SVDCoGTimeCalibrationImporterModule Class Reference

Inheritance diagram for SVDCoGTimeCalibrationImporterModule:

Collaboration diagram for SVDCoGTimeCalibrationImporterModule:

Public Member Functions
def	notApplyCorrectForCDCLatency (self, mode)
def	fillLists (self, mode_byte_object, svdClusters_rel_RecoTracks_cl)
def	set_localdb (self, localDB)
def	initialize (self)
def	event (self)
def	terminate (self)

Public Attributes
	notApplyCDCLatencyCorrection
	parameter that allows to apply or not the CDC latency correction
	NTOT
	counts the number of clusters
	localdb
	set the name of the localDB used
	outputFileName
	name of the output file
	resList
	lists used to create the histograms for each TB : residuals
	spList
	scatterplot t0 vs cog
	cogList
	cog
	cdcList
	t0
	snrList
	Cluster SNR.
	nList
	number of clusters
	sumCOGList
	sum of CoG times
	Evt
	counts the number of events
	EventT0Hist
	distribution of EventT0
	AlphaUTB
	alpha parameter vs TB, for U side
	AlphaVTB
	alpha parameter vs TB, for V side
	BetaUTB
	beta parameter vs TB, for U side
	BetaVTB
	beta parameter vs TB, for V side
	MeanHistVTB
	mean of the residuals distribution vs TB, for V side
	MeanHistUTB
	mean of the residuals distribution vs TB, for U side
	RMSHistVTB
	RMS of the residuals distribution vs TB, for V side.
	RMSHistUTB
	RMS of the residuals distribution vs TB, for U side.
	MeanFitVTB
	mean of the residuals distribution vs TB, for V side (from gaussian fit)
	MeanFitUTB
	mean of the residuals distribution vs TB, for U side (from gaussian fit)
	RMSFitUTB
	RMS of the residuals distribution vs TB, for U side (from gaussian fit)
	RMSFitVTB
	RMS of the residuals distribution vs TB, for V side (from gaussian fit)
	gaus
	gaus function used for fitting distributions
	cdcEventT0
	registers PyStoreObj EventT0

Detailed Description

Python class used for evaluating the CoG corrections, create a localDB,
creating a localDB with the corrections and a root file to check the corrections

Definition at line 41 of file CoGCalibration_utils.py.

Member Function Documentation

event()

def event

(

self

)

Function that allows to cicle on the events

Definition at line 309 of file CoGCalibration_utils.py.

    def event(self):
        """
        Function that allows to cicle on the events
        """
        svd_evt_info = Belle2.PyStoreObj('SVDEventInfo')
        mode_byte = svd_evt_info.getModeByte()
        # timeClusterU = 0
        # timeClusterV = 0
        # sideIndex = 0
        # TBIndexU = 0
        # TBIndexV = 0
        
        self.Evt = self.Evt + 1
 
        
        self.cdcEventT0 = Belle2.PyStoreObj(cdc_Time0)
        svdCluster_list = Belle2.PyStoreArray(svd_Clusters)
        # svdRecoDigit_list = Belle2.PyStoreArray(svd_recoDigits)
 
        for svdCluster in svdCluster_list:
            # svdRecoDigit = svdCluster.getRelatedTo(svd_recoDigits)
            self.fillLists(mode_byte, svdCluster)
 

fillLists()

def fillLists	(		self,
			mode_byte_object,
			svdClusters_rel_RecoTracks_cl
	)

Function that fill the lists needed for the CoG corrections

parameters:
     mode_byte_object (modeByte): modeByte that contains the information about the TB
     svdClusters_rel_RecoTracks_cl (SVDCluster): cluster related to tracks

Definition at line 60 of file CoGCalibration_utils.py.

    def fillLists(self, mode_byte_object, svdClusters_rel_RecoTracks_cl):
        """
        Function that fill the lists needed for the CoG corrections
 
        parameters:
             mode_byte_object (modeByte): modeByte that contains the information about the TB
             svdClusters_rel_RecoTracks_cl (SVDCluster): cluster related to tracks
        """
 
        timeCluster = svdClusters_rel_RecoTracks_cl.getClsTime()
        snrCluster = svdClusters_rel_RecoTracks_cl.getSNR()
        layerCluster = svdClusters_rel_RecoTracks_cl.getSensorID().getLayerNumber()
        layerIndex = layerCluster - 3
        sensorCluster = svdClusters_rel_RecoTracks_cl.getSensorID().getSensorNumber()
        sensorIndex = sensorCluster - 1
        ladderCluster = svdClusters_rel_RecoTracks_cl.getSensorID().getLadderNumber()
        ladderIndex = ladderCluster - 1
        sideCluster = svdClusters_rel_RecoTracks_cl.isUCluster()
        if sideCluster:
            sideIndex = 1
        else:
            sideIndex = 0
 
        hasTimezero = self.cdcEventT0.hasEventT0()
        # print("Time: " + str(hasTimezero))
        if hasTimezero:
            TBClusters = mode_byte_object.getTriggerBin()
            TBIndex = ord(TBClusters)
            tZero = self.cdcEventT0.getEventT0()
            # tZero_err = self.cdcEventT0.getEventT0Uncertainty()
            # tZero_err = 5.1
            tZeroSync = tZero - 4000./509 * (3 - TBIndex)
            et0 = self.EventT0Hist
            et0.Fill(tZeroSync)
            # print(str(tZero_err))
 
            resHist = self.resList[layerIndex][ladderIndex][sensorIndex][sideIndex][TBIndex]
            resHist.Fill(timeCluster - tZeroSync)
            spHist = self.spList[layerIndex][ladderIndex][sensorIndex][sideIndex][TBIndex]
            # spHist.Fill(timeCluster, 1.3*timeCluster - 50 + random.gauss(0,10))
            spHist.Fill(timeCluster, tZeroSync)
            cogHist = self.cogList[layerIndex][ladderIndex][sensorIndex][sideIndex][TBIndex]
            cogHist.Fill(timeCluster)
            cdcHist = self.cdcList[layerIndex][ladderIndex][sensorIndex][sideIndex][TBIndex]
            cdcHist.Fill(tZeroSync)
            snrHist = self.snrList[layerIndex][ladderIndex][sensorIndex][sideIndex][TBIndex]
            snrHist.Fill(snrCluster)
 
            self.nList[layerIndex][ladderIndex][sensorIndex][sideIndex][TBIndex] += 1
            self.sumCOGList[layerIndex][ladderIndex][sensorIndex][sideIndex][TBIndex] += timeCluster
 
            
            self.NTOT = self.NTOT + 1
 

initialize()

def initialize

(

self

)

Initialize object (histograms, lists, ...) used by the class

Definition at line 124 of file CoGCalibration_utils.py.

    def initialize(self):
        """
        Initialize object (histograms, lists, ...) used by the class
        """
 
        
        self.outputFileName = "CoGCorrectionMonitor_" + self.localdb + ".root"
 
        
        self.resList = []
        
        self.spList = []
        
        self.cogList = []
        
        self.cdcList = []
        
        self.snrList = []
        
        self.nList = []
        
        self.sumCOGList = []
 
        geoCache = Belle2.VXD.GeoCache.getInstance()
 
        self.Evt = 0
        for layer in geoCache.getLayers(Belle2.VXD.SensorInfoBase.SVD):
            layerList0 = []
            layerList1 = []
            layerList2 = []
            layerList3 = []
            layerList4 = []
            layerList5 = []
            layerList6 = []
            layerList7 = []
            layerList8 = []
            self.resList.append(layerList0)
            self.spList.append(layerList1)
            self.cogList.append(layerList2)
            self.cdcList.append(layerList3)
            self.snrList.append(layerList4)
            self.nList.append(layerList8)
            self.sumCOGList.append(layerList7)
            # layerNumber = layer.getLayerNumber()
            for ladder in geoCache.getLadders(layer):
                ladderList0 = []
                ladderList1 = []
                ladderList2 = []
                ladderList3 = []
                ladderList4 = []
                ladderList5 = []
                ladderList6 = []
                ladderList7 = []
                ladderList8 = []
                layerList0.append(ladderList0)
                layerList1.append(ladderList1)
                layerList2.append(ladderList2)
                layerList3.append(ladderList3)
                layerList4.append(ladderList4)
                layerList5.append(ladderList5)
                layerList6.append(ladderList6)
                layerList7.append(ladderList7)
                layerList8.append(ladderList8)
                # ladderNumber = ladder.getLadderNumber()
                for sensor in geoCache.getSensors(ladder):
                    sensorList0 = []
                    sensorList1 = []
                    sensorList2 = []
                    sensorList3 = []
                    sensorList4 = []
                    sensorList5 = []
                    sensorList6 = []
                    sensorList7 = []
                    sensorList8 = []
                    ladderList0.append(sensorList0)
                    ladderList1.append(sensorList1)
                    ladderList2.append(sensorList2)
                    ladderList3.append(sensorList3)
                    ladderList4.append(sensorList4)
                    ladderList5.append(sensorList5)
                    ladderList6.append(sensorList6)
                    ladderList7.append(sensorList7)
                    ladderList8.append(sensorList8)
                    # sensorNumber = sensor.getSensorNumber()
                    for side in range(2):
                        sideList0 = []
                        sideList1 = []
                        sideList2 = []
                        sideList3 = []
                        sideList4 = []
                        sideList5 = []
                        sideList6 = []
                        sideList7 = []
                        sideList8 = []
                        sensorList0.append(sideList0)
                        sensorList1.append(sideList1)
                        sensorList2.append(sideList2)
                        sensorList3.append(sideList3)
                        sensorList4.append(sideList4)
                        sensorList5.append(sideList5)
                        sensorList6.append(sideList6)
                        sensorList7.append(sideList7)
                        sensorList8.append(sideList8)
 
        for i in geoCache.getLayers(Belle2.VXD.SensorInfoBase.SVD):
            layerN = i.getLayerNumber()
            li = layerN - 3
            for j in geoCache.getLadders(i):
                ladderN = j.getLadderNumber()
                ldi = ladderN - 1
                for k in geoCache.getSensors(j):
                    sensorN = k.getSensorNumber()
                    si = sensorN - 1
                    for s in range(2):
                        for t in range(4):
                            self.resList[li][ldi][si][s].append(
                                TH1F("res" + "_" + str(k) + "." + str(s) + "." + str(t), " ", 200, -100, 100))
                            self.spList[li][ldi][si][s].append(
                                TH2D("sp" + "_" + str(k) + "." + str(s) + "." + str(t), " ", 300, -150, 150, 300, -150, 150))
                            self.cogList[li][ldi][si][s].append(
                                TH1F("cog" + "_" + str(k) + "." + str(s) + "." + str(t), " ", 200, -100, 100))
                            self.cdcList[li][ldi][si][s].append(
                                TH1F("cdc" + "_" + str(k) + "." + str(s) + "." + str(t), " ", 200, -100, 100))
                            self.snrList[li][ldi][si][s].append(
                                TH1F("snr" + "_" + str(k) + "." + str(s) + "." + str(t), " ", 100, 0, 100))
                            self.nList[li][ldi][si][s].append(0)
                            self.sumCOGList[li][ldi][si][s].append(0)
        
        self.EventT0Hist = TH1F("EventT0", " ", 200, -100, 100)
        
        self.AlphaUTB = TH2F("alphaVsTB_U", " ", 400, 0.5, 2, 4, 0, 4)
        self.AlphaUTB.GetXaxis().SetTitle("alpha")
        self.AlphaUTB.GetYaxis().SetTitle("trigger bin")
        
        self.AlphaVTB = TH2F("alphaVsTB_V", " ", 400, 0.5, 2, 4, 0, 4)
        self.AlphaVTB.GetXaxis().SetTitle("alpha")
        self.AlphaVTB.GetYaxis().SetTitle("trigger bin")
        
        self.BetaUTB = TH2F("betaVsTB_U", " ", 200, -100, 100, 4, 0, 4)
        self.BetaUTB.GetXaxis().SetTitle("beta (ns)")
        self.BetaUTB.GetYaxis().SetTitle("trigger bin")
        
        self.BetaVTB = TH2F("betaVsTB_V", " ", 200, -100, 100, 4, 0, 4)
        self.BetaVTB.GetXaxis().SetTitle("beta (ns)")
        self.BetaVTB.GetYaxis().SetTitle("trigger bin")
 
        
        self.MeanHistVTB = TH2F("meanHistVsTB_V", " ", 100, -10, 10, 4, 0, 4)
        self.MeanHistVTB.GetXaxis().SetTitle("distribution mean (ns)")
        self.MeanHistVTB.GetYaxis().SetTitle("trigger bin")
        
        self.MeanHistUTB = TH2F("meanHistVsTB_U", " ", 100, -10, 10, 4, 0, 4)
        self.MeanHistUTB.GetXaxis().SetTitle("distribution mean (ns)")
        self.MeanHistUTB.GetYaxis().SetTitle("trigger bin")
        
        self.RMSHistVTB = TH2F("rmsHistVsTB_V", " ", 100, 0, 10, 4, 0, 4)
        self.RMSHistVTB.GetXaxis().SetTitle("distribution RMS (ns)")
        self.RMSHistVTB.GetYaxis().SetTitle("trigger bin")
        
        self.RMSHistUTB = TH2F("rmsHistVsTB_U", " ", 100, 0, 10, 4, 0, 4)
        self.RMSHistUTB.GetXaxis().SetTitle("distribution RMS (ns)")
        self.RMSHistUTB.GetYaxis().SetTitle("trigger bin")
        
        self.MeanFitVTB = TH2F("meanFitVsTB_V", " ", 100, -10, 10, 4, 0, 4)
        self.MeanFitVTB.GetXaxis().SetTitle("fit mean (ns)")
        self.MeanFitVTB.GetYaxis().SetTitle("trigger bin")
        
        self.MeanFitUTB = TH2F("meanFitVsTB_U", " ", 100, -10, 10, 4, 0, 4)
        self.MeanFitUTB.GetXaxis().SetTitle("fit mean (ns)")
        self.MeanFitUTB.GetYaxis().SetTitle("trigger bin")
        
        self.RMSFitUTB = TH2F("rmsFitVsTB_U", " ", 100, 0, 10, 4, 0, 4)
        self.RMSFitUTB.GetXaxis().SetTitle("fit sigma (ns)")
        self.RMSFitUTB.GetYaxis().SetTitle("trigger bin")
        
        self.RMSFitVTB = TH2F("rmsFitVsTB_V", " ", 100, 0, 10, 4, 0, 4)
        self.RMSFitVTB.GetXaxis().SetTitle("fit sigma (ns)")
        self.RMSFitVTB.GetYaxis().SetTitle("trigger bin")
 
        
        self.gaus = TF1("gaus", 'gaus(0)', -150, 100)
 
        self.NTOT = 0
 

notApplyCorrectForCDCLatency()

def notApplyCorrectForCDCLatency	(		self,
			mode
	)

Function that allows to set if apply the CDC latency correction

parameters:
     mode (bool):
     - if True -> not apply correction
     - if False -> apply correction

Definition at line 47 of file CoGCalibration_utils.py.

    def notApplyCorrectForCDCLatency(self, mode):
        """
        Function that allows to set if apply the CDC latency correction
 
        parameters:
             mode (bool):
             - if True -> not apply correction
             - if False -> apply correction
        """
        
        self.notApplyCDCLatencyCorrection = mode
        print("Not Correct for CDC latency: " + str(mode) + " " + str(self.notApplyCDCLatencyCorrection))
 

set_localdb()

def set_localdb	(		self,
			localDB
	)

Function that allows to set the localDB

parameters:
     localDB (str): Name of the localDB used

Definition at line 114 of file CoGCalibration_utils.py.

    def set_localdb(self, localDB):
        """
        Function that allows to set the localDB
 
        parameters:
             localDB (str): Name of the localDB used
        """
        
        self.localdb = localDB
 

terminate()

def terminate

(

self

)

Terminates te class and produces the output rootfile

Definition at line 332 of file CoGCalibration_utils.py.

    def terminate(self):
        """
        Terminates te class and produces the output rootfile
        """
 
        tfile = TFile(self.outputFileName, 'recreate')
        iov = Belle2.IntervalOfValidity.always()
 
        payload = Belle2.SVDCoGTimeCalibrations.t_payload()
 
        timeCal = SVDCoGCalibrationFunction()
        # Bias and Scale
        tbBias = [-50, -50, -50, -50]
        tbScale = [1, 1, 1, 1]
        tbBias_err = [1, 1, 1, 1]
        tbScale_err = [1, 1, 1, 1]
        # tbCovScaleBias = [1, 1, 1, 1]
 
        TCOGMEAN = 0
        T0MEAN = 0
 
        '''
        geoCache = Belle2.VXD.GeoCache.getInstance()
        for layer in geoCache.getLayers(Belle2.VXD.SensorInfoBase.SVD):
            layerNumber = layer.getLayerNumber()
            li = layerNumber - 3
            for ladder in geoCache.getLadders(layer):
                ladderNumber = ladder.getLadderNumber()
                ldi = ladderNumber - 1
                for sensor in geoCache.getSensors(ladder):
                    sensorNumber = sensor.getSensorNumber()
                    si = sensorNumber - 1
                    for side in range(2):
                        for tb in range(4):
                            n = self.nList[li][ldi][si][side][tb]
                            NTOT += n
        '''
        geoCache = Belle2.VXD.GeoCache.getInstance()
        gDirectory.mkdir("plots")
        gDirectory.cd("plots")
        for layer in geoCache.getLayers(Belle2.VXD.SensorInfoBase.SVD):
            layerNumber = layer.getLayerNumber()
            li = layerNumber - 3
            gDirectory.mkdir("layer" + str(layer))
            gDirectory.cd("layer" + str(layer))
            for ladder in geoCache.getLadders(layer):
                ladderNumber = ladder.getLadderNumber()
                ldi = ladderNumber - 1
                for sensor in geoCache.getSensors(ladder):
                    sensorNumber = sensor.getSensorNumber()
                    si = sensorNumber - 1
                    for side in range(2):
                        for tb in range(4):
                            # Resolution distribution Histograms with Gaussian Fit
                            res = self.resList[li][ldi][si][side][tb]
                            fitResult = int(TFitResultPtr(res.Fit(self.gaus, "R")))
 
                            if res.GetEntries() > 5:
                                if side == 1:
                                    self.MeanHistUTB.Fill(res.GetMean(), tb)
                                    self.RMSHistUTB.Fill(res.GetRMS(), tb)
                                    if fitResult > -1:
                                        self.MeanFitUTB.Fill(self.gaus.GetParameter(1), tb)
                                        self.RMSFitUTB.Fill(self.gaus.GetParameter(2), tb)
                                else:
                                    self.MeanHistVTB.Fill(res.GetMean(), tb)
                                    self.RMSHistVTB.Fill(res.GetRMS(), tb)
                                    if fitResult > -1:
                                        self.MeanFitVTB.Fill(self.gaus.GetParameter(1), tb)
                                        self.RMSFitVTB.Fill(self.gaus.GetParameter(2), tb)
 
                            res.Write()
                            # COG Distribution Histograms
                            cog = self.cogList[li][ldi][si][side][tb]
                            cog.Write()
                            # CDC EventT0 Distribution Histograms
                            cdc = self.cdcList[li][ldi][si][side][tb]
                            cdc.Write()
                            # SNR Distribution Histograms
                            snr = self.snrList[li][ldi][si][side][tb]
                            # snrMean = snr.GetMean()
                            snr.Write()
                            # ScatterPlot Histograms with Linear Fit
                            sp = self.spList[li][ldi][si][side][tb]
                            # covscalebias = sp.GetCovariance()
                            pfxsp = sp.ProfileX()
                            sp.Write()
                            pfxsp.Write()
 
                            if sp.GetRMS() != 0:
                                m = sp.GetCovariance() / pow(sp.GetRMS(1), 2)
                                # m = sp.GetCovariance()/cog.GetRMS()
                                m_err = 2 / pow(sp.GetRMS(), 3) * sp.GetRMSError() * sp.GetCovariance()
                                q = sp.GetMean(2) - m * sp.GetMean(1)
                                q_err = math.sqrt(pow(sp.GetMeanError(2), 2) +
                                                  pow(m * sp.GetMeanError(1), 2) + pow(m_err * sp.GetMean(1), 2))
                            else:
                                m = 1
                                m_err = 0
                                q = 0
                                q_err = 0
 
                            if side == 1:
                                self.AlphaUTB.Fill(m, tb)
                                self.BetaUTB.Fill(q, tb)
                            else:
                                self.AlphaVTB.Fill(m, tb)
                                self.BetaVTB.Fill(q, tb)
 
                            n = self.nList[li][ldi][si][side][tb]
 
                            tbBias[tb] = q
                            tbScale[tb] = m
                            tbBias_err[tb] = q_err
                            tbScale_err[tb] = m_err
                            TCOGMEAN += n * (m * self.sumCOGList[li][ldi][si][side][tb] / n + q) / self.NTOT
 
                        T0MEAN = self.EventT0Hist.GetMean()
                        '''
                        print(
                            "Mean of the CoG corrected distribution: " +
                            str(TCOGMEAN) +
                            " Mean of the T0 distribution: " +
                            str(T0MEAN))
                        '''
                        if not self.notApplyCDCLatencyCorrection:
                            tbBias[0] = tbBias[0] - T0MEAN
                            tbBias[1] = tbBias[1] - T0MEAN
                            tbBias[2] = tbBias[2] - T0MEAN
                            tbBias[3] = tbBias[3] - T0MEAN
 
                        timeCal.set_bias(tbBias[0], tbBias[1], tbBias[2], tbBias[3])
                        timeCal.set_scale(tbScale[0], tbScale[1], tbScale[2], tbScale[3])
                        print("setting CoG calibration for " + str(layerNumber) + "." + str(ladderNumber) + "." + str(sensorNumber))
                        payload.set(layerNumber, ladderNumber, sensorNumber, bool(side), 1, timeCal)
            gDirectory.cd("../")
 
        gDirectory.cd("../")
        self.AlphaUTB.Write()
        self.AlphaVTB.Write()
        self.BetaUTB.Write()
        self.BetaVTB.Write()
        self.MeanFitUTB.Write()
        self.MeanFitVTB.Write()
        self.RMSFitUTB.Write()
        self.RMSFitVTB.Write()
        self.MeanHistUTB.Write()
        self.MeanHistVTB.Write()
        self.RMSHistUTB.Write()
        self.RMSHistVTB.Write()
        self.EventT0Hist.Write()
 
        Belle2.Database.Instance().storeData(Belle2.SVDCoGTimeCalibrations.name, payload, iov)
 
        tfile.Close()

Member Data Documentation

AlphaUTB

AlphaUTB

alpha parameter vs TB, for U side

Definition at line 255 of file CoGCalibration_utils.py.

AlphaVTB

AlphaVTB

alpha parameter vs TB, for V side

Definition at line 259 of file CoGCalibration_utils.py.

BetaUTB

BetaUTB

beta parameter vs TB, for U side

Definition at line 263 of file CoGCalibration_utils.py.

BetaVTB

BetaVTB

beta parameter vs TB, for V side

Definition at line 267 of file CoGCalibration_utils.py.

cdcEventT0

cdcEventT0

registers PyStoreObj EventT0

Definition at line 324 of file CoGCalibration_utils.py.

cdcList

cdcList

t0

Definition at line 140 of file CoGCalibration_utils.py.

cogList

cogList

cog

Definition at line 138 of file CoGCalibration_utils.py.

EventT0Hist

EventT0Hist

distribution of EventT0

Definition at line 253 of file CoGCalibration_utils.py.

Evt

Evt

counts the number of events

Definition at line 150 of file CoGCalibration_utils.py.

gaus

gaus

gaus function used for fitting distributions

Definition at line 305 of file CoGCalibration_utils.py.

localdb

localdb

set the name of the localDB used

Definition at line 122 of file CoGCalibration_utils.py.

MeanFitUTB

MeanFitUTB

mean of the residuals distribution vs TB, for U side (from gaussian fit)

Definition at line 292 of file CoGCalibration_utils.py.

MeanFitVTB

MeanFitVTB

mean of the residuals distribution vs TB, for V side (from gaussian fit)

Definition at line 288 of file CoGCalibration_utils.py.

MeanHistUTB

MeanHistUTB

mean of the residuals distribution vs TB, for U side

Definition at line 276 of file CoGCalibration_utils.py.

MeanHistVTB

MeanHistVTB

mean of the residuals distribution vs TB, for V side

Definition at line 272 of file CoGCalibration_utils.py.

nList

nList

number of clusters

Definition at line 144 of file CoGCalibration_utils.py.

notApplyCDCLatencyCorrection

notApplyCDCLatencyCorrection

parameter that allows to apply or not the CDC latency correction

Definition at line 57 of file CoGCalibration_utils.py.

NTOT

NTOT

counts the number of clusters

Definition at line 112 of file CoGCalibration_utils.py.

outputFileName

outputFileName

name of the output file

Definition at line 130 of file CoGCalibration_utils.py.

resList

resList

lists used to create the histograms for each TB : residuals

Definition at line 134 of file CoGCalibration_utils.py.

RMSFitUTB

RMSFitUTB

RMS of the residuals distribution vs TB, for U side (from gaussian fit)

Definition at line 296 of file CoGCalibration_utils.py.

RMSFitVTB

RMSFitVTB

RMS of the residuals distribution vs TB, for V side (from gaussian fit)

Definition at line 300 of file CoGCalibration_utils.py.

RMSHistUTB

RMSHistUTB

RMS of the residuals distribution vs TB, for U side.

Definition at line 284 of file CoGCalibration_utils.py.

RMSHistVTB

RMSHistVTB

RMS of the residuals distribution vs TB, for V side.

Definition at line 280 of file CoGCalibration_utils.py.

snrList

snrList

Cluster SNR.

Definition at line 142 of file CoGCalibration_utils.py.

spList

spList

scatterplot t0 vs cog

Definition at line 136 of file CoGCalibration_utils.py.

sumCOGList

sumCOGList

sum of CoG times

Definition at line 146 of file CoGCalibration_utils.py.

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The documentation for this class was generated from the following file:

• svd/scripts/svd/CoGCalibration_utils.py