SVDValidationTTreeCluster Class Reference

Inheritance diagram for SVDValidationTTreeCluster:

Public Member Functions
def	__init__ (self)
def	event (self)
def	terminate (self)

Public Attributes
	file
	Output ROOT file.
	tree
	TTree for output data.
	data
	instance of EventData class

Detailed Description

class to produce the ttree for cluster reconstruction validation

Definition at line 71 of file SVDValidationTTreeCluster.py.

Constructor & Destructor Documentation

__init__()

def __init__

(

self

)

Initialize the module

Definition at line 74 of file SVDValidationTTreeCluster.py.

    def __init__(self):
        """Initialize the module"""
 
        super().__init__()
 
        
        self.file = ROOT.TFile('../SVDValidationTTreeCluster.root', 'recreate')
        
        self.tree = ROOT.TTree('tree', 'Event data of SVD validation events')
        
        self.data = EventDataCluster()
 
        # Declare tree branches
        for key in EventDataCluster.__dict__:
            if '__' not in key:
                formstring = '/F'
                if isinstance(self.data.__getattribute__(key), int):
                    formstring = '/I'
                self.tree.Branch(key, addressof(self.data, key), key + formstring)
 

Member Function Documentation

event()

def event

(

self

)

 Find clusters with a truehit and save needed information 

Definition at line 94 of file SVDValidationTTreeCluster.py.

    def event(self):
        """ Find clusters with a truehit and save needed information """
        clusters = Belle2.PyStoreArray('SVDClusters')
        eventt0 = Belle2.PyStoreObj('EventT0')
 
        # get EventT0: combined, TOP, CDC, ECL
        self.data.eventt0_all = -1
        self.data.eventt0_top = -1
        self.data.eventt0_cdc = -1
        self.data.eventt0_ecl = -1
        self.data.eventt0_svd = -1
        top = Belle2.Const.DetectorSet(Belle2.Const.TOP)
        cdc = Belle2.Const.DetectorSet(Belle2.Const.CDC)
        ecl = Belle2.Const.DetectorSet(Belle2.Const.ECL)
        svd = Belle2.Const.DetectorSet(Belle2.Const.SVD)
        if eventt0.hasEventT0():
            self.data.eventt0_all = eventt0.getEventT0()
        if eventt0.hasTemporaryEventT0(svd):
            tmp = eventt0.getTemporaryEventT0s(Belle2.Const.SVD)
            self.data.eventt0_svd = tmp.back().eventT0
        if eventt0.hasTemporaryEventT0(cdc):
            tmp = eventt0.getTemporaryEventT0s(Belle2.Const.CDC)
            self.data.eventt0_cdc = tmp.back().eventT0
        if eventt0.hasTemporaryEventT0(top):
            tmp = eventt0.getTemporaryEventT0s(Belle2.Const.TOP)
            self.data.eventt0_top = tmp.back().eventT0
        if eventt0.hasTemporaryEventT0(ecl):
            evtT0List_ECL = eventt0.getTemporaryEventT0s(Belle2.Const.ECL)
            # Select the event t0 value from the ECL as the one with the smallest chi squared value (defined as ".quality")
            smallest_ECL_t0_minChi2 = evtT0List_ECL[0].quality
            self.data.eventt0_ecl = evtT0List_ECL[0].eventT0
            for tmp in evtT0List_ECL:
                if tmp.quality < smallest_ECL_t0_minChi2:
                    smallest_ECL_t0_minChi2 = tmp.quality
                    self.data.eventt0_ecl = tmp.eventT0
 
        for cluster in clusters:
 
            cluster_truehits = cluster.getRelationsTo('SVDTrueHits')
 
            # Sensor identification
            sensorInfo = Belle2.VXD.GeoCache.getInstance().getSensorInfo(cluster.getSensorID())
            sensorID = cluster.getSensorID()
            self.data.sensor_id = int(sensorID)
            sensorNum = sensorID.getSensorNumber()
            self.data.sensor = sensorNum
            layerNum = sensorID.getLayerNumber()
            self.data.layer = layerNum
            if (layerNum == 3):
                sensorType = 1
            else:
                if (sensorNum == 1):
                    sensorType = 0
                else:
                    sensorType = 1
            self.data.sensor_type = sensorType
            ladderNum = sensorID.getLadderNumber()
            self.data.ladder = ladderNum
            if cluster.isUCluster():
                strip_dir = 0
            else:
                strip_dir = 1
 
            self.data.matched = 1
            # We want only clusters with at least one associated TrueHit
            # but, to compute purity, we need to store also some information
            # for clusters not related to true hits
            if len(cluster_truehits) == 0:
                self.data.matched = 0
                # Fill tree
                self.file.cd()
                self.tree.Fill()
                continue
 
            # find the trueHit with highest energy deposit (the "best" match)
            energy = 0
            bestTrueHitIndex = 0
            for i, trueHit in enumerate(cluster_truehits):
                if trueHit.getEnergyDep() > energy:
                    energy = trueHit.getEnergyDep()
                    bestTrueHitIndex = i
            bestTrueHit = cluster_truehits[bestTrueHitIndex]
 
            # Cluster information
            self.data.cluster_clsTime = cluster.getClsTime()
            self.data.cluster_clsTimeSigma = cluster.getClsTimeSigma()
            self.data.cluster_charge = cluster.getCharge()
            self.data.cluster_seedCharge = cluster.getSeedCharge()
            self.data.cluster_size = cluster.getSize()
            self.data.cluster_snr = cluster.getSNR()
            cluster_position = cluster.getPosition()
            if cluster.isUCluster():
                cluster_position = cluster.getPosition(bestTrueHit.getV())
                # Interstrip position calculations
                strip_pitch = sensorInfo.getUPitch(bestTrueHit.getV())
            else:
                strip_pitch = sensorInfo.getVPitch(bestTrueHit.getU())
            self.data.strip_dir = strip_dir
            self.data.strip_pitch = strip_pitch
            self.data.cluster_interstripPosition = cluster_position % strip_pitch / strip_pitch
            # theta and phi definitions
            if cluster.isUCluster():
                uPos = cluster_position
                vPos = 0
            else:
                uPos = 0
                vPos = cluster_position
            localPosition = Math.XYZVector(uPos, vPos, 0)  # sensor center at (0, 0, 0)
            globalPosition = sensorInfo.pointToGlobal(localPosition, True)
            x = globalPosition.X()
            y = globalPosition.Y()
            z = globalPosition.Z()
            # see https://d2comp.kek.jp/record/242?ln=en for the Belle II
            # coordinate system and related variables
            rho = math.sqrt(x * x + y * y)
            r = math.sqrt(x * x + y * y + z * z)
            # get theta as arccosine(z/r)
            thetaRadians = math.acos(z / r)
            theta = (thetaRadians * 180) / math.pi
            # get phi as arccosine(x/rho)
            phiRadians = math.acos(x / rho)
            if y < 0:
                phi = 360 - (phiRadians * 180) / math.pi
            else:
                phi = (phiRadians * 180) / math.pi
            self.data.cluster_theta = theta
            self.data.cluster_phi = phi
            # Pull calculations
            clusterPos = cluster_position
            clusterPosSigma = cluster.getPositionSigma()
            if cluster.isUCluster():
                truehitPos = bestTrueHit.getU()
            else:
                truehitPos = bestTrueHit.getV()
            cluster_residual = clusterPos - truehitPos
            cluster_pull = cluster_residual / clusterPosSigma
            self.data.cluster_position = clusterPos
            self.data.cluster_positionSigma = clusterPosSigma
            self.data.cluster_residual = cluster_residual
            self.data.cluster_pull = cluster_pull
            # Truehit information
            self.data.truehit_position = truehitPos
            truehit_interstripPosition = truehitPos % strip_pitch / strip_pitch
            self.data.truehit_interstripPosition = truehit_interstripPosition
            self.data.truehit_deposEnergy = bestTrueHit.getEnergyDep()
            self.data.truehit_lossmomentum = bestTrueHit.getEntryMomentum().R() - bestTrueHit.getExitMomentum().R()
            self.data.truehit_time = bestTrueHit.getGlobalTime()
 
            # DEBUG options, commented out
            # print("\n new cluster with at least one true hit ("+str(len(cluster_truehits))+")")
            # print("best True hit has energy = "+str(bestTrueHit.getEnergyDep()*1e6)+" eV,\
            # global time = "+str(bestTrueHit.getGlobalTime()))
            # print("cluster isU = "+str(cluster.isUCluster())+", size = "+str(self.data.cluster_size)+"\
            # position = "+str(clusterPos))
            # print("cluster charge = "+str(self.data.cluster_charge)+", time = "+str(self.data.cluster_clsTime))
 
            # Fill tree
            self.file.cd()
            self.tree.Fill()
 

terminate()

def terminate

(

self

)

Close the output file. 

Definition at line 254 of file SVDValidationTTreeCluster.py.

    def terminate(self):
        """Close the output file. """
        self.file.cd()
        self.file.Write()
        self.file.Close()

Member Data Documentation

data

data

instance of EventData class

Definition at line 84 of file SVDValidationTTreeCluster.py.

file

file

Output ROOT file.

Definition at line 80 of file SVDValidationTTreeCluster.py.

tree

tree

TTree for output data.

Definition at line 82 of file SVDValidationTTreeCluster.py.

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

• svd/validation/SVDValidationTTreeCluster.py