Inheritance diagram for ResultRecordingTask:

Public Member Functions
	output (self)

	requires (self)

	create_result_recording_path (self, result_filter_records_name)

	create_path (self)

	remove_output (self)

Public Attributes
	job_name = self.task_id
	set the job name (inherited variable)

Static Public Attributes
	experiment_number = b2luigi.IntParameter()
	Experiment number of the conditions database, e.g.

	random_seed = b2luigi.Parameter()
	Random basf2 seed.

	n_events_training = b2luigi.IntParameter()
	Number of events to generate.

	fast_bdt_option_state_filter
	Hyperparameter option of the FastBDT algorithm.

	result_filter_records_name = b2luigi.Parameter()
	Name of the records file for training the final result filter.

str	batch_system = 'lsf'
	batch system

str	queue = 's'
	queue

Detailed Description

Task to record data for the final result filter. This requires trained state filters.
The cuts on the state filter classifiers are set to rather low values to ensure that all signal is contained in the recorded
file. Also, the values for XXXXXHighUseNStates are chosen conservatively, i.e. rather on the high side.

Definition at line 632 of file combined_to_pxd_ckf_mva_training.py.

Member Function Documentation

◆ create_path()

create_path ( self )

Create basf2 path to process with event generation and simulation.

Definition at line 782 of file combined_to_pxd_ckf_mva_training.py.

    def create_path(self):
        """
        Create basf2 path to process with event generation and simulation.
        """
        return self.create_result_recording_path(
            result_filter_records_name=self.get_output_file_name(self.result_filter_records_name),
        )
 

◆ create_result_recording_path()

create_result_recording_path	(		self,
			result_filter_records_name )

Create a path for the recording of the result filter. This file is then used to train the result filter.

:param result_filter_records_name: Name of the recording file.

Definition at line 687 of file combined_to_pxd_ckf_mva_training.py.

    def create_result_recording_path(self, result_filter_records_name):
        """
        Create a path for the recording of the result filter. This file is then used to train the result filter.
 
        :param result_filter_records_name: Name of the recording file.
        """
 
        path = basf2.create_path()
 
        # get all the file names from the list of input files that are meant for training
        file_list = [fname for fname in self.get_all_input_file_names()
                     if "generated_mc_N" in fname and "training" in fname and fname.endswith(".root")]
        path.add_module("RootInput", inputFileNames=file_list)
 
        path.add_module("Gearbox")
        path.add_module("Geometry")
        path.add_module("SetupGenfitExtrapolation")
 
        add_hit_preparation_modules(path, components=["SVD", "PXD"])
 
        add_track_finding(path, reco_tracks="CDCSVDRecoTracks", components=["CDC", "SVD"], prune_temporary_tracks=False)
 
        path.add_module('TrackFinderMCTruthRecoTracks',
                        RecoTracksStoreArrayName="MCRecoTracks",
                        WhichParticles=[],
                        UsePXDHits=True,
                        UseSVDHits=True,
                        UseCDCHits=True)
 
        path.add_module("MCRecoTracksMatcher", UsePXDHits=False, UseSVDHits=True, UseCDCHits=True,
                        mcRecoTracksStoreArrayName="MCRecoTracks",
                        prRecoTracksStoreArrayName="CDCSVDRecoTracks")
        path.add_module("DAFRecoFitter", recoTracksStoreArrayName="CDCSVDRecoTracks")
 
        fast_bdt_string = create_fbdt_option_string(self.fast_bdt_option_state_filter)
 
        # write the tracking MVA filter parameters and the cut on MVA classifier to be applied on a local db
        iov = [0, 0, 0, -1]
        write_tracking_mva_filter_payloads_to_db(
            f"trk_ToPXDStateFilter_1_Parameter{fast_bdt_string}",
            iov,
            f"trk_ToPXDStateFilter_1{fast_bdt_string}",
            0.01)
 
        write_tracking_mva_filter_payloads_to_db(
            f"trk_ToPXDStateFilter_2_Parameter{fast_bdt_string}",
            iov,
            f"trk_ToPXDStateFilter_2{fast_bdt_string}",
            0.01)
 
        write_tracking_mva_filter_payloads_to_db(
            f"trk_ToPXDStateFilter_3_Parameter{fast_bdt_string}",
            iov,
            f"trk_ToPXDStateFilter_3{fast_bdt_string}",
            0.01)
 
        basf2.conditions.prepend_testing_payloads("localdb/database.txt")
        first_high_filter_parameters = {"DBPayloadName": f"trk_ToPXDStateFilter_1_Parameter{fast_bdt_string}",
                                        "direction": "backward"}
        second_high_filter_parameters = {"DBPayloadName": f"trk_ToPXDStateFilter_2_Parameter{fast_bdt_string}"}
        third_high_filter_parameters = {"DBPayloadName": f"trk_ToPXDStateFilter_3_Parameter{fast_bdt_string}"}
 
        path.add_module("ToPXDCKF",
                        inputRecoTrackStoreArrayName="CDCSVDRecoTracks",
                        outputRecoTrackStoreArrayName="RecoTracks",
                        outputRelationRecoTrackStoreArrayName="CDCSVDRecoTracks",
 
                        relationCheckForDirection="backward",
                        reverseSeed=False,
                        writeOutDirection="backward",
 
                        firstHighFilter="mva",
                        firstHighFilterParameters=first_high_filter_parameters,
                        firstHighUseNStates=10,
 
                        advanceHighFilter="advance",
 
                        secondHighFilter="mva",
                        secondHighFilterParameters=second_high_filter_parameters,
                        secondHighUseNStates=10,
 
                        updateHighFilter="fit",
 
                        thirdHighFilter="mva",
                        thirdHighFilterParameters=third_high_filter_parameters,
                        thirdHighUseNStates=10,
 
                        filter="recording",
                        filterParameters={"rootFileName": result_filter_records_name},
                        exportTracks=False,
 
                        enableOverlapResolving=True)
 
        return path
 

◆ output()

output ( self )

Generate list of output files that the task should produce.
The task is considered finished if and only if the outputs all exist.

Definition at line 658 of file combined_to_pxd_ckf_mva_training.py.

    def output(self):
        """
        Generate list of output files that the task should produce.
        The task is considered finished if and only if the outputs all exist.
        """
        yield self.add_to_output(self.result_filter_records_name)
 

◆ remove_output()

remove_output ( self )

Default function from base b2luigi.Task class.

Definition at line 790 of file combined_to_pxd_ckf_mva_training.py.

    def remove_output(self):
        """
        Default function from base b2luigi.Task class.
        """
        self._remove_output()
 
 

◆ requires()

requires ( self )

This task requires that the training SplitMergeSimTask is finished, as well as that the state filters are trained using
the CKFStateFilterTeacherTask..

Definition at line 665 of file combined_to_pxd_ckf_mva_training.py.

    def requires(self):
        """
        This task requires that the training SplitMergeSimTask is finished, as well as that the state filters are trained using
        the CKFStateFilterTeacherTask..
        """
        yield SplitNMergeSimTask(
            bkgfiles_dir=SummaryTask.bkgfiles_by_exp[self.experiment_number],
            experiment_number=self.experiment_number,
            n_events=self.n_events_training,
            random_seed=self.random_seed,
        )
        filter_numbers = [1, 2, 3]
        for filter_number in filter_numbers:
            yield self.clone(
                CKFStateFilterTeacherTask,
                experiment_number=self.experiment_number,
                n_events=self.n_events_training,
                random_seed=self.random_seed,
                filter_number=filter_number,
                fast_bdt_option_state_filter=self.fast_bdt_option_state_filter
            )
 

Member Data Documentation

◆ batch_system

str batch_system = 'lsf'

staticinherited

batch system

Definition at line 189 of file combined_to_pxd_ckf_mva_training.py.

◆ experiment_number

experiment_number = b2luigi.IntParameter()

static

Experiment number of the conditions database, e.g.

defines simulation geometry

Definition at line 640 of file combined_to_pxd_ckf_mva_training.py.

◆ fast_bdt_option_state_filter

fast_bdt_option_state_filter

static

Initial value:

=  b2luigi.ListParameter(
        
    )

Hyperparameter option of the FastBDT algorithm.

default are the FastBDT default values.

Definition at line 647 of file combined_to_pxd_ckf_mva_training.py.

◆ job_name

job_name = self.task_id

inherited

set the job name (inherited variable)

Definition at line 197 of file combined_to_pxd_ckf_mva_training.py.

◆ n_events_training

n_events_training = b2luigi.IntParameter()

static

Number of events to generate.

Definition at line 645 of file combined_to_pxd_ckf_mva_training.py.

◆ queue

str queue = 's'

staticinherited

queue

Definition at line 191 of file combined_to_pxd_ckf_mva_training.py.

◆ random_seed

random_seed = b2luigi.Parameter()

static

Random basf2 seed.

It is further used to read of the production process to preserve clearness in the b2luigi output.

Definition at line 643 of file combined_to_pxd_ckf_mva_training.py.

◆ result_filter_records_name

result_filter_records_name = b2luigi.Parameter()

static

Name of the records file for training the final result filter.

Definition at line 653 of file combined_to_pxd_ckf_mva_training.py.

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

tracking/scripts/ckf_training/to_pxd/combined_to_pxd_ckf_mva_training.py

Public Member Functions

Public Attributes

Static Public Attributes

Detailed Description

Member Function Documentation

◆ create_path()

◆ create_result_recording_path()

◆ output()

◆ remove_output()

◆ requires()

Member Data Documentation

◆ batch_system

◆ experiment_number

◆ fast_bdt_option_state_filter

◆ job_name

◆ n_events_training

◆ queue

◆ random_seed

◆ result_filter_records_name