Inheritance diagram for Ana:

Public Member Functions
def	initialize (self)

def	event (self)

def	terminate (self)

Public Attributes
	event_info
	EventMetaData.

	mc
	MCParticles.

	finder_trk2d
	TRGCDC2DFinderTracks.

	fast_finder_trk2d
	TRGCDC2DFinderFastTracks.

	trk2d
	TRGCDC2DFitterTracks.

	fast_trk2d
	TRGCDC2DFitterFastTracks.

	trk3d
	TRGCDC3DFitterTracks.

	fast_trk3d
	TRGCDC3DFitterFastTracks.

	trknt
	TRGCDCNeuroTracks.

	fast_trknt
	TRGCDCNeuroFastTracks.

	n2d_finder
	number of TRGCDC2DFinderTracks

	n2d_fast_finder
	number of TRGCDC2DFinderFastTracks

	n2d_fitter
	number of TRGCDC2DFitterTracks

	n2d_fast_fitter
	number of TRGCDC2DFitterFastTracks

	n3d_fitter
	number of TRGCDC3DFitterTracks

	n3d_fast_fitter
	number of TRGCDC3DFitterFastTracks

	n3d_neuro
	number of TRGCDCNeuroTracks

	n3d_fast_neuro
	number of TRGCDCNeuroFastTracks

Static Public Attributes
	outputFileName

Detailed Description

analyze the difference between 2D with and without clone suppression

Definition at line 145 of file z0_with_clone_suppression.py.

Member Function Documentation

◆ event()

def event ( self )

event function of Ana

Definition at line 188 of file z0_with_clone_suppression.py.

    def event(self):
        """event function of Ana"""
        self.n2d_finder += any(self.finder_trk2d)
        self.n2d_fitter += any(self.trk2d)
        self.n3d_fitter += any(self.trk3d)
        self.n3d_neuro += any(self.trknt)
        self.n2d_fast_finder += any(self.fast_finder_trk2d)
        self.n2d_fast_fitter += any(self.fast_trk2d)
        self.n3d_fast_fitter += any(self.fast_trk3d)
        self.n3d_fast_neuro += any(self.fast_trknt)
 
        if len(self.trk2d) == 0 or len(self.fast_trk2d) == 0:
            return
        ts_hits = self.trk2d[0].getRelationsTo('CDCTriggerSegmentHits')
        b2.B2DEBUG(10, f'TS size: {ts_hits.size()}')
        fast_ts_hits = self.fast_trk2d[0].getRelationsTo('CDCTriggerSegmentHits')
        b2.B2DEBUG(10, f'fast TS size: {fast_ts_hits.size()}')
 

◆ initialize()

def initialize ( self )

Initilization of Ana

Definition at line 148 of file z0_with_clone_suppression.py.

    def initialize(self):
        """Initilization of Ana"""
        
        self.event_info = Belle2.PyStoreObj('EventMetaData')
        
        self.mc = Belle2.PyStoreArray('MCParticles')
        
        self.finder_trk2d = Belle2.PyStoreArray('TRGCDC2DFinderTracks')
        
        self.fast_finder_trk2d = Belle2.PyStoreArray('TRGCDC2DFinderFastTracks')
        
        self.trk2d = Belle2.PyStoreArray('TRGCDC2DFitterTracks')
        
        self.fast_trk2d = Belle2.PyStoreArray('TRGCDC2DFitterFastTracks')
        
        self.trk3d = Belle2.PyStoreArray('TRGCDC3DFitterTracks')
        
        self.fast_trk3d = Belle2.PyStoreArray('TRGCDC3DFitterFastTracks')
        
        self.trknt = Belle2.PyStoreArray('TRGCDCNeuroTracks')
        
        self.fast_trknt = Belle2.PyStoreArray('TRGCDCNeuroFastTracks')
 
        self.n2d_finder = 0
        
        self.n2d_fast_finder = 0
        
        self.n2d_fitter = 0
        
        self.n2d_fast_fitter = 0
        
        self.n3d_fitter = 0
        
        self.n3d_fast_fitter = 0
        
        self.n3d_neuro = 0
        
        self.n3d_fast_neuro = 0

◆ terminate()

def terminate ( self )

Terminate Ana

Definition at line 206 of file z0_with_clone_suppression.py.

    def terminate(self):
        """Terminate Ana"""
        total = self.n2d_finder
        fast_total = self.n2d_fast_finder
        all_numbers = ','.join(['{}'] * 8)
 
        b2.B2INFO(all_numbers.format(self.n2d_finder, self.n2d_fitter, self.n3d_fitter, self.n3d_neuro,
                                     self.n2d_fast_finder, self.n2d_fast_fitter, self.n3d_fast_fitter, self.n3d_fast_neuro))
 
        b2.B2INFO(f'2D fitter retention rate: {self.n2d_fitter / total:.2%} ' +
                  f'(original)/ {self.n2d_fast_fitter / fast_total:.2%} (fast)')
        b2.B2INFO(f'3D fitter retention rate: {self.n3d_fitter / self.n2d_fitter:.2%} ' +
                  f'(original)/ {self.n3d_fast_fitter / self.n2d_fast_fitter:.2%} (fast)')
        b2.B2INFO(f'3D neuro retention rate: {self.n3d_neuro / total:.2%} ' +
                  f'(original)/ {self.n3d_fast_neuro / fast_total:.2%} (fast)')
 
 