path_utils.py

 

 
from pybasf2 import B2WARNING, B2FATAL
 
from ROOT import Belle2  # noqa: make the Belle2 namespace available
 
from basf2 import register_module
from geometry import is_detector_present, are_detectors_present, is_any_detector_present
from ckf.path_functions import add_pxd_ckf, add_ckf_based_merger, add_svd_ckf, add_cosmics_svd_ckf, add_cosmics_pxd_ckf
from pxd import add_pxd_reconstruction
from svd import add_svd_reconstruction
from tracking.adjustments import adjust_module
 
 
def use_local_sectormap(path, pathToLocalSM):
    """    Helper function that sets up the SectorMapBootstrapModule in that way that a local sectormap will be
    loaded instead the one from the DB. Has to be applied on the path after the SectorMapBootstrap was
    put into the path (usually in add_reconstructin)
 
    :param path: The path the SectorMapBootstrapModule is in.
    :param pathToLocalSM: the local storage position of the sectormap (including the name)
 
    """
    B2WARNING("Warning will load local SectorMap from:  " + pathToLocalSM)
    adjust_module(path, 'SectorMapBootstrap', **{"ReadSecMapFromDB": False,
                                                 "ReadSectorMap": True, "SectorMapsInputFile": pathToLocalSM})
 
 
def add_geometry_modules(path, components=None):
    """
    Helper function to add the geometry related modules needed for tracking
    to the path.
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: the list of geometry components in use or None for all components.
    """
    # check for detector geometry, necessary for track extrapolation in genfit
    if 'Geometry' not in path:
        path.add_module('Geometry', useDB=True)
        if components is not None:
            B2WARNING("Custom detector components specified: Will still build full geometry")
 
    # Material effects for all track extrapolations
    if 'SetupGenfitExtrapolation' not in path:
        path.add_module('SetupGenfitExtrapolation',
                        energyLossBrems=False, noiseBrems=False)
 
 
def add_hit_preparation_modules(path, components=None, pxd_filtering_offline=False, create_intercepts_for_pxd_ckf=False):
    """
    Helper function to prepare the hit information to be used by tracking.
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: the list of geometry components in use or None for all components.
    :param pxd_filtering_offline: PXD data reduction is performed after CDC and SVD tracking,
            so PXD reconstruction has to wait until the ROIs are calculated.
    :param create_intercepts_for_pxd_ckf: If True, the PXDROIFinder is added to the path to create PXDIntercepts to be used
        for hit filtering when creating the CKF relations. This independent of the offline PXD digit filtering which is
        steered by 'pxd_filtering_offline'. This can be applied for both data and MC.
    """
 
    # Preparation of the SVD clusters
    if is_detector_present("SVD", components):
        add_svd_reconstruction(path)
 
    # Preparation of the PXD clusters
    if is_detector_present("PXD", components) and not pxd_filtering_offline and not create_intercepts_for_pxd_ckf:
        add_pxd_reconstruction(path)
 
 
def add_track_fit_and_track_creator(path, components=None, pruneTracks=False, trackFitHypotheses=None,
                                    reco_tracks="RecoTracks", add_mva_quality_indicator=True, v0_finding=True):
    """
    Helper function to add the modules performing the
    track fit, the V0 fit and the Belle2 track creation to the path.
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: the list of geometry components in use or None for all components.
    :param pruneTracks: Delete all hits expect the first and the last from the found tracks.
    :param trackFitHypotheses: Which pdg hypotheses to fit. Defaults to [211, 321, 2212].
    :param reco_tracks: Name of the StoreArray where the reco tracks should be stored
    :param v0_finding: if false, the V0Finder module is not executed
    :param add_mva_quality_indicator: If true, add the MVA track quality estimation
        to the path that sets the quality indicator property of the found tracks.
    """
 
    add_prefilter_track_fit_and_track_creator(path, components=components,
                                              trackFitHypotheses=trackFitHypotheses,
                                              reco_tracks=reco_tracks,
                                              add_mva_quality_indicator=add_mva_quality_indicator)
 
    add_postfilter_track_fit_and_track_creator(path,
                                               trackFitHypotheses=trackFitHypotheses,
                                               reco_tracks=reco_tracks)
 
    # V0 finding
    if v0_finding:
        path.add_module('V0Finder', RecoTracks=reco_tracks, v0FitterMode=1)
 
    if pruneTracks:
        add_prune_tracks(path, components=components, reco_tracks=reco_tracks)
 
 
def add_prefilter_track_fit_and_track_creator(path, components=None, trackFitHypotheses=None,
                                              stopOnSuccessfulTrackFit=True,
                                              reco_tracks="RecoTracks", add_mva_quality_indicator=True):
    """
    Helper function to add only the modules required to calculate HLT filter decision:
    performing the track fit and the Belle2 track creation to the path.
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: the list of geometry components in use or None for all components.
    :param reco_tracks: Name of the StoreArray where the reco tracks should be stored
    :param trackFitHypotheses: Which pdg hypotheses to fit. Defaults to [211, 321, 2212].
    :param stopOnSuccessfulTrackFit: If true (default), the TrackCreator will stop when a fit is successful
        among the listed "trackFitHypotheses". Otherwise, all listed hypotheses are attempted.
    :param add_mva_quality_indicator: If true, add the MVA track quality estimation
        to the path that sets the quality indicator property of the found tracks.
    """
 
    # Correct time seed
    path.add_module("IPTrackTimeEstimator",
                    recoTracksStoreArrayName=reco_tracks, useFittedInformation=False)
    # track fitting
    path.add_module("DAFRecoFitter", recoTracksStoreArrayName=reco_tracks).set_name(
        "Combined_DAFRecoFitter")
    # Add MVA classifier that uses information not included in the calculation of the fit p-value
    # to add a track quality indicator for classification of fake vs. MC-matched tracks
 
    if add_mva_quality_indicator:
        path.add_module("TrackQualityEstimatorMVA", collectEventFeatures=True)
    # create Belle2 tracks from the RecoTrack objects (which have genfit tracks)
    # By default, stops creating Belle2 tracks when a successful fit is found among given hypotheses,
    # rest will be fitted in the postfilter
    path.add_module('TrackCreator', recoTrackColName=reco_tracks,
                    pdgCodes=[211, 321, 2212] if not trackFitHypotheses else trackFitHypotheses,
                    stopOnSuccessfulTrackFit=stopOnSuccessfulTrackFit
                    ).set_name("TrackCreator_prefilter")
 
 
def add_postfilter_track_fit_and_track_creator(path,
                                               trackFitHypotheses=None,
                                               reco_tracks="RecoTracks"):
    """
    Helper function to add the modules not required to calculate HLT filter decision,
    and ran after the HLT decision calculation.
    It performs track fit and creates Belle II tracks with additional mass hypotheses.
 
    :param path: The path to add the tracking reconstruction modules to
    :param reco_tracks: Name of the StoreArray where the reco tracks should be stored
    :param trackFitHypotheses: Which pdg hypotheses to fit. Defaults to [211, 321, 2212].
    """
 
    # By default, some hypotheses are already fitted until a successful fit is found in the prefilter
    # Rest of the hypotheses will be fitted here.
    # Muon fit is working but gives very similar as the Pion due to the closeness of masses
    # -> therefore not in the default fit list
    # Electron fit has as systematic bias and therefore not done here. Therefore, pion fits
    # will be used for electrons which gives a better result as GenFit's current electron
    # implementation.
    path.add_module('TrackCreator', recoTrackColName=reco_tracks,
                    pdgCodes=[211, 321, 2212] if not trackFitHypotheses else trackFitHypotheses,
                    stopOnSuccessfulTrackFit=False,
                    ).set_name("TrackCreator_postfilter")
 
 
def add_cr_track_fit_and_track_creator(path, components=None,
                                       prune_tracks=False, event_timing_extraction=True,
                                       reco_tracks="RecoTracks", tracks=""):
    """
    Helper function to add the modules performing the cdc cr track fit
    and track creation to the path.
 
    :param path: The path to which to add the tracking reconstruction modules
    :param components: the list of geometry components in use or None for all components.
    :param reco_tracks: The name of the reco tracks to use
    :param tracks: the name of the output Belle tracks
    :param prune_tracks: Delete all hits expect the first and the last from the found tracks.
    :param event_timing_extraction: extract the event time
    """
 
    # Time seed
    path.add_module("PlaneTriggerTrackTimeEstimator",
                    recoTracksStoreArrayName=reco_tracks,
                    pdgCodeToUseForEstimation=13,
                    triggerPlanePosition=[0., 0., 0.],
                    triggerPlaneDirection=[0., 1., 0.],
                    useFittedInformation=False)
 
    # Initial track fitting
    path.add_module("DAFRecoFitter",
                    recoTracksStoreArrayName=reco_tracks,
                    probCut=0.00001,
                    pdgCodesToUseForFitting=13).set_name(f"DAFRecoFitter {reco_tracks}")
 
    # Correct time seed
    path.add_module("PlaneTriggerTrackTimeEstimator",
                    recoTracksStoreArrayName=reco_tracks,
                    pdgCodeToUseForEstimation=13,
                    triggerPlanePosition=[0., 0., 0.],
                    triggerPlaneDirection=[0., 1., 0.],
                    useFittedInformation=True)
 
    # Final Track fitting
    path.add_module("DAFRecoFitter",
                    recoTracksStoreArrayName=reco_tracks,
                    pdgCodesToUseForFitting=13
                    ).set_name(f"DAFRecoFitter {reco_tracks}")
 
    if event_timing_extraction:
        # Extract the time
        path.add_module("FullGridChi2TrackTimeExtractor",
                        RecoTracksStoreArrayName=reco_tracks,
                        GridMaximalT0Value=40,
                        GridMinimalT0Value=-40,
                        GridGridSteps=6
                        )
 
        # Track fitting
        path.add_module("DAFRecoFitter",
                        # probCut=0.00001,
                        recoTracksStoreArrayName=reco_tracks,
                        pdgCodesToUseForFitting=13
                        ).set_name(f"DAFRecoFitter {reco_tracks}")
 
    # Create Belle2 Tracks from the genfit Tracks
    path.add_module('TrackCreator',
                    pdgCodes=[13],
                    recoTrackColName=reco_tracks,
                    trackColName=tracks,
                    useClosestHitToIP=True,
                    useBFieldAtHit=True
                    )
 
    # Prune genfit tracks
    if prune_tracks:
        add_prune_tracks(path=path, components=components, reco_tracks=reco_tracks)
 
 
def add_mc_matcher(path, components=None, mc_reco_tracks="MCRecoTracks",
                   reco_tracks="RecoTracks", use_second_cdc_hits=False,
                   split_after_delta_t=-1.0, matching_method="hit",
                   relate_tracks_to_mcparticles=True,
                   chi2_cutoffs=[128024, 95, 173, 424, 90, 424],
                   chi2_linalg=False):
    """
    Match the tracks to the MC truth. The matching works based on
    the output of the TrackFinderMCTruthRecoTracks.
    Alternatively one can use the Chi2MCTrackMatcher based on chi2 values
    calculated from the helixparameters of Tracks and MCParticles.
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: the list of geometry components in use or None for all components.
    :param mc_reco_tracks: Name of the StoreArray where the mc reco tracks will be stored
    :param reco_tracks: Name of the StoreArray where the reco tracks should be stored
    :param use_second_cdc_hits: If true, the second hit information will be used in the CDC track finding.
    :param split_after_delta_t: If positive, split MCRecoTrack into multiple MCRecoTracks if the time
                                distance between two adjacent SimHits is more than the given value
    :param matching_method:     hit: uses the hit-matching
                                chi2: uses the chi2-matching
    :param relate_tracks_to_mcparticles:    If True (default), Tracks are related to MCParticles. Only works
                                            if the TrackCreator is in the path before. Needs to be set to False
                                            if only track finding is performed, but no Tracks are created.
    :param chi2_cutoffs:        If chi2 matching method is used, this list defines the individual cut-off values
                                for the chi2 values. Thereby each charged stable particle gets its cut-off
                                value. The order of the pdgs is [11,13,211,2212,321,1000010020]. The default
                                values are determined from a small study investigating chi2 value distribution of
                                trivial matching pairs.
    :param chi2_linalg:         If chi2 matching is used, this defines package used to invert the covariance5
                                matrix. ROOT has been shown to be faster than eigen. If False ROOT is used. If True
                                eigen is used.
    """
    if (matching_method == "hit"):
        path.add_module('TrackFinderMCTruthRecoTracks',
                        RecoTracksStoreArrayName=mc_reco_tracks,
                        WhichParticles=[],
                        UseSecondCDCHits=use_second_cdc_hits,
                        UsePXDHits=is_detector_present("PXD", components),
                        UseSVDHits=is_detector_present("SVD", components),
                        UseCDCHits=is_detector_present("CDC", components),
                        SplitAfterDeltaT=split_after_delta_t)
 
        path.add_module('MCRecoTracksMatcher',
                        mcRecoTracksStoreArrayName=mc_reco_tracks,
                        prRecoTracksStoreArrayName=reco_tracks,
                        UsePXDHits=is_detector_present("PXD", components),
                        UseSVDHits=is_detector_present("SVD", components),
                        UseCDCHits=is_detector_present("CDC", components))
 
        if relate_tracks_to_mcparticles:
            path.add_module('TrackToMCParticleRelator')
 
    elif (matching_method == "chi2"):
        print("Warning: The Chi2MCTrackMatcherModule is currently not fully developed and tested!")
        path.add_module('Chi2MCTrackMatcherModule',
                        CutOffs=chi2_cutoffs,
                        linalg=chi2_linalg)
 
 
def add_prune_tracks(path, components=None, reco_tracks="RecoTracks"):
    """
    Adds removal of the intermediate states at each measurement from the fitted tracks.
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: the list of geometry components in use or None for all components.
    :param reco_tracks: Name of the StoreArray where the reco tracks should be stored
    """
 
    # do not add any pruning, if no tracking detectors are in the components
    if components and not is_any_detector_present(["SVD", "CDC"], components):
        return
 
    path.add_module('PruneRecoTracks', storeArrayName=reco_tracks).set_name("PruneRecoTracks " + reco_tracks)
    path.add_module("PruneGenfitTracks")
 
 
def add_flipping_of_recoTracks(
        path,
        fit_tracks=True,
        reco_tracks="RecoTracks",
        trackFitHypotheses=None,
        reco_tracks_flipped="RecoTracks_flipped"):
    """
    This function adds the mva based selections and the flipping of the recoTracks
 
    :param path: The path to add the tracking reconstruction modules to
    :param fit_tracks: fit the flipped recotracks or not
    :param reco_tracks: Name of the StoreArray where the reco tracks should be flipped
    :param trackFitHypotheses: Which pdg hypotheses to fit. Defaults to [211, 321, 2212].
    :param reco_tracks_flipped: Name of the temporary StoreArray for the flipped RecoTracks
    """
 
    path.add_module("FlipQuality", recoTracksStoreArrayName=reco_tracks,
                    identifier='TRKTrackFlipAndRefit_MVA1_weightfile',
                    indexOfFlippingMVA=1).set_name("FlipQuality_1stMVA")
 
    path.add_module("RecoTracksReverter", inputStoreArrayName=reco_tracks,
                    outputStoreArrayName=reco_tracks_flipped)
    if fit_tracks:
        path.add_module("DAFRecoFitter", recoTracksStoreArrayName=reco_tracks_flipped).set_name("Combined_DAFRecoFitter_flipped")
        path.add_module("IPTrackTimeEstimator",
                        recoTracksStoreArrayName=reco_tracks_flipped, useFittedInformation=False)
    path.add_module("TrackCreator", trackColName="Tracks_flipped",
                    trackFitResultColName="TrackFitResults_flipped",
                    recoTrackColName=reco_tracks_flipped,
                    pdgCodes=[
                        211,
                        321,
                        2212] if not trackFitHypotheses else trackFitHypotheses).set_name("TrackCreator_flipped")
    path.add_module("FlipQuality", recoTracksStoreArrayName=reco_tracks,
                    identifier='TRKTrackFlipAndRefit_MVA2_weightfile',
                    indexOfFlippingMVA=2).set_name("FlipQuality_2ndMVA")
    path.add_module("FlippedRecoTracksMerger",
                    inputStoreArrayName=reco_tracks,
                    inputStoreArrayNameFlipped=reco_tracks_flipped)
 
 
def add_pxd_track_finding(path, components, input_reco_tracks, output_reco_tracks, use_mc_truth=False,
                          add_both_directions=False, temporary_reco_tracks="PXDRecoTracks", **kwargs):
    """Add the pxd track finding to the path"""
    if not is_detector_present("PXD", components):
        return
 
    if use_mc_truth:
        # MC CKF needs MC matching information
        path.add_module("MCRecoTracksMatcher", UsePXDHits=False,
                        UseSVDHits=is_detector_present("SVD", components), UseCDCHits=is_detector_present("CDC", components),
                        mcRecoTracksStoreArrayName="MCRecoTracks",
                        prRecoTracksStoreArrayName=input_reco_tracks)
 
    add_pxd_ckf(path, svd_cdc_reco_tracks=input_reco_tracks, pxd_reco_tracks=temporary_reco_tracks,
                direction="backward", use_mc_truth=use_mc_truth, **kwargs)
 
    if add_both_directions:
        add_pxd_ckf(path, svd_cdc_reco_tracks=input_reco_tracks, pxd_reco_tracks=temporary_reco_tracks,
                    direction="forward", use_mc_truth=use_mc_truth, **kwargs)
 
    path.add_module("RelatedTracksCombiner", CDCRecoTracksStoreArrayName=input_reco_tracks,
                    VXDRecoTracksStoreArrayName=temporary_reco_tracks, recoTracksStoreArrayName=output_reco_tracks)
 
 
def add_pxd_cr_track_finding(path, components, input_reco_tracks, output_reco_tracks, use_mc_truth=False,
                             add_both_directions=False, temporary_reco_tracks="PXDRecoTracks", **kwargs):
    """Add the pxd track finding to the path"""
    if not is_detector_present("PXD", components):
        return
 
    if use_mc_truth:
        # MC CKF needs MC matching information
        path.add_module("MCRecoTracksMatcher", UsePXDHits=False,
                        UseSVDHits=is_detector_present("SVD", components), UseCDCHits=is_detector_present("CDC", components),
                        mcRecoTracksStoreArrayName="MCRecoTracks",
                        prRecoTracksStoreArrayName=input_reco_tracks)
 
    add_cosmics_pxd_ckf(path, svd_cdc_reco_tracks=input_reco_tracks, pxd_reco_tracks=temporary_reco_tracks,
                        direction="backward", use_mc_truth=use_mc_truth, **kwargs)
 
    if add_both_directions:
        add_cosmics_pxd_ckf(path, svd_cdc_reco_tracks=input_reco_tracks, pxd_reco_tracks=temporary_reco_tracks,
                            direction="forward", use_mc_truth=use_mc_truth, **kwargs)
 
    path.add_module("RelatedTracksCombiner", CDCRecoTracksStoreArrayName=input_reco_tracks,
                    VXDRecoTracksStoreArrayName=temporary_reco_tracks, recoTracksStoreArrayName=output_reco_tracks)
 
 
def add_svd_track_finding(
        path,
        components,
        input_reco_tracks,
        output_reco_tracks,
        svd_ckf_mode="SVD_after",
        use_mc_truth=False,
        add_both_directions=True,
        temporary_reco_tracks="SVDRecoTracks",
        temporary_svd_cdc_reco_tracks="SVDPlusCDCStandaloneRecoTracks",
        use_svd_to_cdc_ckf=True,
        prune_temporary_tracks=True,
        add_mva_quality_indicator=False,
        svd_standalone_mode="VXDTF2",
        **kwargs,
):
    """
    Add SVD track finding to the path.
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: The list of geometry components in use or None for all components.
    :param input_reco_tracks: Name of the StoreArray with the input reco tracks (usually from CDC) that are used in the
           CKF track finding and are merged with the newly found SVD tracks into the ``output_reco_tracks``.
    :param output_reco_tracks: Name of the StoreArray where the reco tracks outputted by the SVD track finding should be
           stored.
    :param svd_ckf_mode: String designating the mode of the CDC-to-SVD CKF, that is how it is combined with the SVD
            standalone track finding. One of "SVD_after", "SVD_before", "SVD_before_with_second_ckf",
            "only_ckf", "ckf_merger_plus_spacepoint_ckf", "SVD_alone", "cosmics".
    :param use_mc_truth: Add mc matching and use the MC information in the CKF (but not in the VXDTF2)
    :param add_both_directions: Whether to add the CKF with both forward and backward extrapolation directions instead
           of just one.
    :param temporary_reco_tracks: Intermediate store array where the SVD tracks from the SVD standalone track finding
           are stored, before they are merged with CDC tracks and extended via the CKF tracking.
    :param temporary_svd_cdc_reco_tracks: Intermediate store array where the combination of ``temporary_reco_tracks``
           (from SVD) and ``input_reco_tracks`` (from CDC standalone) is stored, before the CKF is applied.
           It is only used if ``use_svd_to_cdc_ckf`` is true. Otherwise, the combination is stored directly in
           ``output_reco_tracks``.
    :param use_svd_to_cdc_ckf: Whether to enable the CKF extrapolation from the SVD into the CDC.
           That CKF application is not affected by ``svd_ckf_mode``.
    :param prune_temporary_tracks: Delete all hits expect the first and last from intermediate track objects.
    :param add_mva_quality_indicator: Add the VXDQualityEstimatorMVA module to set the quality indicator
           property for tracks from VXDTF2 standalone tracking
           (ATTENTION: Standard triplet QI of VXDTF2 is replaced in this case
           -> setting this option to 'True' will have some influence on the final track collection)
    :param svd_standalone_mode: Which SVD standalone tracking is used.
           Options are "VXDTF2", "SVDHough", "VXDTF2_and_SVDHough", and "SVDHough_and_VXDTF2".
           Defaults to "VXDTF2"
    :param cdc_backtrack_chain: The backtrack relation chain for finding the original CDC RecoTracks.
    :param svd_backtrack_chain: The backtrack relation chain for finding the original SVD RecoTracks.
    """
 
    if not is_detector_present("SVD", components):
        return
 
    if not input_reco_tracks or input_reco_tracks == "":
        # We do not have an input track store array. So lets just add SVD standalone track finding
        add_svd_standalone_tracking(path, components=["SVD"],
                                    svd_standalone_mode=svd_standalone_mode,
                                    reco_tracks=output_reco_tracks,
                                    add_mva_quality_indicator=add_mva_quality_indicator)
        return
 
    if use_mc_truth:
        # MC CKF needs MC matching information
        path.add_module("MCRecoTracksMatcher", UsePXDHits=False, UseSVDHits=False,
                        UseCDCHits=is_detector_present("CDC", components),
                        mcRecoTracksStoreArrayName="MCRecoTracks",
                        prRecoTracksStoreArrayName=input_reco_tracks)
 
    if svd_ckf_mode == "SVD_before":
        add_svd_standalone_tracking(path, components=["SVD"],
                                    svd_standalone_mode=svd_standalone_mode,
                                    reco_tracks=temporary_reco_tracks,
                                    add_mva_quality_indicator=add_mva_quality_indicator)
        add_ckf_based_merger(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                             use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_ckf_based_merger(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                                 use_mc_truth=use_mc_truth, direction="forward", **kwargs)
 
    elif svd_ckf_mode == "SVD_before_with_second_ckf":
        add_svd_standalone_tracking(path, components=["SVD"],
                                    svd_standalone_mode=svd_standalone_mode,
                                    reco_tracks=temporary_reco_tracks,
                                    add_mva_quality_indicator=add_mva_quality_indicator)
        add_ckf_based_merger(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                             use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_ckf_based_merger(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                                 use_mc_truth=use_mc_truth, direction="forward", **kwargs)
        add_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                    use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                        use_mc_truth=use_mc_truth, direction="forward", **kwargs)
 
    elif svd_ckf_mode == "only_ckf":
        add_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                    use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                        use_mc_truth=use_mc_truth, direction="forward", **kwargs)
 
    # option for inside-out tracking when we start with SVD tracking
    elif svd_ckf_mode == "ckf_merger_plus_spacepoint_ckf":
        add_ckf_based_merger(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                             use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_ckf_based_merger(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                                 use_mc_truth=use_mc_truth, direction="forward", **kwargs)
        add_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                    use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                        use_mc_truth=use_mc_truth, direction="forward", **kwargs)
 
    elif svd_ckf_mode == "SVD_after":
        add_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                    use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                        use_mc_truth=use_mc_truth, direction="forward", **kwargs)
 
        add_svd_standalone_tracking(path, components=["SVD"],
                                    svd_standalone_mode=svd_standalone_mode,
                                    reco_tracks=temporary_reco_tracks,
                                    add_mva_quality_indicator=add_mva_quality_indicator)
        add_ckf_based_merger(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                             use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_ckf_based_merger(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                                 use_mc_truth=use_mc_truth, direction="forward", **kwargs)
 
    elif svd_ckf_mode == "SVD_alone":
        add_svd_standalone_tracking(path, components=["SVD"],
                                    svd_standalone_mode=svd_standalone_mode,
                                    reco_tracks=temporary_reco_tracks,
                                    add_mva_quality_indicator=add_mva_quality_indicator)
        path.add_module('VXDCDCTrackMerger',
                        CDCRecoTrackColName=input_reco_tracks,
                        VXDRecoTrackColName=temporary_reco_tracks)
 
    elif svd_ckf_mode == "cosmics":
        add_cosmics_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                            use_mc_truth=use_mc_truth, direction="backward", **kwargs)
        if add_both_directions:
            add_cosmics_svd_ckf(path, cdc_reco_tracks=input_reco_tracks, svd_reco_tracks=temporary_reco_tracks,
                                use_mc_truth=use_mc_truth, direction="forward", **kwargs)
 
    else:
        raise ValueError(f"Do not understand the svd_ckf_mode {svd_ckf_mode}")
 
    if use_svd_to_cdc_ckf:
        combined_svd_cdc_standalone_tracks = temporary_svd_cdc_reco_tracks
    else:
        combined_svd_cdc_standalone_tracks = output_reco_tracks
 
    # Write out the combinations of tracks
    path.add_module("RelatedTracksCombiner", VXDRecoTracksStoreArrayName=temporary_reco_tracks,
                    CDCRecoTracksStoreArrayName=input_reco_tracks,
                    recoTracksStoreArrayName=combined_svd_cdc_standalone_tracks)
 
    if use_svd_to_cdc_ckf:
        path.add_module("ToCDCCKF",
                        inputWireHits="CDCWireHitVector",
                        inputRecoTrackStoreArrayName=combined_svd_cdc_standalone_tracks,
                        relatedRecoTrackStoreArrayName="CKFCDCRecoTracks",
                        relationCheckForDirection="backward",
                        ignoreTracksWithCDChits=True,
                        outputRecoTrackStoreArrayName="CKFCDCRecoTracks",
                        outputRelationRecoTrackStoreArrayName=combined_svd_cdc_standalone_tracks,
                        writeOutDirection="backward",
                        stateBasicFilterParameters={"maximalHitDistance": 0.15},
                        pathFilter="arc_length",
                        maximalLayerJump=4)
 
        path.add_module("CDCCKFTracksCombiner",
                        CDCRecoTracksStoreArrayName="CKFCDCRecoTracks",
                        VXDRecoTracksStoreArrayName=combined_svd_cdc_standalone_tracks,
                        recoTracksStoreArrayName=output_reco_tracks)
 
        if prune_temporary_tracks:
            for temp_reco_track in [combined_svd_cdc_standalone_tracks, "CKFCDCRecoTracks"]:
                path.add_module('PruneRecoTracks', storeArrayName=temp_reco_track).set_name("PruneRecoTracks " + temp_reco_track)
 
 
def add_svd_standalone_tracking(path,
                                components=["SVD"],
                                svd_clusters="",
                                svd_standalone_mode="VXDTF2",
                                reco_tracks="SVDRecoTracks",
                                add_mva_quality_indicator=False,
                                suffix=""):
    """
    Convenience function to add the SVD standalone tracking
 
    :param path: basf2 path
    :param components: components to use, defaults to SVD
    :param svd_clusters: Name of the SVDClusters StoreArray used for tracking
    :param svd_standalone_mode: Which SVD standalone tracking is used.
           Options are "VXDTF2", "SVDHough", "VXDTF2_and_SVDHough", and "SVDHough_and_VXDTF2".
           Defaults to "VXDTF2"
    :param reco_tracks: In case the only SVD standalone tracking is performed, these are the final RecoTracks,
           otherwise it's an intermediate StoreaArray where the SVD tracks from the SVD standalone track finding
           are stored, before they are merged with CDC tracks and extended via the CKF tracking.
    :param add_mva_quality_indicator: Add the VXDQualityEstimatorMVA module to set the quality indicator
           property for tracks from VXDTF2 standalone tracking
           (ATTENTION: Standard triplet QI of VXDTF2 is replaced in this case
           -> setting this option to 'True' will have some influence on the final track collection)
    :param suffix: all names of intermediate Storearrays will have the suffix appended. Useful in cases someone needs to
                   put several instances of track finding in one path.
    """
    if svd_standalone_mode == "VXDTF2":
        add_vxd_track_finding_vxdtf2(path, components=components, svd_clusters=svd_clusters, reco_tracks=reco_tracks,
                                     add_mva_quality_indicator=add_mva_quality_indicator, suffix=suffix)
 
    elif svd_standalone_mode == "SVDHough":
        add_svd_hough_tracking(path, reco_tracks=reco_tracks, suffix=suffix)
 
    elif svd_standalone_mode == "VXDTF2_and_SVDHough":
        add_vxd_track_finding_vxdtf2(path,
                                     components=components,
                                     svd_clusters=svd_clusters,
                                     nameSPTCs="SPTrackCands"+"VXDTF2",
                                     reco_tracks=reco_tracks+"VXDTF2",
                                     add_mva_quality_indicator=add_mva_quality_indicator,
                                     suffix=suffix)
        add_svd_hough_tracking(path,
                               reco_tracks=reco_tracks+"Hough",
                               svd_space_point_track_candidates="SPTrackCands"+"Hough",
                               suffix=suffix)
 
        path.add_module('RecoTrackStoreArrayCombiner',
                        Temp1RecoTracksStoreArrayName=reco_tracks+"VXDTF2", Temp1SPTrackCandsStoreArrayName="SPTrackCands"+"VXDTF2",
                        Temp2RecoTracksStoreArrayName=reco_tracks+"Hough",  Temp2SPTrackCandsStoreArrayName="SPTrackCands"+"Hough",
                        recoTracksStoreArrayName=reco_tracks)
        path.add_module('PruneRecoTracks', storeArrayName=reco_tracks+"VXDTF2").set_name("PruneRecoTracks " + reco_tracks+"VXDTF2")
        path.add_module('PruneRecoTracks', storeArrayName=reco_tracks+"Hough").set_name("PruneRecoTracks " + reco_tracks+"Hough")
 
    elif svd_standalone_mode == "SVDHough_and_VXDTF2":
        add_svd_hough_tracking(path,
                               reco_tracks=reco_tracks+"Hough",
                               svd_space_point_track_candidates="SPTrackCands"+"Hough",
                               suffix=suffix)
        add_vxd_track_finding_vxdtf2(path,
                                     components=components,
                                     svd_clusters=svd_clusters,
                                     nameSPTCs="SPTrackCands"+"VXDTF2",
                                     reco_tracks=reco_tracks+"VXDTF2",
                                     add_mva_quality_indicator=add_mva_quality_indicator,
                                     suffix=suffix)
 
        path.add_module('RecoTrackStoreArrayCombiner',
                        Temp1RecoTracksStoreArrayName=reco_tracks+"Hough", Temp1SPTrackCandsStoreArrayName="SPTrackCands"+"Hough",
                        Temp2RecoTracksStoreArrayName=reco_tracks+"VXDTF2", Temp2SPTrackCandsStoreArrayName="SPTrackCands"+"VXDTF2",
                        recoTracksStoreArrayName=reco_tracks)
        path.add_module('PruneRecoTracks', storeArrayName=reco_tracks+"Hough").set_name("PruneRecoTracks " + reco_tracks+"Hough")
        path.add_module('PruneRecoTracks', storeArrayName=reco_tracks+"VXDTF2").set_name("PruneRecoTracks " + reco_tracks+"VXDTF2")
 
    else:
        raise ValueError(f"Do not understand the svd_standalone_mode {svd_standalone_mode}")
 
 
def add_cdc_track_finding(path, output_reco_tracks="RecoTracks", with_cdc_cellular_automaton=False,
                          use_second_hits=False, add_mva_quality_indicator=True,
                          reattach_hits=False, skip_WireHitPreparer=False, use_cat_finder=False):
    """
    Convenience function for adding all cdc track finder modules
    to the path.
 
    The result is a StoreArray with name @param reco_tracks full of RecoTracks (not TrackCands any more!).
    Use the GenfitTrackCandidatesCreator Module to convert back.
 
    :param path: basf2 path
    :param output_reco_tracks: Name of the output RecoTracks. Defaults to RecoTracks.
    :param with_cdc_cellular_automaton: If true, the cellular automaton track finder algorithm will be used too,
        after the global algorithm (Legendre)
    :param use_second_hits: If true, the second hit information will be used in the CDC track finding.
    :param add_mva_quality_indicator: Add the TFCDC_TrackQualityEstimator module to set the CDC quality
           indicator property of the CDC ``output_reco_tracks``
    :param cdc_quality_estimator_weightfile: Weightfile identifier for the TFCDC_TrackQualityEstimator
    :param reattach_hits: if true, use the ReattachCDCWireHitsToRecoTracks module at the end of the CDC track finding
                          to read hits with bad ADC or TOT rejected by the TFCDC_WireHitPreparer module.
    :param skip_WireHitPreparer: if True, the TFCDC_WireHitPreparer will be skipped. This is necessary if for instance
        the SVD tracking and the ToCDCCKF are run before the full CDC tracking, as the ToCDCCKF already reqires the WireHits
        to be present. Defaults to False, as for the default tracking chain it is required.
    :param use_cat_finder: if True, it runs the CDC AI Track Finder (CATFinder) as CDC track finding algorithm
        instead of the default one.
    """
    # add EventLevelTrackinginfo for logging errors
    if 'RegisterEventLevelTrackingInfo' not in path:
        path.add_module('RegisterEventLevelTrackingInfo')
 
    if not use_cat_finder:
        if not skip_WireHitPreparer:
            # Init the geometry for cdc tracking and the hits and cut low ADC hits
            path.add_module("TFCDC_WireHitPreparer",
                            wirePosition="aligned",
                            useSecondHits=use_second_hits,
                            flightTimeEstimation="outwards",
                            filter="combined",
                            filterParameters={'DBPayloadName': 'trackfindingcdc_WireHitBackgroundDetectorParameters'})
 
        # Constructs clusters
        path.add_module("TFCDC_ClusterPreparer",
                        ClusterFilter="all",
                        ClusterFilterParameters={})
 
        # Find segments within the clusters
        path.add_module("TFCDC_SegmentFinderFacetAutomaton", SegmentRelationFilterParameters={
                        'DBPayloadName': 'trackfindingcdc_RealisticSegmentRelationFilterParameters'})
 
        # Find axial tracks
        path.add_module("TFCDC_AxialTrackFinderLegendre")
 
        # Improve the quality of the axial tracks
        path.add_module("TFCDC_TrackQualityAsserter",
                        corrections=["B2B"])
 
        # Find the stereo hits to those axial tracks
        path.add_module('TFCDC_StereoHitFinder')
 
        # Combine segments with axial tracks
        path.add_module('TFCDC_SegmentTrackCombiner',
                        segmentTrackFilter="mva",
                        segmentTrackFilterParameters={'DBPayloadName': 'trackfindingcdc_SegmentTrackFilterParameters'},
                        trackFilter="mva",
                        trackFilterParameters={'DBPayloadName': 'trackfindingcdc_TrackFilterParameters'})
 
        output_tracks = "CDCTrackVector"
 
        if with_cdc_cellular_automaton:
            output_tracks = "CombinedCDCTrackVector"
            path.add_module("TFCDC_TrackFinderSegmentPairAutomaton",
                            tracks="CDCTrackVector2")
 
            # Overwrites the origin CDCTrackVector
            path.add_module("TFCDC_TrackCombiner",
                            inputTracks="CDCTrackVector",
                            secondaryInputTracks="CDCTrackVector2",
                            tracks=output_tracks)
 
        # Improve the quality of all tracks and output
        path.add_module("TFCDC_TrackQualityAsserter",
                        inputTracks=output_tracks,
                        corrections=[
                            "LayerBreak",
                            "OneSuperlayer",
                            "Small",
                        ])
 
        if with_cdc_cellular_automaton:
            # Add curlers in the axial inner most superlayer
            path.add_module("TFCDC_TrackCreatorSingleSegments",
                            inputTracks=output_tracks,
                            MinimalHitsBySuperLayerId={0: 15})
 
        if add_mva_quality_indicator:
            # Add CDC-specific mva method to set the quality indicator for the CDC tracks
            path.add_module(
                "TFCDC_TrackQualityEstimator",
                inputTracks=output_tracks,
                filter='mva',
                filterParameters={'DBPayloadName': 'trackfindingcdc_TrackQualityEstimatorParameters'},
                deleteTracks=True,
                resetTakenFlag=True,
                deactivateIfDeadBoard=False,
                minLayerJumpsForDeadBoards=4
            )
 
        # Export CDCTracks to RecoTracks representation
        path.add_module("TFCDC_TrackExporter",
                        inputTracks=output_tracks,
                        RecoTracksStoreArrayName="CDCRecoTracksBeforeReattaching" if reattach_hits else output_reco_tracks)
 
        if reattach_hits:
            # The ReattachCDCWireHitsToRecoTracks module (below) requires the SetupGenfitExtrapolation module
            if 'SetupGenfitExtrapolation' not in path:
                # Prepare Genfit extrapolation
                path.add_module('SetupGenfitExtrapolation')
 
                # Loop over low-ADC/TOT CDCWireHits and RecoTracks and reattach the hits to the tracks if they are close enough
                path.add_module("ReattachCDCWireHitsToRecoTracks",
                                inputRecoTracksStoreArrayName="CDCRecoTracksBeforeReattaching",
                                outputRecoTracksStoreArrayName=output_reco_tracks)
 
    else:
        path.add_module(
            "TFCDC_WireHitPreparer",
            wirePosition="aligned",
            useSecondHits=use_second_hits,
            flightTimeEstimation="outwards",
            filter="cuts_from_DB",
        )
 
        path.add_module(
            "CATFinder",
            recoTracksStoreArrayName=output_reco_tracks
        )
 
    # Correct time seed (only necessary for the CDC tracks)
    path.add_module("IPTrackTimeEstimator",
                    useFittedInformation=False,
                    recoTracksStoreArrayName=output_reco_tracks)
 
    # run fast t0 estimation from CDC hits only
    path.add_module("CDCHitBasedT0Extraction")
 
    # prepare mdst event level info
    path.add_module("CDCTrackingEventLevelMdstInfoFillerFromHits")
    if not use_cat_finder:
        path.add_module("CDCTrackingEventLevelMdstInfoFillerFromSegments")
 
 
def add_eclcdc_track_finding(path, components, output_reco_tracks="RecoTracks", prune_temporary_tracks=True):
    """
    Convenience function for adding all track finder modules to the path that are based on ecl seeds.
 
    The result is a StoreArray with name @param reco_tracks full of RecoTracks.
    Use the GenfitTrackCandidatesCreator Module to convert back.
 
    :param path: basf2 path
    :param components: the list of geometry components in use or None for all components.
    :param output_reco_tracks: Name of the output RecoTracks. Defaults to RecoTracks.
    :param pruneTracks: Delete all hits expect the first and the last from the found tracks.
    """
    if not are_detectors_present(["CDC", "ECL"], components):
        return
 
    ecl_cdc_reco_tracks = "ECLCDCRecoTracks"
 
    if not is_detector_present("SVD", components):
        ecl_cdc_reco_tracks = output_reco_tracks
 
    # collections that will be pruned
    temporary_reco_track_list = []
 
    path.add_module("ToCDCFromEclCKF",
                    inputWireHits="CDCWireHitVector",
                    minimalEnRequirementCluster=0.3,
                    eclSeedRecoTrackStoreArrayName='EclSeedRecoTracks',
                    hitFindingDirection="backward",
                    outputRecoTrackStoreArrayName="CDCRecoTracksFromEcl",
                    outputRelationRecoTrackStoreArrayName="EclSeedRecoTracks",
                    writeOutDirection="forward",
                    stateBasicFilterParameters={"maximalHitDistance": 7.5, "maximalHitDistanceEclSeed": 75.0},
                    stateExtrapolationFilterParameters={"direction": "backward"},
                    pathFilter="arc_length_fromEcl",
                    inputECLshowersStoreArrayName="ECLShowers",
                    trackFindingDirection="backward",
                    setTakenFlag=False,
                    seedComponent="ECL"
                    )
 
    path.add_module("ToCDCCKF",
                    inputWireHits="CDCWireHitVector",
                    inputRecoTrackStoreArrayName="CDCRecoTracksFromEcl",
                    relatedRecoTrackStoreArrayName=ecl_cdc_reco_tracks,
                    relationCheckForDirection="backward",
                    outputRecoTrackStoreArrayName=ecl_cdc_reco_tracks,
                    outputRelationRecoTrackStoreArrayName="CDCRecoTracksFromEcl",
                    writeOutDirection="backward",
                    stateBasicFilterParameters={"maximalHitDistance": 0.75},
                    stateExtrapolationFilterParameters={"direction": "forward"},
                    pathFilter="arc_length",
                    seedComponent="ECL"
                    )
    # "EclSeedRecoTracks" don't have to be added to the list as these do not contain any hits
    temporary_reco_track_list.append('CDCRecoTracksFromEcl')
 
    # Do the following modules have to be added as these are executed already after
    # the CDC standalone?
    # If so: they also have to be included in the new SVD->CDC CKF (see add_svd_track_finding(..) above)
 
    # Correct time seed (only necessary for the CDC tracks)
    # path.add_module("IPTrackTimeEstimator",
    #                useFittedInformation=False,
    #                recoTracksStoreArrayName=ecl_cdc_reco_tracks)
 
    # run fast t0 estimation from CDC hits only
    # path.add_module("CDCHitBasedT0Extraction")
 
    # prepare mdst event level info
    # path.add_module("CDCTrackingEventLevelMdstInfoFiller")
 
    if is_detector_present("SVD", components):
        add_svd_track_finding(path, components=components, input_reco_tracks=ecl_cdc_reco_tracks,
                              output_reco_tracks=output_reco_tracks, use_mc_truth=False,
                              svd_ckf_mode="only_ckf", add_both_directions=False,
                              temporary_reco_tracks="ECLSVDRecoTracks", use_svd_to_cdc_ckf=False,
                              prune_temporary_tracks=prune_temporary_tracks)
        temporary_reco_track_list.append(ecl_cdc_reco_tracks)
        temporary_reco_track_list.append('ECLSVDRecoTracks')
 
    if prune_temporary_tracks:
        for temporary_reco_track_name in temporary_reco_track_list:
            if temporary_reco_track_name != output_reco_tracks:
                path.add_module(
                    'PruneRecoTracks',
                    storeArrayName=temporary_reco_track_name).set_name(
                    "PruneRecoTracks " +
                    temporary_reco_track_name)
 
 
def add_cdc_cr_track_finding(path, output_reco_tracks="RecoTracks", trigger_point=(0, 0, 0), merge_tracks=True,
                             use_second_cdc_hits=False):
    """
    Convenience function for adding all cdc track finder modules currently dedicated for the CDC-TOP testbeam
    to the path.
 
    The result is a StoreArray with name @param reco_tracks full of RecoTracks (not TrackCands any more!).
 
    Arguments
    ---------
    path: basf2.Path
       The path to be filled
    output_reco_tracks: str
       Name of the output RecoTracks. Defaults to RecoTracks.
    merge_tracks: bool
       The upper and lower half of the tracks should be merged together in one track
    use_second_hits: bool
       If true, the second hit information will be used in the CDC track finding.
    """
 
    # Init the geometry for cdc tracking and the hits
    path.add_module("TFCDC_WireHitPreparer",
                    useSecondHits=use_second_cdc_hits,
                    flightTimeEstimation="downwards",
                    filter="cuts_from_DB",
                    triggerPoint=trigger_point)
 
    # Constructs clusters and reduce background hits
    path.add_module("TFCDC_ClusterPreparer",
                    ClusterFilter="mva_bkg",
                    ClusterFilterParameters={'DBPayloadName': 'trackfindingcdc_ClusterFilterParameters'})
 
    # Find segments within the clusters
    path.add_module("TFCDC_SegmentFinderFacetAutomaton",
                    SegmentOrientation="downwards")
 
    # Find axial tracks
    path.add_module("TFCDC_AxialTrackFinderLegendre")
 
    # Improve the quality of the axial tracks
    path.add_module("TFCDC_TrackQualityAsserter",
                    corrections=["B2B"])
 
    # Find the stereo hits to those axial tracks
    path.add_module('TFCDC_StereoHitFinder')
 
    # Combine segments with axial tracks
    path.add_module('TFCDC_SegmentTrackCombiner',
                    segmentTrackFilter="mva",
                    segmentTrackFilterParameters={'DBPayloadName': 'trackfindingcdc_SegmentTrackFilterParameters'},
                    trackFilter="mva",
                    trackFilterParameters={'DBPayloadName': 'trackfindingcdc_TrackFilterParameters'})
 
    # Improve the quality of all tracks and output
    path.add_module("TFCDC_TrackQualityAsserter",
                    corrections=["LayerBreak", "OneSuperlayer", "Small"],
                    )
 
    # Flip track orientation to always point downwards
    path.add_module("TFCDC_TrackOrienter",
                    inputTracks="CDCTrackVector",
                    tracks="OrientedCDCTrackVector",
                    TrackOrientation="downwards",
                    )
 
    output_tracks = "OrientedCDCTrackVector"
 
    if merge_tracks:
        # Merge tracks together if needed
        path.add_module("TFCDC_TrackLinker",
                        inputTracks="OrientedCDCTrackVector",
                        tracks="MergedCDCTrackVector",
                        filter="phi",
                        )
        output_tracks = "MergedCDCTrackVector"
 
        # However, we also want to export the non merged tracks
        # Correct time seed - assumes velocity near light speed
        path.add_module("TFCDC_TrackFlightTimeAdjuster",
                        inputTracks="OrientedCDCTrackVector",
                        )
 
        # Export CDCTracks to RecoTracks representation
        path.add_module("TFCDC_TrackExporter",
                        inputTracks="OrientedCDCTrackVector",
                        RecoTracksStoreArrayName="NonMergedRecoTracks")
 
    # Correct time seed - assumes velocity near light speed
    path.add_module("TFCDC_TrackFlightTimeAdjuster",
                    inputTracks=output_tracks,
                    )
 
    # Export CDCTracks to RecoTracks representation
    path.add_module("TFCDC_TrackExporter",
                    inputTracks=output_tracks,
                    RecoTracksStoreArrayName=output_reco_tracks)
 
    # run fast t0 estimation from CDC hits only
    path.add_module("CDCHitBasedT0Extraction")
 
 
def add_vxd_track_finding_vxdtf2(
    path,
    svd_clusters="",
    reco_tracks="RecoTracks",
    nameSPTCs='SPTrackCands',
    components=None,
    suffix="",
    useTwoStepSelection=True,
    PXDminSVDSPs=3,
    sectormap_file=None,
    custom_setup_name=None,
    min_SPTC_quality=0.,
    filter_overlapping=True,
    add_mva_quality_indicator=False,
):
    """
    Convenience function for adding all vxd track finder Version 2 modules
    to the path.
 
    The result is a StoreArray with name @param reco_tracks full of RecoTracks (not TrackCands any more!).
    Use the GenfitTrackCandidatesCreator Module to convert back.
 
    :param path: basf2 path
    :param svd_clusters: SVDCluster collection name
    :param reco_tracks: Name of the output RecoTracks, Defaults to RecoTracks.
    :param nameSPTCs: Name of the SpacePointTrackCands StoreArray
    :param components: List of the detector components to be used in the reconstruction. Defaults to None which means
                       all components.
    :param suffix: all names of intermediate Storearrays will have the suffix appended. Useful in cases someone needs to
                   put several instances of track finding in one path.
    :param useTwoStepSelection: if True Families will be defined during path creation and will be used to create only
                                the best candidate per family.
    :param PXDminSVDSPs: When using PXD require at least this number of SVD SPs for the SPTCs
    :param sectormap_file: if set to a finite value, a file will be used instead of the sectormap in the database.
    :param custom_setup_name: Set a custom setup name for the tree in the sector map.
    :param min_SPTC_quality: minimal qualityIndicator value to keeps SPTCs after the QualityEstimation.
                                 0 means no cut. Default: 0
    :param filter_overlapping: Whether to use SVDOverlapResolver, Default: True
    :param add_mva_quality_indicator: Whether to use the MVA Quality Estimator module for VXDTF2 tracks to set the
           quality_indicator property of the found ``reco_tracks``. Default: False.
    """
    
 
    # setting different for pxd and svd:
    if is_detector_present("PXD", components):
        setup_name = "SVDPXDDefault"
        db_sec_map_file = "VXDSectorMap_v000.root"
        use_pxd = True
    else:
        setup_name = "SVDOnlyDefault"
        db_sec_map_file = "SVDSectorMap_v000.root"
        use_pxd = False
 
    
 
    # setup the event level tracking info to log errors and stuff
    nameTrackingInfoModule = "RegisterEventLevelTrackingInfo" + suffix
    nameEventTrackingInfo = "EventLevelTrackingInfo" + suffix
    if nameTrackingInfoModule not in path:
        # Use modified name of module and created StoreObj as module might be added twice (PXDDataReduction)
        registerEventlevelTrackingInfo = register_module('RegisterEventLevelTrackingInfo')
        registerEventlevelTrackingInfo.set_name(nameTrackingInfoModule)
        registerEventlevelTrackingInfo.param('EventLevelTrackingInfoName', nameEventTrackingInfo)
        path.add_module(registerEventlevelTrackingInfo)
 
    nameSPs = 'SpacePoints' + suffix
 
    pxdSPCreatorName = 'PXDSpacePointCreator' + suffix
    if pxdSPCreatorName not in [e.name() for e in path.modules()]:
        if use_pxd:
            spCreatorPXD = register_module('PXDSpacePointCreator')
            spCreatorPXD.set_name(pxdSPCreatorName)
            spCreatorPXD.param('NameOfInstance', 'PXDSpacePoints')
            spCreatorPXD.param('SpacePoints', "PXD" + nameSPs)
            path.add_module(spCreatorPXD)
 
    # SecMap Bootstrap
    secMapBootStrap = register_module('SectorMapBootstrap')
    secMapBootStrap.param('ReadSectorMap', sectormap_file is not None)  # read from file
    secMapBootStrap.param('ReadSecMapFromDB', sectormap_file is None)  # this will override ReadSectorMap
    secMapBootStrap.param('SectorMapsInputFile', sectormap_file or db_sec_map_file)
    secMapBootStrap.param('SetupToRead', custom_setup_name or setup_name)
    secMapBootStrap.param('WriteSectorMap', False)
    path.add_module(secMapBootStrap)
 
    
 
    spacePointArrayNames = ["SVD" + nameSPs]
    if use_pxd:
        spacePointArrayNames += ["PXD" + nameSPs]
 
    nameSegNet = 'SegmentNetwork' + suffix
 
    segNetProducer = register_module('SegmentNetworkProducer')
    segNetProducer.param('NetworkOutputName', nameSegNet)
    segNetProducer.param('SpacePointsArrayNames', spacePointArrayNames)
    segNetProducer.param('sectorMapName', custom_setup_name or setup_name)
    segNetProducer.param('EventLevelTrackingInfoName', nameEventTrackingInfo)
    path.add_module(segNetProducer)
 
    
 
    # append a suffix to the storearray name
    nameSPTCs += suffix
 
    trackFinder = register_module('TrackFinderVXDCellOMat')
    trackFinder.param('NetworkName', nameSegNet)
    trackFinder.param('SpacePointTrackCandArrayName', nameSPTCs)
    trackFinder.param('printNetworks', False)
    trackFinder.param('setFamilies', useTwoStepSelection)
    trackFinder.param('selectBestPerFamily', useTwoStepSelection)
    trackFinder.param('xBestPerFamily', 30)
    trackFinder.param('EventLevelTrackingInfoName', nameEventTrackingInfo)
    path.add_module(trackFinder)
 
    if useTwoStepSelection:
        subSetModule = register_module('AddVXDTrackCandidateSubSets')
        subSetModule.param('NameSpacePointTrackCands', nameSPTCs)
        path.add_module(subSetModule)
 
    
 
    # When using PXD require at least PXDminSVDSPs SVD SPs for the SPTCs
    if use_pxd:
        pxdSVDCut = register_module('PXDSVDCut')
        pxdSVDCut.param('minSVDSPs', PXDminSVDSPs)
        pxdSVDCut.param('SpacePointTrackCandsStoreArrayName', nameSPTCs)
        path.add_module(pxdSVDCut)
 
    if add_mva_quality_indicator:
        path.add_module(
            "VXDQualityEstimatorMVA",
            SpacePointTrackCandsStoreArrayName=nameSPTCs,
        )
    else:
        path.add_module(
            'QualityEstimatorVXD',
            EstimationMethod='tripletFit',
            SpacePointTrackCandsStoreArrayName=nameSPTCs,
        )
 
    if min_SPTC_quality > 0.:
        qualityIndicatorCutter = register_module('VXDTrackCandidatesQualityIndicatorCutter')
        qualityIndicatorCutter.param('minRequiredQuality', min_SPTC_quality)
        qualityIndicatorCutter.param('NameSpacePointTrackCands', nameSPTCs)
        path.add_module(qualityIndicatorCutter)
 
    # will discard track candidates (with low quality estimators) if the number of TC is above threshold
    maxCandidateSelection = register_module('BestVXDTrackCandidatesSelector')
    maxCandidateSelection.param('NameSpacePointTrackCands', nameSPTCs)
    maxCandidateSelection.param('NewNameSpacePointTrackCands', nameSPTCs)
    maxCandidateSelection.param('SubsetCreation', False)
    path.add_module(maxCandidateSelection)
 
    # Properties
    vIPRemover = register_module('SPTCvirtualIPRemover')
    vIPRemover.param('tcArrayName', nameSPTCs)
    # want to remove virtualIP for any track length
    vIPRemover.param('maxTCLengthForVIPKeeping', 0)
    path.add_module(vIPRemover)
 
    
 
    if filter_overlapping:
        overlapResolver = register_module('SVDOverlapResolver')
        overlapResolver.param('NameSpacePointTrackCands', nameSPTCs)
        overlapResolver.param('ResolveMethod', 'greedy')  # other option is  'hopfield'
        overlapResolver.param('NameSVDClusters', svd_clusters)
        path.add_module(overlapResolver)
 
    
 
    momSeedRetriever = register_module('SPTCmomentumSeedRetriever')
    momSeedRetriever.param('tcArrayName', nameSPTCs)
    path.add_module(momSeedRetriever)
 
    converter = register_module('SPTC2RTConverter')
    converter.param('recoTracksStoreArrayName', reco_tracks)
    converter.param('spacePointsTCsStoreArrayName', nameSPTCs)
    converter.param('svdClustersName', svd_clusters)
    converter.param('svdHitsStoreArrayName', svd_clusters)
    path.add_module(converter)
 
 
def add_svd_hough_tracking(path,
                           svd_space_points='SVDSpacePoints',
                           svd_clusters='SVDClusters',
                           reco_tracks='RecoTracks',
                           svd_space_point_track_candidates='SPTrackCands',
                           suffix=''):
    """
    Convenience function to add the SVDHoughTracking to the path.
    :param path: The path to add the SVDHoughTracking module to.
    :param svd_space_points: Name of the StoreArray containing the SVDSpacePoints
    :param svd_clusters: Name of the StoreArray containing the SVDClusters
    :param reco_tracks: Name of the StoreArray containing the RecoTracks
    :param svd_space_point_track_candidates: Name of the StoreArray containing the SpacePointTrackCandidates
    :param suffix: all names of intermediate StoreArrays will have the suffix appended. Useful in cases someone needs to
                   put several instances of track finding in one path.
    """
 
    path.add_module('SVDHoughTracking',
                    SVDSpacePointStoreArrayName=svd_space_points + suffix,
                    SVDClustersStoreArrayName=svd_clusters + suffix,
                    finalOverlapResolverNameSVDClusters=svd_clusters + suffix,
                    refinerOverlapResolverNameSVDClusters=svd_clusters + suffix,
                    RecoTracksStoreArrayName=reco_tracks + suffix,
                    SVDSpacePointTrackCandsStoreArrayName=svd_space_point_track_candidates + suffix,
                    relationFilter='angleAndTime',
                    twoHitUseNBestHits=2,
                    threeHitUseNBestHits=3,
                    fourHitUseNBestHits=3,
                    fiveHitUseNBestHits=2,
                    )
 
 
def add_default_cdc_svd_tracking_chain(path,
                                       components,
                                       svd_reco_tracks,
                                       cdc_reco_tracks,
                                       output_reco_tracks,
                                       with_cdc_cellular_automaton=False,
                                       use_second_cdc_hits=False,
                                       add_cdcTrack_QI=True,
                                       use_mc_truth=False,
                                       svd_ckf_mode="SVD_after",
                                       add_both_directions=True,
                                       use_svd_to_cdc_ckf=True,
                                       svd_standalone_mode="VXDTF2",
                                       add_vxdTrack_QI=False,
                                       prune_temporary_tracks=True,
                                       use_cat_finder=False
                                       ):
    """
    Add the default CDC based tracking chain to the path, i.e. CDC standalone followed by the ToSVDSpacePointCKF, the SVD standalone
    track finding, a CKF based merger for standalone tracks, and finally the SVDToCDCCKF (if setup as such).
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: the list of geometry components in use or None for all components.
    :param svd_reco_tracks: name of the SVD standalone RecoTracks StoreArray
    :param cdc_reco_tracks: name of the CDC standalone RecoTracks StoreArray
    :param output_reco_tracks: name of the combined CDC+SVD RecoTracks StoreArray that is the final result of this tracking path
    :param with_cdc_cellular_automaton: If true, in the CDC track finding the cellular automaton algorithm will be used too,
        after the global algorithm (Legendre)
    :param use_second_cdc_hits: whether to use the secondary CDC hit during CDC track finding or not
    :param add_cdcTrack_QI: If true, add the MVA track quality estimation
        to the path that sets the quality indicator property of the found CDC standalone tracks
    :param use_mc_truth: Use the truth information in the CKF modules
    :param svd_ckf_mode: how to apply the CKF (with or without SVD standalone tracking). Defaults to "SVD_after".
    :param add_both_directions: Curlers may be found in the wrong orientation by the CDC track finder, so try to
           extrapolate also in the other direction.
    :param use_svd_to_cdc_ckf: if true, add SVD to CDC CKF module.
    :param svd_standalone_mode: Which SVD standalone tracking is used.
           Options are "VXDTF2", "SVDHough", "VXDTF2_and_SVDHough", and "SVDHough_and_VXDTF2".
           Defaults to "VXDTF2"
    :param add_vxdTrack_QI: If true, add the MVA track quality estimation
        to the path that sets the quality indicator property of the found VXDTF2 tracks
        (ATTENTION: Standard triplet QI of VXDTF2 is replaced in this case
        -> setting this option to 'True' will have some influence on the final track collection)
    :param prune_temporary_tracks: If false, store all information of the single CDC and VXD tracks before merging.
        If true, prune them.
    :param use_cat_finder: if True, it runs the CDC AI Track Finder (CATFinder) as CDC track finding algorithm
        instead of the default one.
    """
 
    # collections that will be pruned
    temporary_reco_track_list = []
 
    # the name of the most recent track collection
    latest_reco_tracks = None
 
    if is_detector_present("CDC", components):
        add_cdc_track_finding(
            path,
            with_cdc_cellular_automaton=with_cdc_cellular_automaton,
            use_second_hits=use_second_cdc_hits,
            output_reco_tracks=cdc_reco_tracks,
            add_mva_quality_indicator=add_cdcTrack_QI,
            use_cat_finder=use_cat_finder
        )
        temporary_reco_track_list.append(cdc_reco_tracks)
        latest_reco_tracks = cdc_reco_tracks
 
    if is_detector_present("SVD", components):
        add_svd_track_finding(path,
                              components=components,
                              input_reco_tracks=latest_reco_tracks,
                              output_reco_tracks=output_reco_tracks,
                              use_mc_truth=use_mc_truth,
                              temporary_reco_tracks=svd_reco_tracks,
                              svd_ckf_mode=svd_ckf_mode,
                              add_both_directions=add_both_directions,
                              use_svd_to_cdc_ckf=use_svd_to_cdc_ckf,
                              prune_temporary_tracks=prune_temporary_tracks,
                              add_mva_quality_indicator=add_vxdTrack_QI,
                              svd_standalone_mode=svd_standalone_mode)
        temporary_reco_track_list.append(svd_reco_tracks)
        temporary_reco_track_list.append(output_reco_tracks)
        latest_reco_tracks = output_reco_tracks
 
    return (latest_reco_tracks, temporary_reco_track_list)
 
 
def add_inverted_svd_cdc_tracking_chain(path,
                                        components,
                                        svd_reco_tracks,
                                        cdc_reco_tracks,
                                        svd_cdc_reco_tracks,
                                        cdcckf_reco_tracks="CKFCDCRecoTracks",
                                        output_reco_tracks="CombinedSVDCDCRecoTracks",
                                        add_vxdTrack_QI=True,
                                        svd_standalone_mode="VXDTF2",
                                        with_cdc_cellular_automaton=False,
                                        use_second_cdc_hits=False,
                                        add_cdcTrack_QI=True,
                                        use_mc_truth=False,
                                        add_both_directions=True,
                                        prune_temporary_tracks=True,
                                        temporary_reco_tracks_merging_strategy='before_ToSVDCKF',
                                        **kwargs,):
    """
    Add an inverted SVD based tracking chain to the path, i.e. SVD standalone followed by the ToCDCCKF, the CDC standalone
    track finding, a CKF based merger for standalone tracks, and finally the CDCToSVDSpacePointCKF.
 
    ATTENTION: The inverted tracking chain is neither optimised nor guaranteed to be bug free.
    ATTENTION: Please remove this comment once the inverted tracking has been optimised and is assumed to be bug-free.
 
    :param path: The path to add the tracking reconstruction modules to
    :param components: the list of geometry components in use or None for all components.
    :param svd_reco_tracks: name of the SVD standalone RecoTracks StoreArray
    :param cdc_reco_tracks: name of the CDC standalone RecoTracks StoreArray
    :param svd_cdc_reco_tracks: name of the intermediate combined CDC+SVD RecoTracks StoreArray
    :param cdcckf_reco_tracks: name of the intermediate RecoTracks StoreArray from the SVDToCDCCKF
    :param output_reco_tracks: name of the combined CDC+SVD RecoTracks StoreArray that is the final result of this tracking path
    :param add_vxdTrack_QI: If true, add the MVA track quality estimation
        to the path that sets the quality indicator property of the found VXDTF2 tracks
        (ATTENTION: Standard triplet QI of VXDTF2 is replaced in this case
        -> setting this option to 'True' will have some influence on the final track collection)
    :param svd_standalone_mode: Which SVD standalone tracking is used.
           Options are "VXDTF2", "SVDHough", "VXDTF2_and_SVDHough", and "SVDHough_and_VXDTF2".
           Defaults to "VXDTF2"
    :param with_cdc_cellular_automaton: If true, in the CDC track finding the cellular automaton algorithm will be used too,
        after the global algorithm (Legendre)
    :param use_second_cdc_hits: whether to use the secondary CDC hit during CDC track finding or not
    :param add_cdcTrack_QI: If true, add the MVA track quality estimation
        to the path that sets the quality indicator property of the found CDC standalone tracks
    :param use_mc_truth: Use the truth information in the CKF modules
    :param add_both_directions: Curlers may be found in the wrong orientation by the CDC track finder, so try to
           extrapolate also in the other direction.
    :param prune_temporary_tracks: If false, store all information of the single CDC and VXD tracks before merging.
        If true, prune them.
    :param temporary_reco_tracks_merging_strategy: When are the temporary CDC RecoTracks merged? Before or after the ToSVDCKF?
        Allowed options: \"before_ToSVDCKF\" (default) and \"after_ToCDCCKF\".
    """
 
    B2WARNING("ATTENTION: The inverted tracking chain starting from SVD is an experimental feature. "
              "It is neither well optimised nor tested for the time being. "
              "Please be careful when interpreting the results!")
 
    if temporary_reco_tracks_merging_strategy not in ["before_ToSVDCKF", "after_ToCDCCKF"]:
        B2FATAL("Invalid option for 'temporary_reco_tracks_merging_strategy'. "
                "Allowed options are 'before_ToSVDCKF' and 'after_ToCDCCKF'.")
 
    # collections that will be pruned
    temporary_reco_track_list = []
 
    # the name of the most recent track collection
    latest_reco_tracks = None
 
    if is_detector_present("SVD", components):
        add_svd_track_finding(path,
                              components=components,
                              input_reco_tracks="",
                              output_reco_tracks=svd_reco_tracks,
                              add_mva_quality_indicator=add_vxdTrack_QI,
                              svd_standalone_mode=svd_standalone_mode)
        temporary_reco_track_list.append(svd_reco_tracks)
        latest_reco_tracks = svd_reco_tracks
 
        path.add_module("DAFRecoFitter", recoTracksStoreArrayName=svd_reco_tracks).set_name(f"DAFRecoFitter {svd_reco_tracks}")
 
    if is_detector_present("CDC", components):
        path.add_module("TFCDC_WireHitPreparer",
                        wirePosition="aligned",
                        useSecondHits=use_second_cdc_hits,
                        flightTimeEstimation="outwards",
                        filter="combined",
                        filterParameters={'DBPayloadName': 'trackfindingcdc_WireHitBackgroundDetectorParameters'})
 
        path.add_module("ToCDCCKF",
                        inputWireHits="CDCWireHitVector",
                        inputRecoTrackStoreArrayName=svd_reco_tracks,
                        relatedRecoTrackStoreArrayName=cdcckf_reco_tracks,
                        relationCheckForDirection="backward",
                        ignoreTracksWithCDChits=True,
                        outputRecoTrackStoreArrayName=cdcckf_reco_tracks,
                        outputRelationRecoTrackStoreArrayName=svd_reco_tracks,
                        writeOutDirection="backward",
                        stateBasicFilterParameters={"maximalHitDistance": 0.15},
                        pathFilter="arc_length",
                        maximalLayerJump=4)
 
        path.add_module("CDCCKFTracksCombiner",
                        CDCRecoTracksStoreArrayName=cdcckf_reco_tracks,
                        VXDRecoTracksStoreArrayName=svd_reco_tracks,
                        recoTracksStoreArrayName=svd_cdc_reco_tracks)
 
        temporary_reco_track_list.append(cdcckf_reco_tracks)
        temporary_reco_track_list.append(svd_cdc_reco_tracks)
        latest_reco_tracks = svd_cdc_reco_tracks
 
        add_cdc_track_finding(path,
                              with_cdc_cellular_automaton=with_cdc_cellular_automaton,
                              use_second_hits=use_second_cdc_hits,
                              output_reco_tracks=cdc_reco_tracks,
                              add_mva_quality_indicator=add_cdcTrack_QI,
                              skip_WireHitPreparer=True)
        temporary_reco_track_list.append(cdc_reco_tracks)
        latest_reco_tracks = cdc_reco_tracks
 
    if temporary_reco_tracks_merging_strategy == "before_ToSVDCKF":
        path.add_module("RecoTrackStoreArrayCombiner",
                        Temp1RecoTracksStoreArrayName=latest_reco_tracks,
                        Temp2RecoTracksStoreArrayName=svd_cdc_reco_tracks,
                        recoTracksStoreArrayName="CombinedCDCSVDRecoTracks")
        temporary_reco_track_list.append("CombinedCDCSVDRecoTracks")
        latest_reco_tracks = "CombinedCDCSVDRecoTracks"
 
    if is_detector_present("SVD", components):
        # combined_reco_tracks_name is only relevant in the 'after_ToCDCCKF' option
        combined_reco_tracks_name = "CDCSVDRecoTracks"
 
        # The output of the additional SVD tracking (ToSVDCKF in this case) depends on whether
        # the CKF is the last or second to last algorithm to run. If it's the last one, use 'output_reco_tracks',
        # else use 'CDCSVDRecoTracks'
        tmp_output_reco_tracks = output_reco_tracks if "before_ToSVDCKF" else combined_reco_tracks_name
        add_svd_track_finding(path,
                              components=components,
                              input_reco_tracks=latest_reco_tracks,
                              output_reco_tracks=tmp_output_reco_tracks,
                              temporary_reco_tracks=svd_reco_tracks,
                              use_mc_truth=use_mc_truth,
                              svd_ckf_mode="ckf_merger_plus_spacepoint_ckf",
                              add_both_directions=add_both_directions,
                              use_svd_to_cdc_ckf=False,
                              prune_temporary_tracks=prune_temporary_tracks)
        if temporary_reco_tracks_merging_strategy == "before_ToSVDCKF":
            temporary_reco_track_list.append(output_reco_tracks)
            latest_reco_tracks = output_reco_tracks
        elif temporary_reco_tracks_merging_strategy == "after_ToSVDCKF":
            temporary_reco_track_list.append(combined_reco_tracks_name)
            latest_reco_tracks = combined_reco_tracks_name
 
    if temporary_reco_tracks_merging_strategy == "after_ToSVDCKF":
        path.add_module("RecoTrackStoreArrayCombiner",
                        Temp1RecoTracksStoreArrayName=latest_reco_tracks,
                        Temp2RecoTracksStoreArrayName=svd_cdc_reco_tracks,
                        recoTracksStoreArrayName=output_reco_tracks)
        temporary_reco_track_list.append(output_reco_tracks)
        latest_reco_tracks = output_reco_tracks
 
    return (latest_reco_tracks, temporary_reco_track_list)