LegendreBinningValidationModule Class Reference

Inheritance diagram for LegendreBinningValidationModule:

Public Member Functions
	__init__ (self, output_file_name)
	initialize (self)
	prepare (self)
	pick (self, track)
	peel (self, 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
	mc_track_lookup = None
	by default, there is no method to find matching MC tracks
	track_fitter = origin_track_fitter
	Use the CDCReimannFitter with a constrained origin for track fitting.
	lower_curv_bounds = np.array([bin[0] for bin in bin_bounds])
	cached copy of lower bounds
	upper_curv_bounds = np.array([bin[1] for bin in bin_bounds])
	cached copy of upper bounds
	mc_hit_lookup = TFCDC.CDCMCHitLookUp.getInstance()
	Method to find matching MC 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 = refiners.save_tree()
	Save a tree of all collected variables in a sub folder.
	save_histograms = refiners.save_histograms(outlier_z_score=5.0, allow_discrete=True)
	Save histograms in a sub folder.
	save_profiles
	Save profile histograms in a sub folder.
	save_cross_curv_profile
	Save cross-curvature profile histograms in a sub folder.
	save_scatter = refiners.save_scatters(x=['curvature_estimate'], y='n_hits')
	Save scatterplots in a sub folder.
int	default_expert_level = 1
	The default value of expert_level if not specified explicitly by the caller.

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__()

__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)
 
        ## by default, there is no method to find matching MC tracks
        self.mc_track_lookup = None
 
        origin_track_fitter = TFCDC.CDCRiemannFitter()
        origin_track_fitter.setOriginConstrained()
        ## Use the CDCReimannFitter with a constrained origin for track fitting
        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)
 
        ## cached copy of lower bounds
        self.lower_curv_bounds = np.array([bin[0] for bin in bin_bounds])
        ## cached copy of upper 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

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

)

Receive signal at the start of event processing

Reimplemented from HarvestingModule.

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()
 

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,
			track )

Aggregate the track and MC information for track-segment analysis

Reimplemented from HarvestingModule.

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()

pick	(		self,
			track )

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

Reimplemented from HarvestingModule.

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()

prepare

(

self

)

Initialize the MC-hit lookup method

Reimplemented from HarvestingModule.

Definition at line 120 of file record.py.

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

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

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.

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.

lower_curv_bounds

lower_curv_bounds = np.array([bin[0] for bin in bin_bounds])

cached copy of lower bounds

Definition at line 106 of file record.py.

mc_hit_lookup

mc_hit_lookup = TFCDC.CDCMCHitLookUp.getInstance()

Method to find matching MC tracks.

Method to find matching MC hits

Definition at line 118 of file record.py.

mc_track_lookup

mc_track_lookup = None

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

Definition at line 90 of file record.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.

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.

save_cross_curv_profile

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

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

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

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

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.

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_fitter

track_fitter = origin_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 = np.array([bin[1] for bin in bin_bounds])

cached copy of upper bounds

Definition at line 108 of file record.py.

---

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

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