( err ) {
fclose(file);
return err;
}
//Initialize all pedestals to zero, RMS values to default:
fPedestalU.clear();
fPedestalU.resize( fNstripsU );
fPedRMSU.clear();
fPedRMSU.resize( fNstripsU );
// std::cout << "got " << rawpedu.size() << " u pedestal mean values and " << rawrmsu.size() << " u pedestal rms values" << std::endl;
// std::cout << "got " << rawpedv.size() << " v pedestal mean values and " << rawrmsv.size() << " v pedestal rms values" << std::endl;
// for( int i=0; i<rawpedu.size(); i++ ){
// cout << i << ", " << rawpedu[i] << endl;
// }
for ( UInt_t istrip=0; istrip<fNstripsU; istrip++ ){
fPedestalU[istrip] = 0.0;
fPedRMSU[istrip] = 10.0; //placeholder to be replaced by value from database
if( rawpedu.size() == fNstripsU ){
fPedestalU[istrip] = rawpedu[istrip];
}else if( rawpedu.size() == fNstripsU/128 ){
fPedestalU[istrip] = rawpedu[istrip/128];
}else if(!rawpedu.empty()){
fPedestalU[istrip] = rawpedu[0];
}
if( rawrmsu.size() == fNstripsU ){
fPedRMSU[istrip] = rawrmsu[istrip];
}else if( rawrmsu.size() == fNstripsU/128 ){
fPedRMSU[istrip] = rawrmsu[istrip/128];
}else if(!rawrmsu.empty()){
fPedRMSU[istrip] = rawrmsu[0];
}
}
//Initialize all pedestals to zero, RMS values to default:
fPedestalV.clear();
fPedestalV.resize( fNstripsV );
fPedRMSV.clear();
fPedRMSV.resize( fNstripsV );
for( UInt_t istrip=0; istrip<fNstripsV; istrip++ ){
fPedestalV[istrip] = 0.0;
fPedRMSV[istrip] = 10.0;
if( rawpedv.size() == fNstripsV ){
fPedestalV[istrip] = rawpedv[istrip];
}else if( rawpedv.size() == fNstripsV/128 ){
fPedestalV[istrip] = rawpedv[istrip/128];
}else if(!rawpedv.empty()){
fPedestalV[istrip] = rawpedv[0];
}
if( rawrmsv.size() == fNstripsV ){
fPedRMSV[istrip] = rawrmsv[istrip];
}else if( rawrmsv.size() == fNstripsV/128 ){
fPedRMSV[istrip] = rawrmsv[istrip/128];
}else if(!rawrmsv.empty()){
fPedRMSV[istrip] = rawrmsv[0];
}
}
// //resize all the "decoded strip" arrays to their maximum possible values for this module:
UInt_t nstripsmax = fNstripsU + fNstripsV;
fStrip.resize( nstripsmax );
fAxis.resize( nstripsmax );
fADCsamples.resize( nstripsmax );
fRawADCsamples.resize( nstripsmax );
fADCsamples_deconv.resize( nstripsmax );
//The lines below are problematic and unnecessary
for( unsigned int istrip=0; istrip<nstripsmax; istrip++ ){
fADCsamples[istrip].resize( fN_MPD_TIME_SAMP );
fRawADCsamples[istrip].resize( fN_MPD_TIME_SAMP );
fADCsamples_deconv[istrip].resize( fN_MPD_TIME_SAMP );
}
fADCsums.resize( nstripsmax );
fADCsumsDeconv.resize( nstripsmax );
fStripADCavg.resize( nstripsmax );
fStripIsU.resize( nstripsmax );
fStripIsV.resize( nstripsmax );
fStripOnTrack.resize( nstripsmax );
fStripIsNeg.resize( nstripsmax );
fStripIsNegU.resize( nstripsmax );
fStripIsNegV.resize( nstripsmax );
fStripIsNegOnTrack.resize( nstripsmax );
fStripIsNegOnTrackU.resize( nstripsmax );
fStripIsNegOnTrackV.resize( nstripsmax );
fStripRaw.resize( nstripsmax );
fStripEvent.resize( nstripsmax );
fStripCrate.resize( nstripsmax );
fStripMPD.resize( nstripsmax );
fStripADC_ID.resize( nstripsmax );
fStripTrackIndex.resize( nstripsmax );
fKeepStrip.resize( nstripsmax );
fMaxSamp.resize( nstripsmax );
fMaxSampDeconv.resize( nstripsmax );
fMaxSampDeconvCombo.resize( nstripsmax );
fADCmax.resize( nstripsmax );
fADCmaxDeconv.resize( nstripsmax );
fADCmaxDeconvCombo.resize( nstripsmax );
fTmean.resize( nstripsmax );
fTmeanDeconv.resize( nstripsmax );
fTsigma.resize( nstripsmax );
fStripTdiff.resize( nstripsmax );
fStripTSchi2.resize( nstripsmax );
fStripTSprob.resize( nstripsmax );
fStripCorrCoeff.resize( nstripsmax );
fStripTfit.resize( nstripsmax );
fTcorr.resize( nstripsmax );
//Storing these by individual strip is redundant but convenient:
fStrip_ENABLE_CM.resize( nstripsmax );
fStrip_CM_GOOD.resize( nstripsmax );
fStrip_BUILD_ALL_SAMPLES.resize( nstripsmax );
fStripUonTrack.resize( nstripsmax );
fStripVonTrack.resize( nstripsmax );
fADCsamples1D.resize( nstripsmax * fN_MPD_TIME_SAMP );
fRawADCsamples1D.resize( nstripsmax * fN_MPD_TIME_SAMP );
fADCsamplesDeconv1D.resize( nstripsmax * fN_MPD_TIME_SAMP );
//default all common-mode mean and RMS values to 0 and 10 respectively if they were
// NOT loaded from the DB and/or they are loaded with the wrong size:
if( fCommonModeMeanU.size() != fNAPVs_U ){
fCommonModeMeanU.resize( fNAPVs_U );
for( unsigned int iAPV=0; iAPV<fNAPVs_U; iAPV++ ){
fCommonModeMeanU[iAPV] = 0.0;
}
}
if( fCommonModeRMSU.size() != fNAPVs_U ){
fCommonModeRMSU.resize( fNAPVs_U );
for( unsigned int iAPV=0; iAPV<fNAPVs_U; iAPV++ ){
fCommonModeRMSU[iAPV] = 10.0;
}
}
//default all common-mode mean and RMS values to 0 and 10 respectively if they were
// NOT loaded from the DB and/or they were loaded with the wrong size:
if( fCommonModeMeanV.size() != fNAPVs_V ){
fCommonModeMeanV.resize( fNAPVs_V );
for( unsigned int iAPV=0; iAPV<fNAPVs_V; iAPV++ ){
fCommonModeMeanV[iAPV] = 0.0;
}
}
if( fCommonModeRMSV.size() != fNAPVs_V ){
fCommonModeRMSV.resize( fNAPVs_V );
for( unsigned int iAPV=0; iAPV<fNAPVs_V; iAPV++ ){
fCommonModeRMSV[iAPV] = 10.0;
}
}
// Initialize default "CM correction bias" values to zero if they were not loaded from the DB:
if( fCMbiasU.size() != fNAPVs_U ){
fCMbiasU.resize( fNAPVs_U );
for( unsigned int iAPV=0; iAPV<fNAPVs_U; iAPV++ ){
fCMbiasU[iAPV] = 0.0;
}
}
if( fCMbiasV.size() != fNAPVs_V ){
fCMbiasV.resize( fNAPVs_V );
for( unsigned int iAPV=0; iAPV<fNAPVs_V; iAPV++ ){
fCMbiasV[iAPV] = 0.0;
}
}
//default all gains to 1 if they were not loaded from the DB and/or if they were loaded with the
//wrong size:
if( fUgain.size() != fNAPVs_U ){
fUgain.resize(fNAPVs_U);
for( unsigned int iAPV=0; iAPV<fNAPVs_U; iAPV++ ){
fUgain[iAPV] = 1.0;
}
}
//Multiply in Module gain:
for( unsigned int iAPV=0; iAPV<fNAPVs_U; iAPV++ ){
fUgain[iAPV] *= fModuleGain;
}
if( fVgain.size() != fNAPVs_V ){
fVgain.resize(fNAPVs_V);
for( unsigned int iAPV=0; iAPV<fNAPVs_V; iAPV++ ){
fVgain[iAPV] = 1.0;
}
}
for( unsigned int iAPV=0; iAPV<fNAPVs_V; iAPV++ ){
fVgain[iAPV] *= fModuleGain;
}
if( fPedestalMode ){
fZeroSuppress = false;
fOnlineZeroSuppression = false;
//fPedSubFlag = 0;
}
//Add parsing of timing cut arguments now:
//All timing cut arguments have default values so we can parse them individually:
if( t0_temp.size() > 0 ){
if( t0_temp.size() == 1 ){
fStripMaxTcut_central[0] = fStripMaxTcut_central[1] = t0_temp[0];
} else if( t0_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_central[axis] = t0_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut center (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tcut_temp.size() > 0 ){
if( tcut_temp.size() == 1 ){
fStripMaxTcut_width[0] = fStripMaxTcut_width[1] = tcut_temp[0];
} else if( tcut_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_width[axis] = tcut_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut width (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tsigma_temp.size() > 0 ){
if( tsigma_temp.size() == 1 ){
fStripMaxTcut_sigma[0] = fStripMaxTcut_sigma[1] = tsigma_temp[0];
} else if( tsigma_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_sigma[axis] = tsigma_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut sigma (must be 1 or 2). Fix database");
return kInitError;
}
}
//Deconvoluted strip time cuts:
//All timing cut arguments have default values so we can parse them individually:
if( t0_deconv_temp.size() > 0 ){
if( t0_deconv_temp.size() == 1 ){
fStripMaxTcut_central_deconv[0] = fStripMaxTcut_central_deconv[1] = t0_deconv_temp[0];
} else if( t0_deconv_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_central_deconv[axis] = t0_deconv_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut center deconv (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tcut_deconv_temp.size() > 0 ){
if( tcut_deconv_temp.size() == 1 ){
fStripMaxTcut_width_deconv[0] = fStripMaxTcut_width_deconv[1] = tcut_deconv_temp[0];
} else if( tcut_deconv_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_width_deconv[axis] = tcut_deconv_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut width (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tsigma_deconv_temp.size() > 0 ){
if( tsigma_deconv_temp.size() == 1 ){
fStripMaxTcut_sigma_deconv[0] = fStripMaxTcut_sigma_deconv[1] = tsigma_deconv_temp[0];
} else if( tsigma_deconv_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_sigma_deconv[axis] = tsigma_deconv_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut center (must be 1 or 2). Fix database");
return kInitError;
}
}
//Fit strip time cuts:
//All timing cut arguments have default values so we can parse them individually:
if( t0_fit_temp.size() > 0 ){
if( t0_fit_temp.size() == 1 ){
fStripMaxTcut_central_fit[0] = fStripMaxTcut_central_fit[1] = t0_fit_temp[0];
} else if( t0_fit_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_central_fit[axis] = t0_fit_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut fit center (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tcut_fit_temp.size() > 0 ){
if( tcut_fit_temp.size() == 1 ){
fStripMaxTcut_width_fit[0] = fStripMaxTcut_width_fit[1] = tcut_fit_temp[0];
} else if( tcut_fit_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_width_fit[axis] = tcut_fit_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut width (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tsigma_fit_temp.size() > 0 ){
if( tsigma_fit_temp.size() == 1 ){
fStripMaxTcut_sigma_fit[0] = fStripMaxTcut_sigma_fit[1] = tsigma_fit_temp[0];
} else if( tsigma_fit_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fStripMaxTcut_sigma_fit[axis] = tsigma_fit_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for max strip tcut center (must be 1 or 2). Fix database");
return kInitError;
}
}
//Parsing hit time mean and sigma: standard
if( t0hit_temp.size() != 0 ){
if( t0hit_temp.size() == 1 ){
fHitTimeMean[1] = fHitTimeMean[0] = t0hit_temp[0];
} else if( t0hit_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fHitTimeMean[axis] = t0hit_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for hit time mean (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tsigmahit_temp.size() != 0 ){
if( tsigmahit_temp.size() == 1 ){
fHitTimeSigma[1] = fHitTimeSigma[0] = tsigmahit_temp[0];
} else if( tsigmahit_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fHitTimeSigma[axis] = tsigmahit_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for hit time sigma (must be 1 or 2). Fix database");
return kInitError;
}
}
//Parsing hit time mean and sigma: deconvoluted:
if( t0hit_deconv_temp.size() != 0 ){
if( t0hit_deconv_temp.size() == 1 ){
fHitTimeMeanDeconv[1] = fHitTimeMeanDeconv[0] = t0hit_deconv_temp[0];
} else if( t0hit_deconv_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fHitTimeMeanDeconv[axis] = t0hit_deconv_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for hit time mean (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tsigmahit_deconv_temp.size() != 0 ){
if( tsigmahit_deconv_temp.size() == 1 ){
fHitTimeSigmaDeconv[1] = fHitTimeSigmaDeconv[0] = tsigmahit_deconv_temp[0];
} else if( tsigmahit_deconv_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fHitTimeSigmaDeconv[axis] = tsigmahit_deconv_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for hit time sigma (must be 1 or 2). Fix database");
return kInitError;
}
}
//cluster time mean and sigma parsing: fit times
if( t0hit_fit_temp.size() != 0 ){
if( t0hit_fit_temp.size() == 1 ){
fHitTimeMeanFit[1] = fHitTimeMeanFit[0] = t0hit_fit_temp[0];
} else if( t0hit_fit_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){
fHitTimeMeanFit[axis] = t0hit_fit_temp[axis];
}
} else {
Error(Here("ReadDatabase"), "Incorrect number of values for hit time mean (must be 1 or 2). Fix database");
return kInitError;
}
}
if( tsigmahit_fit_temp.size() != 0 ){
if( tsigmahit_fit_temp.size() == 1 ){
fHitTimeSigmaFit[1] = fHitTimeSigmaFit[0] = tsigmahit_fit_temp[0];
} else if( tsigmahit_fit_temp.size() == 2 ){
for( int axis=0; axis<2; axis++ ){