Inheritance diagram for PXDPositionEstimation:

Collaboration diagram for PXDPositionEstimation:

Public Member Functions
def	initialize (self)

def	event (self)

def	terminate (self)

Public Attributes
	nclusters
	Counter for all clusters.

	nfound_shapes
	Counter for cluster where shape likelyhood was found in payload.

	nfound_offset
	Counter for clusters where position correction was found in payload.

	rfile
	Output file to store all plots.

	hist_map_momentum
	Histograms for true particle momenta.

	hist_map_theta_u
	Histograms for true particle angle thetaU.

	hist_map_theta_v
	Histograms for true particle angle thetaV.

	hist_map_clustercharge
	Histograms for cluster charge related to particle.

	hist_map_residual_u
	Histograms for u residuals.

	hist_map_residual_v
	Histograms for v residuals.

	hist_map_residual_v_special
	Histograms for v residuals for smaller thetaV range.

	hist_map_residual_pull_u
	Histograms for u residual pulls.

	hist_map_residual_pull_v
	Histograms for v residual pulls.

	binlimits
	ThetaV angle ranges for v residuals.

Detailed Description

Histogram the difference position residuals and pulls between clusters and truehits.

Definition at line 26 of file test_cluster_position_estimator.py.

Member Function Documentation

◆ event()

def event ( self )

Fill the residual and pull histograms

Definition at line 106 of file test_cluster_position_estimator.py.

    def event(self):
        """Fill the residual and pull histograms"""
 
        # Get truehits
        truehits = Belle2.PyStoreArray("PXDTrueHits")
 
        for truehit in truehits:
            if isinstance(truehit, Belle2.PXDTrueHit):
                sensor_info = Belle2.VXD.GeoCache.get(truehit.getSensorID())
                clusters = truehit.getRelationsFrom("PXDClusters")
 
                # now check if we find a cluster
                for j, cls in enumerate(clusters):
                    # we ignore all clusters where less then 100 electrons come from
                    # our truehit
                    if clusters.weight(j) < 100:
                        continue
 
                    mom = truehit.getMomentum()
                    tu = mom[0] / mom[2]
                    tv = mom[1] / mom[2]
                    thetaU = math.atan(tu) * 180 / math.pi
                    thetaV = math.atan(tv) * 180 / math.pi
 
                    # Only look at primary particles -> check if the following is needed
                    # for mcp in truehit.getRelationsFrom("MCParticles"):
                    #    if not mcp.hasStatus(1):
                    #        reject = True
 
                    # Get instance of position estimator
                    PositionEstimator = Belle2.PXD.PXDClusterPositionEstimator.getInstance()
                    clusterkind = cls.getKind()
 
                    # Clusterkinds 0,1,2,3 refer to all cases which can currently
                    # be corrected. Cases where a cluster pixel touches a sensor
                    # edge or contains pixel with varying vPitch are excluded here.
                    if clusterkind <= 3 and mom.Mag() > 0.02:
 
                        self.nclusters += 1
 
                        # Fill momentum and angles for clusterkind
                        self.hist_map_momentum[clusterkind].Fill(mom.Mag())
                        self.hist_map_theta_u[clusterkind].Fill(thetaU)
                        self.hist_map_theta_v[clusterkind].Fill(thetaV)
                        self.hist_map_clustercharge[clusterkind].Fill(cls.getCharge())
 
                        # Fill clusterkind=4 for all PXD sensors
                        self.hist_map_momentum[4].Fill(mom.Mag())
                        self.hist_map_theta_u[4].Fill(thetaU)
                        self.hist_map_theta_v[4].Fill(thetaV)
                        self.hist_map_clustercharge[4].Fill(cls.getCharge())
 
                        # Fill the histograms (mode=2)
                        mode = 2
                        pull_u = (truehit.getU() - cls.getU()) / cls.getUSigma()
                        pull_v = (truehit.getV() - cls.getV()) / cls.getVSigma()
 
                        self.hist_map_residual_u[(clusterkind, mode)].Fill(truehit.getU() - cls.getU())
                        self.hist_map_residual_v[(clusterkind, mode)].Fill(truehit.getV() - cls.getV())
                        self.hist_map_residual_pull_u[(clusterkind, mode)].Fill(pull_u)
                        self.hist_map_residual_pull_v[(clusterkind, mode)].Fill(pull_v)
 
                        if thetaV >= self.binlimits[0][0] and thetaV < self.binlimits[0][1]:
                            self.hist_map_residual_v_special[(clusterkind, mode, 0)].Fill(truehit.getV() - cls.getV())
                        elif thetaV >= self.binlimits[1][0] and thetaV < self.binlimits[1][1]:
                            self.hist_map_residual_v_special[(clusterkind, mode, 1)].Fill(truehit.getV() - cls.getV())
                        else:
                            self.hist_map_residual_v_special[(clusterkind, mode, 2)].Fill(truehit.getV() - cls.getV())
 
                        shape_likelyhood = PositionEstimator.getShapeLikelyhood(cls, tu, tv)
                        if shape_likelyhood > 0:
                            self.nfound_shapes += 1
 
                        offset = PositionEstimator.getClusterOffset(cls, tu, tv)
                        if offset:
                            # Now, we can safely querry the correction
                            self.nfound_offset += 1
 
                            # We need to explicitely add a shift to the offsets
                            # This is not needed when working with PXDRecoHits
                            shiftU = sensor_info.getUCellPosition(cls.getUStart())
                            shiftV = sensor_info.getVCellPosition(cls.getVStart())
 
                            # Fill the histograms (mode=0)
                            mode = 0
                            pull_u = (truehit.getU() - shiftU - offset.getU()) / (math.sqrt(offset.getUSigma2()))
                            pull_v = (truehit.getV() - shiftV - offset.getV()) / (math.sqrt(offset.getVSigma2()))
 
                            self.hist_map_residual_u[(clusterkind, mode)].Fill(truehit.getU() - shiftU - offset.getU())
                            self.hist_map_residual_v[(clusterkind, mode)].Fill(truehit.getV() - shiftV - offset.getV())
                            self.hist_map_residual_pull_u[(clusterkind, mode)].Fill(pull_u)
                            self.hist_map_residual_pull_v[(clusterkind, mode)].Fill(pull_v)
 
                            if thetaV >= self.binlimits[0][0] and thetaV < self.binlimits[0][1]:
                                self.hist_map_residual_v_special[(clusterkind, mode, 0)].Fill(
                                    truehit.getV() - shiftV - offset.getV())
                            elif thetaV >= self.binlimits[1][0] and thetaV < self.binlimits[1][1]:
                                self.hist_map_residual_v_special[(clusterkind, mode, 1)].Fill(
                                    truehit.getV() - shiftV - offset.getV())
                            else:
                                self.hist_map_residual_v_special[(clusterkind, mode, 2)].Fill(
                                    truehit.getV() - shiftV - offset.getV())
 
                            # Fill the histograms (mode=1)
                            mode = 1
                            self.hist_map_residual_u[(clusterkind, mode)].Fill(truehit.getU() - shiftU - offset.getU())
                            self.hist_map_residual_v[(clusterkind, mode)].Fill(truehit.getV() - shiftV - offset.getV())
                            self.hist_map_residual_pull_u[(clusterkind, mode)].Fill(pull_u)
                            self.hist_map_residual_pull_v[(clusterkind, mode)].Fill(pull_v)
 
                            if thetaV >= self.binlimits[0][0] and thetaV < self.binlimits[0][1]:
                                self.hist_map_residual_v_special[(clusterkind, mode, 0)].Fill(
                                    truehit.getV() - shiftV - offset.getV())
                            elif thetaV >= self.binlimits[1][0] and thetaV < self.binlimits[1][1]:
                                self.hist_map_residual_v_special[(clusterkind, mode, 1)].Fill(
                                    truehit.getV() - shiftV - offset.getV())
                            else:
                                self.hist_map_residual_v_special[(clusterkind, mode, 2)].Fill(
                                    truehit.getV() - shiftV - offset.getV())
 
                        else:
 
                            # Fill the histograms (mode=1)
                            mode = 1
                            pull_u = (truehit.getU() - cls.getU()) / cls.getUSigma()
                            pull_v = (truehit.getV() - cls.getV()) / cls.getVSigma()
 
                            self.hist_map_residual_u[(clusterkind, mode)].Fill(truehit.getU() - cls.getU())
                            self.hist_map_residual_v[(clusterkind, mode)].Fill(truehit.getV() - cls.getV())
                            self.hist_map_residual_pull_u[(clusterkind, mode)].Fill(pull_u)
                            self.hist_map_residual_pull_v[(clusterkind, mode)].Fill(pull_v)
 
                            if thetaV >= self.binlimits[0][0] and thetaV < self.binlimits[0][1]:
                                self.hist_map_residual_v_special[(clusterkind, mode, 0)].Fill(truehit.getV() - cls.getV())
                            elif thetaV >= self.binlimits[1][0] and thetaV < self.binlimits[1][1]:
                                self.hist_map_residual_v_special[(clusterkind, mode, 1)].Fill(truehit.getV() - cls.getV())
                            else:
                                self.hist_map_residual_v_special[(clusterkind, mode, 2)].Fill(truehit.getV() - cls.getV())
 

◆ initialize()

def initialize ( self )

Create histograms for pulls and residuals

Definition at line 31 of file test_cluster_position_estimator.py.

    def initialize(self):
        """
        Create histograms for pulls and residuals
        """
 
        
        self.nclusters = 0
        
        self.nfound_shapes = 0
        
        self.nfound_offset = 0
 
        # Let's create a root file to store all profiles
        
        self.rfile = ROOT.TFile("PXDPositionEstimation.root", "RECREATE")
        self.rfile.cd()
 
        
        self.hist_map_momentum = {}
        
        self.hist_map_theta_u = {}
        
        self.hist_map_theta_v = {}
        
        self.hist_map_clustercharge = {}
 
        # Loop over clusterkinds (=4 means 'all' kinds)
        for kind in range(5):
            self.hist_map_momentum[kind] = ROOT.TH1F(f"hist_momentum_kind_{kind:d}",
                                                     f'Particle momentum kind={kind:d}', 5000, 0.0, 10.0)
            self.hist_map_theta_u[kind] = ROOT.TH1F(f"hist_theta_u_kind_{kind:d}",
                                                    f'Particle angle thetaU kind={kind:d}', 180, -90, +90)
            self.hist_map_theta_v[kind] = ROOT.TH1F(f"hist_theta_v_kind_{kind:d}",
                                                    f'Particle angle thetaV kind={kind:d}', 180, -90, +90)
            self.hist_map_clustercharge[kind] = ROOT.TH1F(f"hist_clustercharge_kind_{kind:d}",
                                                          f'Cluster charge kind={kind:d}', 255, 0.0, 255.0)
 
        
        self.hist_map_residual_u = {}
        
        self.hist_map_residual_v = {}
        
        self.hist_map_residual_v_special = {}
        
        self.hist_map_residual_pull_u = {}
        
        self.hist_map_residual_pull_v = {}
 
        for kind in range(4):
            for mode in range(3):
                self.hist_map_residual_u[(kind, mode)] = ROOT.TH1F(f'hist_map_residual_u_kind_{kind:d}_mode_{mode:d}',
                                                                   f'PXD residual U kind={kind:d} mode={mode:d}',
                                                                   400, -0.007, +0.007)
                self.hist_map_residual_v[(kind, mode)] = ROOT.TH1F(f'hist_map_residual_v_kind_{kind:d}_mode_{mode:d}',
                                                                   f'PXD residual V kind={kind:d} mode={mode:d}',
                                                                   400, -0.007, +0.007)
                self.hist_map_residual_pull_u[(kind, mode)] = ROOT.TH1F(f'hist_map_residual_pull_u_kind_{kind:d}_mode_{mode:d}',
                                                                        f'PXD residual pull U kind={kind:d} mode={mode:d}',
                                                                        200, -10, +10)
                self.hist_map_residual_pull_v[(kind, mode)] = ROOT.TH1F(f'hist_map_residual_pull_v_kind_{kind:d}_mode_{mode:d}',
                                                                        f'PXD residual pull V kind={kind:d} mode={mode:d}',
                                                                        200, -10, +10)
 
                
                self.binlimits = {}
                self.binlimits[0] = (-90, -30)
                self.binlimits[1] = (-30, +30)
                self.binlimits[2] = (+30, +90)
 
                for bin in range(3):
                    name = f'hist_map_residual_v_kind_{kind:d}_mode_{mode:d}_special_{bin:d}'
                    title = f'PXD residual V kind={kind:d} mode={mode:d} {self.binlimits[bin][0]:.0f}' + \
                        f'<thetaV<{self.binlimits[bin][1]:.0f}'
                    self.hist_map_residual_v_special[(kind, mode, bin)] = ROOT.TH1F(name, title, 400, -0.007, +0.007)
 

◆ terminate()

def terminate ( self )

Format and write all histograms and plot them

Definition at line 245 of file test_cluster_position_estimator.py.

    def terminate(self):
        """
        Format and write all histograms and plot them
        """
 
        for kind in range(5):
            self.hist_map_momentum[kind].SetLineWidth(2)
            self.hist_map_momentum[kind].SetXTitle('momentum / GeV')
            self.hist_map_momentum[kind].SetYTitle('number of particles')
 
            self.hist_map_theta_u[kind].SetLineWidth(2)
            self.hist_map_theta_u[kind].SetXTitle('thetaU / degree')
            self.hist_map_theta_u[kind].SetYTitle('number of particles')
 
            self.hist_map_theta_v[kind].SetLineWidth(2)
            self.hist_map_theta_v[kind].SetXTitle('thetaV / degree')
            self.hist_map_theta_v[kind].SetYTitle('number of particles')
 
            self.hist_map_clustercharge[kind].SetLineWidth(2)
            self.hist_map_clustercharge[kind].SetXTitle('cluster charge / ADU')
            self.hist_map_clustercharge[kind].SetYTitle('number of particles')
 
        for kind in range(4):
            for mode in range(3):
                self.hist_map_residual_pull_u[(kind, mode)].SetLineWidth(2)
                self.hist_map_residual_pull_u[(kind, mode)].SetXTitle('pull u')
                self.hist_map_residual_pull_u[(kind, mode)].SetYTitle('number of particles')
 
                self.hist_map_residual_pull_v[(kind, mode)].SetLineWidth(2)
                self.hist_map_residual_pull_v[(kind, mode)].SetXTitle('pull v')
                self.hist_map_residual_pull_v[(kind, mode)].SetYTitle('number of particles')
 
                self.hist_map_residual_u[(kind, mode)].SetLineWidth(2)
                self.hist_map_residual_u[(kind, mode)].SetXTitle('residuals u / cm')
                self.hist_map_residual_u[(kind, mode)].SetYTitle('number of particles')
 
                self.hist_map_residual_v[(kind, mode)].SetLineWidth(2)
                self.hist_map_residual_v[(kind, mode)].SetXTitle('residuals v / cm')
                self.hist_map_residual_v[(kind, mode)].SetYTitle('number of particles')
 
                for bin in range(3):
                    self.hist_map_residual_v_special[(kind, mode, bin)].SetLineWidth(2)
                    self.hist_map_residual_v_special[(kind, mode, bin)].SetXTitle('residuals v / cm')
                    self.hist_map_residual_v_special[(kind, mode, bin)].SetYTitle('number of particles')
 
        hcoverage = ROOT.TH1F("hist_coverage", 'Coverage of corrections', 2, 1, 2)
        hcoverage.SetBinContent(1, 100.0 * float(self.nfound_offset / self.nclusters))
        hcoverage.SetBinContent(2, 100.0 * float(self.nfound_shapes / self.nclusters))
        hcoverage.SetLineWidth(2)
        hcoverage.SetYTitle('coverage / %')
        hcoverage.SetTitle('Coverage of cluster shape corrections')
 
        print(f"Coverage of cluster shape corrections is {100.0 * float(self.nfound_offset / self.nclusters):.2f}% ")
        print(f"Coverage of cluster shape likelyhoods is {100.0 * float(self.nfound_shapes / self.nclusters):.2f}% ")
 
        self.rfile.Write()
        self.rfile.Close()
 
 