LegendreBinningValidationModule Class Reference

Inheritance diagram for LegendreBinningValidationModule:

Public Member Functions
def	__init__ (self, output_file_name)
def	initialize (self)
def	prepare (self)
def	pick (self, track)
def	peel (self, track)

Public Attributes
	mc_track_lookup
	by default, there is no method to find matching MC tracks
	track_fitter
	Use the CDCReimannFitter with a constrained origin for track fitting.
	lower_curv_bounds
	cached copy of lower bounds
	upper_curv_bounds
	cached copy of upper bounds
	mc_hit_lookup
	Method to find matching MC hits.

Static Public Attributes
refiners	save_tree = refiners.save_tree()
	Save a tree of all collected variables in a sub folder.
refiners	save_histograms = refiners.save_histograms(outlier_z_score=5.0, allow_discrete=True)
	Save histograms in a sub folder.
refiners	save_profiles
	Save profile histograms in a sub folder.
refiners	save_cross_curv_profile
	Save cross-curvature profile histograms in a sub folder.
refiners	save_scatter = refiners.save_scatters(x=['curvature_estimate'], y='n_hits')
	Save scatterplots in a sub folder.

Detailed Description

Module to collect information about the generated segments and
compose validation plots on terminate.

Definition at line 79 of file record.py.

Constructor & Destructor Documentation

__init__()

def __init__	(		self,
			output_file_name
	)

Constructor

Definition at line 84 of file record.py.

    def __init__(self, output_file_name):
        """Constructor"""
        super().__init__(foreach='CDCTrackVector',
                         output_file_name=output_file_name)
 
        
        self.mc_track_lookup = None
 
        origin_track_fitter = TFCDC.CDCRiemannFitter()
        origin_track_fitter.setOriginConstrained()
        
        self.track_fitter = origin_track_fitter
 
        curv_bounds = []
        with open('fine_curv_bounds.txt') as curv_bounds_file:
            for curv_bound_line in curv_bounds_file:
                curv_bounds.append(float(curv_bound_line))
 
        bin_bounds = list(zip(curv_bounds[0::2], curv_bounds[1::2]))
        bin_bounds = sorted(bin_bounds)
 
        
        self.lower_curv_bounds = np.array([bin[0] for bin in bin_bounds])
        
        self.upper_curv_bounds = np.array([bin[1] for bin in bin_bounds])
 
        assert (len(self.lower_curv_bounds) == len(self.upper_curv_bounds))
 

Member Function Documentation

initialize()

def initialize

(

self

)

Receive signal at the start of event processing

Definition at line 112 of file record.py.

    def initialize(self):
        """Receive signal at the start of event processing"""
        super().initialize()
        
        self.mc_track_lookup = TFCDC.CDCMCTrackLookUp.getInstance()
        
        self.mc_hit_lookup = TFCDC.CDCMCHitLookUp.getInstance()
 

peel()

def peel	(		self,
			track
	)

Aggregate the track and MC information for track-segment analysis

Definition at line 132 of file record.py.

    def peel(self, track):
        """Aggregate the track and MC information for track-segment analysis"""
        track_fitter = self.track_fitter
 
        rl_drift_circle = 1
        unit_variance = 0
        observations2D = TFCDC.CDCObservations2D(rl_drift_circle, unit_variance)
 
        for recoHit3D in track:
            observations2D.append(recoHit3D)
 
        trajectory2D = track_fitter.fit(observations2D)
        trajectory2D.setLocalOrigin(TFCDC.Vector2D(0, 0))
 
        n_hits = track.size()
        pt = trajectory2D.getAbsMom2D()
        curv = trajectory2D.getCurvature()
        curl_curv = abs(self.lower_curv_bounds[0])
        bin_curv = curv if abs(curv) < curl_curv else abs(curv)
        curv_var = trajectory2D.getLocalVariance(0)
        impact = trajectory2D.getGlobalImpact()
        phi0 = trajectory2D.getLocalCircle().phi0()
 
        circle = trajectory2D.getLocalCircle()
        n12 = circle.n12()
 
        cross_curvs = []
        for recoHit3D in track:
            wire_ref_pos = recoHit3D.getRefPos2D()
            drift_length = recoHit3D.getSignedRecoDriftLength()
            r = wire_ref_pos.norm()
            cross_curv = -2 * (n12.dot(wire_ref_pos) - drift_length) / (r * r - drift_length * drift_length)
            cross_curvs.append(cross_curv)
 
        cross_curvs = np.array(cross_curvs)
        cross_curv = np.median(cross_curvs)
        cross_curv_var = np.median(np.abs(cross_curvs - cross_curv))
 
        basic_curv_precision = TFCDC.PrecisionUtil.getBasicCurvPrecision(cross_curv)
        origin_curv_precision = TFCDC.PrecisionUtil.getOriginCurvPrecision(cross_curv)
        non_origin_curv_precision = TFCDC.PrecisionUtil.getNonOriginCurvPrecision(cross_curv)
 
        bin_id = np.digitize([abs(cross_curv)], self.lower_curv_bounds)
        if bin_id == 0:
            max_curv_precision = 0.00007
        else:
            max_curv_precision = self.upper_curv_bounds[bin_id - 1] - self.lower_curv_bounds[bin_id - 1]
 
        random_bin_id = random.randrange(len(self.upper_curv_bounds))
        random_lower_curv_bound = self.lower_curv_bounds[random_bin_id]
        random_upper_curv_bound = self.upper_curv_bounds[random_bin_id]
        curv_dense = random.uniform(random_lower_curv_bound, random_upper_curv_bound)
        curv_width = random_upper_curv_bound - random_lower_curv_bound
 
        return dict(
            n_hits=n_hits,
            curvature_estimate=curv,
            curvature_variance=curv_var,
            abs_curvature_estimate=abs(curv),
            inv_curv=1.0 / abs(curv),
            cross_curv=cross_curv,
            cross_curv_var=cross_curv_var,
            basic_curv_precision=basic_curv_precision,
            origin_curv_precision=origin_curv_precision,
            non_origin_curv_precision=non_origin_curv_precision,
            max_curv_precision=max_curv_precision,
            pt=pt,
            curv_bin=bin_curv,
            curv_dense=curv_dense,
            curv_width=curv_width,
            impact_estimate=impact,
            phi0=phi0,
        )
 

pick()

def pick	(		self,
			track
	)

Select tracks with at least 4 segments and associated primary MC particle

Definition at line 124 of file record.py.

    def pick(self, track):
        """Select tracks with at least 4 segments and associated primary MC particle"""
        mc_track_lookup = self.mc_track_lookup
        mc_particle = mc_track_lookup.getMCParticle(track)
 
        # Check that mc_particle is not a nullptr
        return mc_particle and is_primary(mc_particle) and track.size() > 3
 

prepare()

def prepare

(

self

)

Initialize the MC-hit lookup method

Definition at line 120 of file record.py.

    def prepare(self):
        """Initialize the MC-hit lookup method"""
        TFCDC.CDCMCHitLookUp.getInstance().fill()
 

Member Data Documentation

lower_curv_bounds

lower_curv_bounds

cached copy of lower bounds

Definition at line 106 of file record.py.

mc_hit_lookup

mc_hit_lookup

Method to find matching MC hits.

Definition at line 118 of file record.py.

mc_track_lookup

mc_track_lookup

by default, there is no method to find matching MC tracks

Method to find matching MC tracks.

Definition at line 90 of file record.py.

save_cross_curv_profile

refiners save_cross_curv_profile

static

Initial value:

=  refiners.save_profiles(x=['cross_curv'],
                                                     y=['cross_curv_var',
                                                        'curvature_estimate',
                                                        'basic_curv_precision',
                                                        'origin_curv_precision',
                                                        'non_origin_curv_precision',
                                                        'max_curv_precision',
                                                        ],
                                                     outlier_z_score=5.0)

Save cross-curvature profile histograms in a sub folder.

Definition at line 218 of file record.py.

save_histograms

refiners save_histograms = refiners.save_histograms(outlier_z_score=5.0, allow_discrete=True)

static

Save histograms in a sub folder.

Definition at line 210 of file record.py.

save_profiles

refiners save_profiles

static

Initial value:

=  refiners.save_profiles(x=['curvature_estimate', 'phi0'],
                                           y='curvature_variance',
                                           outlier_z_score=5.0)

Save profile histograms in a sub folder.

Definition at line 213 of file record.py.

save_scatter

refiners save_scatter = refiners.save_scatters(x=['curvature_estimate'], y='n_hits')

static

Save scatterplots in a sub folder.

Definition at line 229 of file record.py.

save_tree

refiners save_tree = refiners.save_tree()

static

Save a tree of all collected variables in a sub folder.

Definition at line 208 of file record.py.

track_fitter

track_fitter

Use the CDCReimannFitter with a constrained origin for track fitting.

Definition at line 95 of file record.py.

upper_curv_bounds

upper_curv_bounds

cached copy of upper bounds

Definition at line 108 of file record.py.

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

• tracking/trackFindingCDC/studies/legendreBinning/record.py