Inheritance diagram for MCSideTrackingValidationModule:

[legend]

Collaboration diagram for MCSideTrackingValidationModule:

[legend]

Public Member Functions
	__init__ (self, name, contact, output_file_name=None, reco_tracks_name='RecoTracks', mc_reco_tracks_name='MCRecoTracks', expert_level=None)

	initialize (self)

	prepare (self)

	pick (self, mc_reco_track)

	peel (self, mc_reco_track)

	peel_mc_to_pr_match_info (self, mc_reco_track)

	peel_hit_efficiencies_in_all_pr_tracks (self, mc_reco_track)

	id (self)

	event (self)

	terminate (self)

	barn (self)

	gather (self)

	refine (self, crops)

Static Public Member Functions
	create_crop_part_collection ()

	iter_store_obj (store_obj)

Public Attributes
	reco_tracks_name = reco_tracks_name
	Name of the StoreArray of the tracks from pattern recognition.

	mc_reco_tracks_name = mc_reco_tracks_name
	Name of the StoreArray of the ideal mc tracks.

	track_match_look_up = None
	Reference to the track match lookup object reading the relation information constructed by the MCMatcherTracksModule.

	found_det_hit_ids = set()
	Set of all detector and hits ids contained in any pr track.

	matched_det_hit_ids = set()
	Set of all detector and hits ids contained in matched pr tracks.

	clone_det_hit_ids = set()
	Set of all detector and hits ids contained in clone pr tracks.

	fake_det_hit_ids = set()
	Set of all detector and hits ids contained in background and ghost pr tracks.

	foreach = foreach
	Name of the StoreArray or iterable StoreObjPtr that contains the objects to be harvested.

	output_file_name = output_file_name
	Name of the ROOT output file to be generated.

	title = title or self.name()
	Name of this harvest.

	contact = contact
	Contact email address to be displayed on the validation page.

int	expert_level = self.default_expert_level if expert_level is None else expert_level
	Integer expert level that controls to detail of plots to be generated.

list	refiners = []
	A list of additional refiner instances to be executed on top of the refiner methods that are members of this class.

	show_results = show_results
	Switch to show the result ROOT file in a TBrowser on terminate.

	stash = self.barn()
	stash of the harvested crops (start with those in the barn)

	crops
	the dictionaries from peel

	raw_crops = raw_crops
	the dictionaries from peel as a numpy.array of doubles

Static Public Attributes
	save_tree
	Save a tree of all collected variables in a sub folder.

	save_tree_basic
	Save a basic tree.

	save_overview_figures_of_merit
	Generate the average finding efficiencies and hit efficiencies.

	save_hit_efficiency_histogram
	Save a histogram of the hit efficiency.

dict	renaming_select_for_finding_efficiency_profiles
	Rename the efficiency-profile quantities so that they display nicely in ROOT TLatex.

	save_finding_efficiency_profiles
	Make profile of finding efficiency.

	save_finding_efficiency_by_tan_lamba_profiles
	Make profile of finding efficiency versus tan(lambda)

	save_finding_efficiency_by_tan_lamba_in_pt_groups_profiles
	Make profiles of finding efficiency versus tan(lambda) grouped by transverse momentum.

dict	renaming_select_for_hit_efficiency_profiles
	Rename the hit-profile quantities so that they display nicely in ROOT TLatex.

	save_hit_efficiency_profiles
	Make profile of hit efficiency.

	save_hit_efficiency_by_tan_lambda_profiles
	Make profile of finding efficiency versus tan(lambda)

	save_finding_efficiency_by_pt_profiles_groupbyCharge
	Charge dependent histograms Make profile of finding efficiency versus pt, tan(lambda)

	save_finding_efficiency_by_tan_lambda_profiles_groupbyCharge
	Charge dependent histograms Make profile of finding efficiency versus pt, tan(lambda)

	save_hit_efficiency_by_pt_profiles_groupbyCharge
	Charge dependent histograms Make profile of finding efficiency versus pt, tan(lambda)

	save_hit_efficiency_by_tan_lambda_profiles_groupbyCharge
	Charge dependent histograms Make profile of finding efficiency versus pt, tan(lambda)

	save_hit_efficiency_in_all_found_hist
	This creates a histogram for all MC track displaying the ratio of hits contained in any PR track Hence this is distinctly larger than the hit efficiency to the matched PR track Usefulness under discussion.

	save_missing_mc_tracks_hit_efficiency_in_all_found_hist
	This creates a histogram for each missing MC track displaying the ratio of hits contained in any PR tracks High values in this hit efficiencies means that the MC track is consumed by other PR tracks but no proper match could be established.

int	default_expert_level = 1
	The default value of expert_level if not specified explicitly by the caller.

Detailed Description

Module to collect matching information about the found particles and to generate
   validation plots and figures of merit on the performance of track finding.

 Expert level behavior:
    expert_level = default_expert_level: all figures and plots from this module except tree entries
    expert_level > default_expert_level: everything including tree entries
    expert_level <= default_expert_level//2: only basic figures
    default_expert_level//2 < expert_level < default_expert_level: basic figures and basic tree entries

Definition at line 22 of file mc_side_module.py.

Constructor & Destructor Documentation

◆ init()

__init__	(	self,
		name,
		contact,
		output_file_name = None,
		reco_tracks_name = 'RecoTracks',
		mc_reco_tracks_name = 'MCRecoTracks',
		expert_level = None )

Constructor

Definition at line 35 of file mc_side_module.py.

            expert_level=None):
        """Constructor"""
 
        output_file_name = output_file_name or name + 'TrackingValidation.root'
 
        super().__init__(foreach=mc_reco_tracks_name,
                         name=name,
                         output_file_name=output_file_name,
                         contact=contact,
                         expert_level=expert_level)
 
        ## Name of the StoreArray of the tracks from pattern recognition
        self.reco_tracks_name = reco_tracks_name
 
        ## Name of the StoreArray of the ideal mc tracks
        self.mc_reco_tracks_name = mc_reco_tracks_name
 
        ## Reference to the track match lookup object reading the relation information constructed by the MCMatcherTracksModule
        self.track_match_look_up = None
 
        if self.expert_level >= self.default_expert_level:
            ## Set of all detector and hits ids contained in any pr track. Updated each event.
            self.found_det_hit_ids = set()
 
            ## Set of all detector and hits ids contained in matched pr tracks. Updated each event.
            self.matched_det_hit_ids = set()
 
            ## Set of all detector and hits ids contained in clone pr tracks. Updated each event.
            self.clone_det_hit_ids = set()
 
            ## Set of all detector and hits ids contained in background and ghost pr tracks. Updated each event.
            self.fake_det_hit_ids = set()
 

Member Function Documentation

◆ barn()

barn ( self )

inherited

Coroutine that receives the dictionaries of names and values from peel and store them.

Reimplemented in PickleHarvestingModule.

Definition at line 287 of file harvesting.py.

    def barn(self):
        """Coroutine that receives the dictionaries of names and values from peel and store them."""
        crop = (yield)
        raw_crops = copy.copy(crop)
        crops = copy.copy(crop)
 
        if isinstance(crop, numbers.Number):
            raw_crops = self.create_crop_part_collection()
            try:
                while True:
                    raw_crops.append(crop)
                    # next crop
                    crop = (yield)
            except GeneratorExit:
                crops = np.array(raw_crops)
 
        elif isinstance(crop, collections.abc.MutableMapping):
            for part_name in crop:
                raw_crops[part_name] = self.create_crop_part_collection()
 
            try:
                while True:
                    for part_name, parts in list(raw_crops.items()):
                        if part_name in crop:
                            parts.append(crop[part_name])
                        else:
                            parts.append(np.NaN)
                    # next crop
                    crop = (yield)
            except GeneratorExit:
                for part_name, parts in list(raw_crops.items()):
                    crops[part_name] = np.array(parts)
 
        else:
            msg = f"Unrecognised crop {crop} of type {type(crop)}"
            raise ValueError(msg)
 
        
        self.raw_crops = raw_crops
        
        self.crops = crops
 

◆ create_crop_part_collection()

create_crop_part_collection ( )

staticinherited

Create the storing objects for the crop values

Currently a numpy.array of doubles is used to store all values in memory.

Definition at line 279 of file harvesting.py.

    def create_crop_part_collection():
        """Create the storing objects for the crop values
 
        Currently a numpy.array of doubles is used to store all values in memory.
        """
        return array.array("d")
 

◆ event()

event ( self )

inherited

Event method of the module

* Does invoke the prepare method before the iteration starts.
* In each event fetch the StoreArray / iterable StoreObjPtr,
* Iterate through all instances
* Feed each instance to the pick method to decide it the instance is relevant
* Forward it to the peel method that should generated a dictionary of values
* Store each dictionary of values

Definition at line 239 of file harvesting.py.

    def event(self):
        """Event method of the module
 
        * Does invoke the prepare method before the iteration starts.
        * In each event fetch the StoreArray / iterable StoreObjPtr,
        * Iterate through all instances
        * Feed each instance to the pick method to decide it the instance is relevant
        * Forward it to the peel method that should generated a dictionary of values
        * Store each dictionary of values
        """
        self.prepare()
        stash = self.stash.send
        pick = self.pick
        peel = self.peel
        for crop in self.gather():
            if pick(crop):
                crop = peel(crop)
                if isinstance(crop, types.GeneratorType):
                    many_crops = crop
                    for crop in many_crops:
                        stash(crop)
                else:
                    stash(crop)
 

◆ gather()

gather ( self )

inherited

Iterator that yield the instances form the StoreArray / iterable StoreObj.

Yields
------
Object instances from the StoreArray, iterable StoreObj or the StoreObj itself
in case it is not iterable.

Definition at line 329 of file harvesting.py.

    def gather(self):
        """Iterator that yield the instances form the StoreArray / iterable StoreObj.
 
        Yields
        ------
        Object instances from the StoreArray, iterable StoreObj or the StoreObj itself
        in case it is not iterable.
        """
 
        registered_store_arrays = Belle2.PyStoreArray.list()
        registered_store_objs = Belle2.PyStoreObj.list()
 
        foreach = self.foreach
        foreach_is_store_obj = foreach in registered_store_objs
        foreach_is_store_array = foreach in registered_store_arrays
 
        if foreach is not None:
            if foreach_is_store_array:
                store_array = Belle2.PyStoreArray(self.foreach)
                yield from store_array
 
            elif foreach_is_store_obj:
                store_obj = Belle2.PyStoreObj(self.foreach)
                try:
                    yield from self.iter_store_obj(store_obj)
                except TypeError:
                    # Cannot iter the store object. Yield it instead.
                    yield store_obj.obj()
 
            else:
                msg = f"Name {self.foreach} does not refer to a valid object on the data store"
                raise KeyError(msg)
        else:
            yield None
 

◆ id()

id ( self )

inherited

Working around that name() is a method.

Exposing the name as a property using a different name

Definition at line 224 of file harvesting.py.

    def id(self):
        """Working around that name() is a method.
 
        Exposing the name as a property using a different name
        """
        return self.name()
 

◆ initialize()

initialize ( self )

Initialization signal at the start of the event processing

Reimplemented from HarvestingModule.

Definition at line 75 of file mc_side_module.py.

    def initialize(self):
        """Initialization signal at the start of the event processing"""
        super().initialize()
        self.track_match_look_up = Belle2.TrackMatchLookUp(self.mc_reco_tracks_name, self.reco_tracks_name)
 

◆ iter_store_obj()

iter_store_obj ( store_obj )

staticinherited

Obtain a iterator from a StoreObj

Repeatedly calls iter(store_obj) or store_obj.__iter__()
until the final iterator returns itself

Returns
-------
iterator of the StoreObj

Definition at line 443 of file harvesting.py.

    def iter_store_obj(store_obj):
        """Obtain a iterator from a StoreObj
 
        Repeatedly calls iter(store_obj) or store_obj.__iter__()
        until the final iterator returns itself
 
        Returns
        -------
        iterator of the StoreObj
        """
        iterable = store_obj.obj()
        last_iterable = None
        while iterable is not last_iterable:
            if hasattr(iterable, "__iter__"):
                iterable, last_iterable = iterable.__iter__(), iterable
            else:
                iterable, last_iterable = iter(iterable), iterable
        return iterable
 
 

◆ peel()

peel	(		self,
			mc_reco_track )

Looks at the individual Monte Carlo tracks and store information about them

Reimplemented from HarvestingModule.

Definition at line 119 of file mc_side_module.py.

    def peel(self, mc_reco_track):
        """Looks at the individual Monte Carlo tracks and store information about them"""
        track_match_look_up = self.track_match_look_up
 
        # Analyse from the Monte Carlo reference side
        mc_reco_tracks = Belle2.PyStoreArray(self.foreach)
        multiplicity = mc_reco_tracks.getEntries()
 
        mc_particle = track_match_look_up.getRelatedMCParticle(mc_reco_track)
        is_primary = bool(mc_particle.hasStatus(Belle2.MCParticle.c_PrimaryParticle))
        mc_to_pr_match_info_crops = self.peel_mc_to_pr_match_info(mc_reco_track)
        mc_store_array_crops = peelers.peel_store_array_info(mc_reco_track, key="mc_{part_name}")
 
        crops = dict(is_primary=is_primary,
                     multiplicity=multiplicity,
                     **mc_to_pr_match_info_crops,
                     **mc_store_array_crops
                     )
 
        if self.expert_level >= self.default_expert_level:
            reco_track = track_match_look_up.getRelatedPRRecoTrack(mc_reco_track)
            mc_particle_crops = peelers.peel_mc_particle(mc_particle)
            hit_content_crops = peelers.peel_reco_track_hit_content(mc_reco_track)
 
            # Custom peel function to get single detector hit purities
            subdetector_hit_efficiency_crops = peelers.peel_subdetector_hit_efficiency(mc_reco_track, reco_track)
 
            mc_hit_efficiencies_in_all_pr_tracks_crops = self.peel_hit_efficiencies_in_all_pr_tracks(mc_reco_track)
 
            # Event Info
            event_meta_data = Belle2.PyStoreObj("EventMetaData")
            event_crops = peelers.peel_event_info(event_meta_data)
 
            # Store Array for easier joining
            store_array_crops = peelers.peel_store_array_info(reco_track, key="pr_{part_name}")
 
            # Information on PR reco track
            pr_purity_information = {
                "pr_hit_purity": track_match_look_up.getRelatedPurity(reco_track) if reco_track else float("nan"),
                **peelers.peel_subdetector_hit_purity(reco_track=reco_track, mc_reco_track=mc_reco_track,
                                                      key="pr_{part_name}")
            }
 
            # Information on TrackFinders
            trackfinder_crops = peelers.peel_trackfinder(reco_track)
 
            # Basic peel function to get Quality Indicators
            qualityindicator_crops = peelers.peel_quality_indicators(reco_track)
 
            crops.update(dict(**hit_content_crops,
                              **mc_particle_crops,
                              **subdetector_hit_efficiency_crops,
                              **mc_hit_efficiencies_in_all_pr_tracks_crops,
                              **event_crops,
                              **store_array_crops,
                              **pr_purity_information,
                              **trackfinder_crops,
                              **qualityindicator_crops
                              ))
 
        return crops
 

◆ peel_hit_efficiencies_in_all_pr_tracks()

peel_hit_efficiencies_in_all_pr_tracks	(		self,
			mc_reco_track )

Extracts hit efficiencies

Definition at line 195 of file mc_side_module.py.

    def peel_hit_efficiencies_in_all_pr_tracks(self, mc_reco_track):
        """Extracts hit efficiencies"""
        mc_det_hit_ids = utilities.get_det_hit_ids(mc_reco_track)
 
        hit_efficiency_in_all_found = utilities.calc_hit_efficiency(self.found_det_hit_ids,
                                                                    mc_det_hit_ids)
 
        unfound_hit_efficiency = 1.0 - hit_efficiency_in_all_found
 
        hit_efficiency_in_all_matched = utilities.calc_hit_efficiency(self.matched_det_hit_ids,
                                                                      mc_det_hit_ids)
 
        hit_efficiency_in_all_fake = utilities.calc_hit_efficiency(self.fake_det_hit_ids,
                                                                   mc_det_hit_ids)
 
        hit_efficiency_crops = dict(
            hit_efficiency_in_all_found=hit_efficiency_in_all_found,
            unfound_hit_efficiency=unfound_hit_efficiency,
            hit_efficiency_in_all_matched=hit_efficiency_in_all_matched,
            hit_efficiency_in_all_fake=hit_efficiency_in_all_fake,
        )
        return hit_efficiency_crops
 

◆ peel_mc_to_pr_match_info()

peel_mc_to_pr_match_info	(		self,
			mc_reco_track )

Extracts track-match information from the MCMatcherTracksModule results

Definition at line 181 of file mc_side_module.py.

    def peel_mc_to_pr_match_info(self, mc_reco_track):
        """Extracts track-match information from the MCMatcherTracksModule results"""
        track_match_look_up = self.track_match_look_up
        return dict(
            is_matched=track_match_look_up.isAnyChargeMatchedMCRecoTrack(mc_reco_track),
            is_matched_correct_charge=track_match_look_up.isCorrectChargeMatchedMCRecoTrack(mc_reco_track),
            is_matched_wrong_charge=track_match_look_up.isWrongChargeMatchedMCRecoTrack(mc_reco_track),
            is_merged=track_match_look_up.isAnyChargeMergedMCRecoTrack(mc_reco_track),
            is_merged_correct_charge=track_match_look_up.isCorrectChargeMergedMCRecoTrack(mc_reco_track),
            is_merged_wrong_charge=track_match_look_up.isWrongChargeMergedMCRecoTrack(mc_reco_track),
            is_missing=track_match_look_up.isMissingMCRecoTrack(mc_reco_track),
            hit_efficiency=track_match_look_up.getRelatedEfficiency(mc_reco_track),
        )
 

◆ pick()

pick	(		self,
			mc_reco_track )

Pick every MCRecoTrack

Reimplemented from HarvestingModule.

Definition at line 115 of file mc_side_module.py.

    def pick(self, mc_reco_track):
        """Pick every MCRecoTrack"""
        return True
 

◆ prepare()

prepare ( self )

Collect some statistics about the pattern recognition tracks used for comparison to the MC tracks

Executed once at the start of each event.

Reimplemented from HarvestingModule.

Definition at line 80 of file mc_side_module.py.

    def prepare(self):
        """Collect some statistics about the pattern recognition tracks used for comparison to the MC tracks
 
        Executed once at the start of each event.
        """
        super().prepare()
        if self.expert_level >= self.default_expert_level:
            reco_tracks = Belle2.PyStoreArray(self.reco_tracks_name)
            track_match_look_up = self.track_match_look_up
 
            found_det_hit_ids = set()
            matched_det_hit_ids = set()
            clone_det_hit_ids = set()
            fake_det_hit_ids = set()
 
            for reco_track in reco_tracks:
                det_hit_ids = utilities.get_det_hit_ids(reco_track)
 
                found_det_hit_ids |= det_hit_ids
 
                if track_match_look_up.isAnyChargeMatchedPRRecoTrack(reco_track):
                    matched_det_hit_ids |= det_hit_ids
 
                if track_match_look_up.isAnyChargeClonePRRecoTrack(reco_track):
                    clone_det_hit_ids |= det_hit_ids
 
                if (track_match_look_up.isGhostPRRecoTrack(reco_track) or
                        track_match_look_up.isBackgroundPRRecoTrack(reco_track)):
                    fake_det_hit_ids |= det_hit_ids
 
            self.found_det_hit_ids = found_det_hit_ids
            self.matched_det_hit_ids = matched_det_hit_ids
            self.clone_det_hit_ids = clone_det_hit_ids
            self.fake_det_hit_ids = fake_det_hit_ids
 

◆ refine()

refine	(		self,
			crops )

inherited

Receive the gathered crops and forward them to the refiners.

Reimplemented in PickleHarvestingModule.

Definition at line 398 of file harvesting.py.

    def refine(self, crops):
        """Receive the gathered crops and forward them to the refiners."""
 
        kwds = {}
        if self.output_file_name:
            # Save everything to a ROOT file
            if isinstance(self.output_file_name, ROOT.TFile):
                output_tdirectory = self.output_file_name
            else:
                output_tfile = ROOT.TFile(self.output_file_name, 'recreate')
                output_tdirectory = output_tfile
 
        else:
            output_tdirectory = None
 
        try:
            with root_cd(output_tdirectory):
                for refiner in self.refiners:
                    refiner(self, crops, tdirectory=output_tdirectory, **kwds)
 
                # Get the methods marked as refiners from the class
                cls = type(self)
                for name in dir(cls):
                    if isinstance(getattr(cls, name), Refiner):
                        refiner = getattr(self, name)
                        # Getattr already binds self
                        refiner(crops, tdirectory=output_tdirectory, **kwds)
 
        finally:
            # If we opened the TFile ourself, close it again
            if self.output_file_name:
                if isinstance(self.output_file_name, str):
                    output_tfile.Close()
 
        if self.show_results and self.output_file_name:
            if isinstance(self.output_file_name, str):
                output_tfile = ROOT.TFile(self.output_file_name)
                root_browse(output_tfile)
                input("Press enter to close")
                output_tfile.Close()
            else:
                root_browse(self.output_file_name)
                input("Press enter to close")
 

◆ terminate()

terminate ( self )

inherited

Termination method of the module.

Finalize the collected crops.
Start the refinement.

Reimplemented in ClusterFilterValidationModule.

Definition at line 263 of file harvesting.py.

    def terminate(self):
        """Termination method of the module.
 
        Finalize the collected crops.
        Start the refinement.
        """
 
        self.stash.close()
        del self.stash
 
        try:
            self.refine(self.crops)
        except AttributeError:
            pass
 

Member Data Documentation

◆ clone_det_hit_ids

clone_det_hit_ids = set()

Set of all detector and hits ids contained in clone pr tracks.

Updated each event.

Definition at line 70 of file mc_side_module.py.

◆ contact

contact = contact

inherited

Contact email address to be displayed on the validation page.

Definition at line 211 of file harvesting.py.

◆ crops

crops

inherited

the dictionaries from peel

Definition at line 274 of file harvesting.py.

◆ default_expert_level

int default_expert_level = 1

staticinherited

The default value of expert_level if not specified explicitly by the caller.

Definition at line 156 of file harvesting.py.

◆ expert_level

int expert_level = self.default_expert_level if expert_level is None else expert_level

inherited

Integer expert level that controls to detail of plots to be generated.

Definition at line 214 of file harvesting.py.

◆ fake_det_hit_ids

fake_det_hit_ids = set()

Set of all detector and hits ids contained in background and ghost pr tracks.

Updated each event.

Definition at line 73 of file mc_side_module.py.

◆ foreach

foreach = foreach

inherited

Name of the StoreArray or iterable StoreObjPtr that contains the objects to be harvested.

Definition at line 196 of file harvesting.py.

◆ found_det_hit_ids

found_det_hit_ids = set()

Set of all detector and hits ids contained in any pr track.

Updated each event.

Definition at line 64 of file mc_side_module.py.

◆ matched_det_hit_ids

matched_det_hit_ids = set()

Set of all detector and hits ids contained in matched pr tracks.

Updated each event.

Definition at line 67 of file mc_side_module.py.

◆ mc_reco_tracks_name

mc_reco_tracks_name = mc_reco_tracks_name

Name of the StoreArray of the ideal mc tracks.

Definition at line 57 of file mc_side_module.py.

◆ output_file_name

output_file_name = output_file_name

inherited

Name of the ROOT output file to be generated.

Definition at line 199 of file harvesting.py.

◆ raw_crops

raw_crops = raw_crops

inherited

the dictionaries from peel as a numpy.array of doubles

Definition at line 325 of file harvesting.py.

◆ reco_tracks_name

reco_tracks_name = reco_tracks_name

Name of the StoreArray of the tracks from pattern recognition.

Definition at line 54 of file mc_side_module.py.

◆ refiners

list refiners = []

inherited

A list of additional refiner instances to be executed on top of the refiner methods that are members of this class.

Definition at line 218 of file harvesting.py.

◆ renaming_select_for_finding_efficiency_profiles

dict renaming_select_for_finding_efficiency_profiles

static

Initial value:

=  {
        'is_matched': 'finding efficiency',
        'd0_truth': 'd_{0}',
        'pt_truth': 'p_{t}',
        'multiplicity': 'multiplicity',
        'phi0_truth': '#phi',
    }

Rename the efficiency-profile quantities so that they display nicely in ROOT TLatex.

Definition at line 272 of file mc_side_module.py.

◆ renaming_select_for_hit_efficiency_profiles

dict renaming_select_for_hit_efficiency_profiles

static

Initial value:

=  {
        'hit_efficiency': 'hit efficiency',
        'd0_truth': 'd_{0}',
        'pt_truth': 'p_{t}',
        'multiplicity': 'multiplicity',
        'phi0_truth': '#phi',
    }

Rename the hit-profile quantities so that they display nicely in ROOT TLatex.

Definition at line 330 of file mc_side_module.py.

◆ save_finding_efficiency_by_pt_profiles_groupbyCharge

save_finding_efficiency_by_pt_profiles_groupbyCharge

static

Initial value:

=  refiners.save_profiles(
        
    )

Charge dependent histograms Make profile of finding efficiency versus pt, tan(lambda)

Definition at line 370 of file mc_side_module.py.

◆ save_finding_efficiency_by_tan_lamba_in_pt_groups_profiles

save_finding_efficiency_by_tan_lamba_in_pt_groups_profiles

static

Initial value:

=  refiners.save_profiles(
        
    )

Make profiles of finding efficiency versus tan(lambda) grouped by transverse momentum.

Definition at line 311 of file mc_side_module.py.

◆ save_finding_efficiency_by_tan_lamba_profiles

save_finding_efficiency_by_tan_lamba_profiles

static

Initial value:

=  refiners.save_profiles(
        
    )

Make profile of finding efficiency versus tan(lambda)

Definition at line 294 of file mc_side_module.py.

◆ save_finding_efficiency_by_tan_lambda_profiles_groupbyCharge

save_finding_efficiency_by_tan_lambda_profiles_groupbyCharge

static

Initial value:

=  refiners.save_profiles(
        
    )

Charge dependent histograms Make profile of finding efficiency versus pt, tan(lambda)

Definition at line 388 of file mc_side_module.py.

◆ save_finding_efficiency_profiles

save_finding_efficiency_profiles

static

Initial value:

=  refiners.save_profiles(
        
    )

Make profile of finding efficiency.

Definition at line 281 of file mc_side_module.py.

◆ save_hit_efficiency_by_pt_profiles_groupbyCharge

save_hit_efficiency_by_pt_profiles_groupbyCharge

static

Initial value:

=  refiners.save_profiles(
        
    )

Charge dependent histograms Make profile of finding efficiency versus pt, tan(lambda)

Definition at line 407 of file mc_side_module.py.

◆ save_hit_efficiency_by_tan_lambda_profiles

save_hit_efficiency_by_tan_lambda_profiles

static

Initial value:

=  refiners.save_profiles(
        
    )

Make profile of finding efficiency versus tan(lambda)

Definition at line 352 of file mc_side_module.py.

◆ save_hit_efficiency_by_tan_lambda_profiles_groupbyCharge

save_hit_efficiency_by_tan_lambda_profiles_groupbyCharge

static

Initial value:

=  refiners.save_profiles(
        
    )

Charge dependent histograms Make profile of finding efficiency versus pt, tan(lambda)

Definition at line 425 of file mc_side_module.py.

◆ save_hit_efficiency_histogram

save_hit_efficiency_histogram

static

Initial value:

=  refiners.save_histograms(
        
    )

Save a histogram of the hit efficiency.

Definition at line 262 of file mc_side_module.py.

◆ save_hit_efficiency_in_all_found_hist

save_hit_efficiency_in_all_found_hist

static

Initial value:

=  refiners.save_histograms(
        
    )

This creates a histogram for all MC track displaying the ratio of hits contained in any PR track Hence this is distinctly larger than the hit efficiency to the matched PR track Usefulness under discussion.

Definition at line 445 of file mc_side_module.py.

◆ save_hit_efficiency_profiles

save_hit_efficiency_profiles

static

Initial value:

=  refiners.save_profiles(
        
    )

Make profile of hit efficiency.

Definition at line 339 of file mc_side_module.py.

◆ save_missing_mc_tracks_hit_efficiency_in_all_found_hist

save_missing_mc_tracks_hit_efficiency_in_all_found_hist

static

Initial value:

=  refiners.save_histograms(
        
    )

This creates a histogram for each missing MC track displaying the ratio of hits contained in any PR tracks High values in this hit efficiencies means that the MC track is consumed by other PR tracks but no proper match could be established.

Definition at line 456 of file mc_side_module.py.

◆ save_overview_figures_of_merit

save_overview_figures_of_merit

static

Initial value:

=  refiners.save_fom(
        
    )

Generate the average finding efficiencies and hit efficiencies.

Definition at line 243 of file mc_side_module.py.

◆ save_tree

save_tree

static

Initial value:

=  refiners.save_tree(
        # using cond to suppress false doxygen warnings
        
    )

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

Definition at line 222 of file mc_side_module.py.

◆ save_tree_basic

save_tree_basic

static

Initial value:

=  refiners.save_tree(
        # using cond to suppress false doxygen warnings
        
    )

Save a basic tree.

Definition at line 232 of file mc_side_module.py.

◆ show_results

show_results = show_results

inherited

Switch to show the result ROOT file in a TBrowser on terminate.

Definition at line 221 of file harvesting.py.

◆ stash

stash = self.barn()

inherited

stash of the harvested crops (start with those in the barn)

Definition at line 237 of file harvesting.py.

◆ title

title = title or self.name()

inherited

Name of this harvest.

Title particle of this harvest

Definition at line 208 of file harvesting.py.

◆ track_match_look_up

track_match_look_up = None

Reference to the track match lookup object reading the relation information constructed by the MCMatcherTracksModule.

Definition at line 60 of file mc_side_module.py.

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

tracking/scripts/tracking/harvesting_validation/mc_side_module.py

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Detailed Description

Constructor & Destructor Documentation

◆ __init__()

Member Function Documentation

◆ barn()

◆ create_crop_part_collection()

◆ event()

◆ gather()

◆ id()

◆ initialize()

◆ iter_store_obj()

◆ peel()

◆ peel_hit_efficiencies_in_all_pr_tracks()

◆ peel_mc_to_pr_match_info()

◆ pick()

◆ prepare()

◆ refine()

◆ terminate()

Member Data Documentation

◆ clone_det_hit_ids

◆ contact

◆ crops

◆ default_expert_level

◆ expert_level

◆ fake_det_hit_ids

◆ foreach

◆ found_det_hit_ids

◆ matched_det_hit_ids

◆ mc_reco_tracks_name

◆ output_file_name

◆ raw_crops

◆ reco_tracks_name

◆ refiners

◆ renaming_select_for_finding_efficiency_profiles

◆ renaming_select_for_hit_efficiency_profiles

◆ save_finding_efficiency_by_pt_profiles_groupbyCharge

◆ save_finding_efficiency_by_tan_lamba_in_pt_groups_profiles

◆ save_finding_efficiency_by_tan_lamba_profiles

◆ save_finding_efficiency_by_tan_lambda_profiles_groupbyCharge

◆ save_finding_efficiency_profiles

◆ save_hit_efficiency_by_pt_profiles_groupbyCharge

◆ save_hit_efficiency_by_tan_lambda_profiles

◆ save_hit_efficiency_by_tan_lambda_profiles_groupbyCharge

◆ save_hit_efficiency_histogram

◆ save_hit_efficiency_in_all_found_hist

◆ save_hit_efficiency_profiles

◆ save_missing_mc_tracks_hit_efficiency_in_all_found_hist

◆ save_overview_figures_of_merit

◆ save_tree

◆ save_tree_basic

◆ show_results

◆ stash

◆ title

◆ track_match_look_up

◆ init()