caf_svd_time.py

#!/usr/bin/env python3
 

'''
Script to perform the svd time calibration with the CoG6, CoG3 and ELS3 algorithms
'''
 
import sys
import datetime
import random
 
import basf2 as b2
 
import rawdata as raw
from softwaretrigger.constants import HLT_INPUT_OBJECTS
from tracking import add_tracking_reconstruction
 
from caf.framework import Calibration
from caf import strategies
from caf.utils import IoV
from prompt import CalibrationSettings, INPUT_DATA_FILTERS
from prompt.utils import filter_by_max_events_per_run
 
from prompt.calibrations.caf_cdc import settings as cdc_tracking_calibration
 
b2.set_log_level(b2.LogLevel.INFO)
 
random.seed(42)
 
now = datetime.datetime.now()
 
settings = CalibrationSettings(name="caf_svd_time",
                               expert_username="giulio.dujany",
                               subsystem="svd",
                               description=__doc__,
                               input_data_formats=["raw"],
                               input_data_names=["hadron_calib"],
                               input_data_filters={"hadron_calib": [INPUT_DATA_FILTERS["Data Tag"]["hadron_calib"],
                                                                    INPUT_DATA_FILTERS["Beam Energy"]["4S"],
                                                                    INPUT_DATA_FILTERS["Beam Energy"]["Continuum"],
                                                                    INPUT_DATA_FILTERS["Run Type"]["physics"],
                                                                    INPUT_DATA_FILTERS["Magnet"]["On"]]},
                               depends_on=[cdc_tracking_calibration],  # SVD time depends on CDC tracking calibration
                               expert_config={
                                   "timeAlgorithms": ["CoG3", "ELS3", "CoG6"],
                                   "listOfMutedCalibrations": [],
                                    # "rawTimeCalibration", "timeShiftCalibration", "AbsoluteTimeShiftCalibration", "timeValidation"
                                   "max_events_per_run":  10000,
                                   "max_events_per_file": 5000,
                                   "isMC": False,
                                   "linearCutsOnCoG3": False,
                                   "upperLineParameters": [-94.0, 1.264],
                                   "lowerLineParameters": [-134.0, 1.264],
                                   "rangeRawTimeForIoVCoG6": [20., 80.],
                                   "rangeRawTimeForIoVCoG3": [70., 140.],
                                   "rangeRawTimeForIoVELS3": [20., 80.],
                                   "useRawtimeForTracking": False,
                                   "useSVDGrouping": True
                               },
                               produced_payloads=["SVD3SampleCoGTimeCalibrations",
                                                  "SVD3SampleELSTimeCalibrations",
                                                  "SVDCoGTimeCalibrations",
                                                  "SVDClusterTimeShifter"])
 

 
 
def remove_module(path, name):
 
    new_path = b2.create_path()
    for m in path.modules():
        if name != m.name():
            new_path.add_module(m)
    return new_path

 
 
NEW_RECO_DIGITS_NAME = "SVDRecoDigitsFromTracks"
NEW_SHAPER_DIGITS_NAME = "SVDShaperDigitsFromTracks"
 
 
def create_collector(name="SVDTimeCalibrationCollector",
                     clusters="SVDClustersFromTracks",
                     event_info="SVDEventInfo",
                     event_t0="EventT0",
                     rawBinWidth=2,
                     granularity="run",
                     minRawTimeForIoV=0.,
                     maxRawTimeForIoV=150.):
    """
    Simply creates a SVDTimeCalibrationCollector module with some options.
 
    Returns:
        pybasf2.Module
    """
 
    collector = b2.register_module("SVDTimeCalibrationCollector")
    collector.set_name(name)
    collector.param("SVDClustersFromTracksName", clusters)
    collector.param("SVDEventInfoName", event_info)
    collector.param("EventT0Name", event_t0)
    collector.param("granularity", granularity)
    collector.param("RawCoGBinWidth", rawBinWidth)
    collector.param("RawTimeIoVMin", minRawTimeForIoV)
    collector.param("RawTimeIoVMax", maxRawTimeForIoV)
 
    return collector
 
 
def create_validation_collector(name="SVDTimeValidationCollector",
                                clusters="SVDClusters",
                                clusters_onTracks="SVDClustersOnTracks",
                                event_t0="EventT0",
                                collector_module="SVDTimeValidationCollector",
                                time_algorithm="CoG6",
                                granularity="run"):
    """
    Simply creates a SVDTimeCalibrationCollector module with some options.
 
    Returns:
        pybasf2.Module
    """
 
    collector = b2.register_module(collector_module)
    collector.set_name(name)
    collector.param("SVDClustersName", clusters)
    collector.param("SVDClustersOnTracksName", clusters_onTracks)
    collector.param("EventT0Name", event_t0)
    collector.param("granularity", granularity)
    collector.param("TimeAlgorithm", time_algorithm)
    return collector
 
 
def create_algorithm(
        unique_id,
        prefix="",
        min_entries=10000,
        linearCutsOnCoG3=False,
        interceptUpperLine=-94.0,
        angularCoefficientUpperLine=1.264,
        interceptLowerLine=-134.0,
        angularCoefficientLowerLine=1.264):
    """
    Simply creates a SVDCoGTimeCalibrationAlgorithm class with some options.
 
    Returns:
        ROOT.Belle2.SVDCoGTimeCalibrationAlgorithm
    """
    from ROOT import Belle2  # noqa: make the Belle2 namespace available
    from ROOT.Belle2 import SVDCoGTimeCalibrationAlgorithm
    from ROOT.Belle2 import SVD3SampleCoGTimeCalibrationAlgorithm
    from ROOT.Belle2 import SVD3SampleELSTimeCalibrationAlgorithm
    if "CoG6" in prefix:
        algorithm = SVDCoGTimeCalibrationAlgorithm(unique_id)
    if "CoG3" in prefix:
        algorithm = SVD3SampleCoGTimeCalibrationAlgorithm(unique_id)
        algorithm.setTwoLineSelectionParameters(
            linearCutsOnCoG3,
            interceptUpperLine,
            angularCoefficientUpperLine,
            interceptLowerLine,
            angularCoefficientLowerLine)
    if "ELS3" in prefix:
        algorithm = SVD3SampleELSTimeCalibrationAlgorithm(unique_id)
    if prefix:
        algorithm.setPrefix(prefix)
    algorithm.setMinEntries(min_entries)
 
    return algorithm
 
 
def create_validation_algorithm(prefix="", min_entries=10000):
    """
    Simply creates a SVDCoGTimeValidationAlgorithm class with some options.
 
    Returns:
        ROOT.Belle2.SVDCoGTimeValidationAlgorithm
    """
    from ROOT import Belle2  # noqa: make the Belle2 namespace available
    from ROOT.Belle2 import SVDTimeValidationAlgorithm
 
    algorithm = SVDTimeValidationAlgorithm()
 
    if prefix:
        algorithm.setPrefix(prefix)
    algorithm.setMinEntries(min_entries)
 
    return algorithm
 
 
def create_svd_clusterizer(name="ClusterReconstruction",
                           clusters="SVDClustersFromTracks",
                           reco_digits=None,
                           shaper_digits=None,
                           time_algorithm="CoG6",
                           get_3sample_raw_time=False,
                           shiftSVDClusterTime=None,
                           absoluteShiftSVDClusterTime=None,
                           ):
    """
    Simply creates a SVDClusterizer module with some options.
 
    Returns:
        pybasf2.Module
    """
 
    cluster = b2.register_module("SVDClusterizer")
    cluster.set_name(name)
    cluster.param("Clusters", clusters)
    if shaper_digits is not None:
        cluster.param("ShaperDigits", shaper_digits)
    cluster.param("timeAlgorithm6Samples", time_algorithm)
    if shiftSVDClusterTime is not None:
        cluster.param("shiftSVDClusterTime", shiftSVDClusterTime)
    cluster.param("useDB", False)
    if get_3sample_raw_time:
        cluster.param("returnClusterRawTime", True)
    if absoluteShiftSVDClusterTime is not None:
        cluster.param("absoluteShiftSVDClusterTime", absoluteShiftSVDClusterTime)
    return cluster
 
 
def create_pre_collector_path(
        clusterizers,
        isMC=False,
        max_events_per_run=10000,
        max_events_per_file=10000,
        useSVDGrouping=True,
        useRawtimeForTracking=False,
        is_validation=False):
    """
    Create a basf2 path that runs a common reconstruction path and also runs several SVDSimpleClusterizer
    modules with different configurations. This way they reuse the same reconstructed objects.
 
    Parameters:
        clusterizers (list[pybasf2.Module]): All the differently configured
            SVDSimpleClusterizer modules. They should output to different datastore objects.
        max_events_per_run (int, optional): Max events read per run. Defaults to 10000.
        is_validation (bool, optional): Is used to produce the validation plots. Defaults to False.
 
    returns:
        pybasf2.Path
    """
    # Set-up re-processing path
    path = b2.create_path()
 
    # Read from file only what is needed
    if not isMC:
        path.add_module("RootInput", branchNames=HLT_INPUT_OBJECTS, entrySequences=[f'0:{max_events_per_file - 1}'])
    else:
        path.add_module("RootInput")
 
    # unpack raw data to do the tracking
    if not isMC:
        raw.add_unpackers(path, components=['PXD', 'SVD', 'CDC'])
    else:
        path.add_module("Gearbox")
        path.add_module("Geometry")
 
    # proceed only if we acquired 6-sample strips
    skim6SampleEvents = b2.register_module("SVD6SampleEventSkim")
    path.add_module(skim6SampleEvents)
    emptypath = b2.create_path()
    skim6SampleEvents.if_false(emptypath)
 
    if not isMC:
        # run tracking reconstruction
        add_tracking_reconstruction(path, append_full_grid_cdc_eventt0=True, skip_full_grid_cdc_eventt0_if_svd_time_present=False)
        path = remove_module(path, "V0Finder")
        if not is_validation:
            # if we would like using the grouping (True by default), we should use the calibrated cluster time
            # if we would like to use the raw time, than the cluster grouping parameters are OK only for CoG3
            # in the reconstruction (default in reconstruction)
            b2.set_module_parameters(path, 'SVDClusterizer', returnClusterRawTime=useRawtimeForTracking)
            if useSVDGrouping:
                if useRawtimeForTracking:
                    b2.set_module_parameters(path, 'SVDTimeGrouping',
                                             forceGroupingFromDB=False,
                                             useParamFromDB=False,
                                             isEnabledIn6Samples=True,
                                             acceptSigmaN=5,
                                             expectedSignalTimeCenter=100,
                                             expectedSignalTimeMin=70, expectedSignalTimeMax=130,
                                             tRangeLow=-20, tRangeHigh=220)
                    b2.set_module_parameters(path, 'SVDSpacePointCreator',
                                             forceGroupingFromDB=False,
                                             useParamFromDB=False,
                                             useSVDGroupInfoIn6Sample=True,
                                             numberOfSignalGroups=2, formSingleSignalGroup=True)
                else:
                    b2.set_module_parameters(path, 'SVDTimeGrouping',
                                             forceGroupingFromDB=False,
                                             useParamFromDB=False,
                                             isEnabledIn6Samples=True, acceptSigmaN=3,
                                             expectedSignalTimeMin=-30, expectedSignalTimeMax=30)
                    b2.set_module_parameters(path, 'SVDSpacePointCreator',
                                             forceGroupingFromDB=False,
                                             useSVDGroupInfoIn6Sample=True)
            else:
                b2.set_module_parameters(path, 'SVDTimeGrouping', forceGroupingFromDB=False, isEnabledIn6Samples=False)
                b2.set_module_parameters(path, 'SVDSpacePointCreator', forceGroupingFromDB=False, useSVDGroupInfoIn6Sample=False)
 
        # repeat svd reconstruction using only SVDShaperDigitsFromTracks
        path.add_module("SVDShaperDigitsFromTracks")
 
    for cluster in clusterizers:
        path.add_module(cluster)
 
    path = remove_module(path, "SVDMissingAPVsClusterCreator")
 
    return path
 
 
def get_calibrations(input_data, **kwargs):
 
    from ROOT import Belle2  # noqa: make the Belle2 namespace available
    from ROOT.Belle2 import SVDClusterTimeShifterAlgorithm, SVDClusterAbsoluteTimeShifterAlgorithm
 
    file_to_iov_physics = input_data["hadron_calib"]
    expert_config = kwargs.get("expert_config")
    timeAlgorithms = expert_config["timeAlgorithms"]
    listOfMutedCalibrations = expert_config["listOfMutedCalibrations"]
    max_events_per_run = expert_config["max_events_per_run"]  # Maximum number of events selected per each run
    max_events_per_file = expert_config["max_events_per_file"]  # Maximum number of events selected per each file
    isMC = expert_config["isMC"]
    linearCutsOnCoG3 = expert_config["linearCutsOnCoG3"]
    upperLineParameters = expert_config["upperLineParameters"]
    lowerLineParameters = expert_config["lowerLineParameters"]
    rangeRawTimeForIoVCoG6 = expert_config["rangeRawTimeForIoVCoG6"]
    rangeRawTimeForIoVCoG3 = expert_config["rangeRawTimeForIoVCoG3"]
    rangeRawTimeForIoVELS3 = expert_config["rangeRawTimeForIoVELS3"]
    useSVDGrouping = expert_config["useSVDGrouping"]
    useRawtimeForTracking = expert_config["useRawtimeForTracking"]
 
    reduced_file_to_iov_physics = filter_by_max_events_per_run(file_to_iov_physics,
                                                               max_events_per_run, random_select=True,
                                                               max_events_per_file=max_events_per_file)
    good_input_files = list(reduced_file_to_iov_physics.keys())
 
    b2.B2INFO(f"Total number of files used as input = {len(good_input_files)}")
 
    exps = [i.exp_low for i in reduced_file_to_iov_physics.values()]
    runs = sorted([i.run_low for i in reduced_file_to_iov_physics.values()])
 
    firstRun = runs[0]
    lastRun = runs[-1]
    expNum = exps[0]
 
    if not len(good_input_files):
        print("No good input files found! Check that the input files have entries != 0!")
        sys.exit(1)
 
    cog6_suffix = "_CoG6"
    cog3_suffix = "_CoG3"
    els3_suffix = "_ELS3"
 
    calType = "Prompt"
    if isMC:
        calType = "MC"
    unique_id_cog6 = f"SVDCoGTimeCalibrations_{calType}_{now.isoformat()}_INFO:_3rdOrderPol_TBindep_" \
        f"Exp{expNum}_runsFrom{firstRun}to{lastRun}"
    print(f"\nUniqueID_CoG6:\n{unique_id_cog6}")
 
    unique_id_cog3 = f"SVD3SampleCoGTimeCalibrations_{calType}_{now.isoformat()}_INFO:_3rdOrderPol_TBindep_" \
        f"Exp{expNum}_runsFrom{firstRun}to{lastRun}"
    print(f"\nUniqueID_CoG3:\n{unique_id_cog3}")
 
    unique_id_els3 = f"SVD3SampleELSTimeCalibrations_{calType}_{now.isoformat()}_INFO:_TBindep_" \
        f"Exp{expNum}_runsFrom{firstRun}to{lastRun}"
    print(f"\nUniqueID_ELS3:\n{unique_id_els3}")
 
    requested_iov = kwargs.get("requested_iov", None)
    output_iov = IoV(requested_iov.exp_low, requested_iov.run_low, -1, -1)
 
    
    list_of_calibrations = []
 
    
 
    cog6 = create_svd_clusterizer(
        name=f"ClusterReconstruction{cog6_suffix}",
        clusters=f"SVDClustersFromTracks{cog6_suffix}",
        reco_digits=NEW_RECO_DIGITS_NAME,
        shaper_digits=NEW_SHAPER_DIGITS_NAME,
        time_algorithm="CoG6",
        get_3sample_raw_time=True)
 
    cog3 = create_svd_clusterizer(
        name=f"ClusterReconstruction{cog3_suffix}",
        clusters=f"SVDClustersFromTracks{cog3_suffix}",
        reco_digits=NEW_RECO_DIGITS_NAME,
        shaper_digits=NEW_SHAPER_DIGITS_NAME,
        time_algorithm="CoG3",
        get_3sample_raw_time=True)
 
    els3 = create_svd_clusterizer(
        name=f"ClusterReconstruction{els3_suffix}",
        clusters=f"SVDClustersFromTracks{els3_suffix}",
        reco_digits=NEW_RECO_DIGITS_NAME,
        shaper_digits=NEW_SHAPER_DIGITS_NAME,
        time_algorithm="ELS3",
        get_3sample_raw_time=True)
 
    
    eventInfo = "SVDEventInfo"
    if isMC:
        eventInfo = "SVDEventInfoSim"
 
    coll_cog6 = create_collector(
        name=f"SVDTimeCalibrationCollector{cog6_suffix}",
        clusters=f"SVDClustersFromTracks{cog6_suffix}",
        event_info=eventInfo,
        event_t0="EventT0",
        minRawTimeForIoV=rangeRawTimeForIoVCoG6[0],
        maxRawTimeForIoV=rangeRawTimeForIoVCoG6[1])
 
    algo_cog6 = create_algorithm(
        unique_id_cog6,
        prefix=coll_cog6.name(),
        min_entries=10000)
 
    coll_cog3 = create_collector(
        name=f"SVDTimeCalibrationCollector{cog3_suffix}",
        clusters=f"SVDClustersFromTracks{cog3_suffix}",
        event_info=eventInfo,
        rawBinWidth=1,
        event_t0="EventT0",
        minRawTimeForIoV=rangeRawTimeForIoVCoG3[0],
        maxRawTimeForIoV=rangeRawTimeForIoVCoG3[1])
 
    algo_cog3 = create_algorithm(
        unique_id_cog3,
        prefix=coll_cog3.name(),
        min_entries=10000,
        linearCutsOnCoG3=linearCutsOnCoG3,
        interceptUpperLine=upperLineParameters[0],
        angularCoefficientUpperLine=upperLineParameters[1],
        interceptLowerLine=lowerLineParameters[0],
        angularCoefficientLowerLine=lowerLineParameters[1])
 
    coll_els3 = create_collector(
        name=f"SVDTimeCalibrationCollector{els3_suffix}",
        clusters=f"SVDClustersFromTracks{els3_suffix}",
        event_info=eventInfo,
        event_t0="EventT0",
        minRawTimeForIoV=rangeRawTimeForIoVELS3[0],
        maxRawTimeForIoV=rangeRawTimeForIoVELS3[1])
 
    algo_els3 = create_algorithm(
        unique_id_els3,
        prefix=coll_els3.name(),
        min_entries=10000)
 
    
 
    # Check what time algorithms (CoG6, CoG3, ELS3) will be calibrated according to expert input
    list_of_clusterizers = []
    list_of_algorithms = []
    for a in timeAlgorithms:
        if a == "CoG3":
            list_of_clusterizers.append(cog3)
            list_of_algorithms.append(algo_cog3)
        if a == "CoG6":
            list_of_clusterizers.append(cog6)
            list_of_algorithms.append(algo_cog6)
        if a == "ELS3":
            list_of_clusterizers.append(els3)
            list_of_algorithms.append(algo_els3)
 
    pre_collector_path = create_pre_collector_path(
        clusterizers=list_of_clusterizers,
        isMC=isMC, max_events_per_run=max_events_per_run,
        max_events_per_file=max_events_per_file,
        useSVDGrouping=useSVDGrouping, useRawtimeForTracking=useRawtimeForTracking)
 
    # Decide what collector will be "managed" by the CAF
    collector_managed_by_CAF = coll_els3
    if "ELS3" in timeAlgorithms:
        collector_managed_by_CAF = coll_els3
        if "CoG6" in timeAlgorithms:
            pre_collector_path.add_module(coll_cog6)
        if "CoG3" in timeAlgorithms:
            pre_collector_path.add_module(coll_cog3)
    # We leave the coll_els3 to be the one "managed" by the CAF
 
    elif "CoG3" in timeAlgorithms:
        collector_managed_by_CAF = coll_cog3
        if "CoG6" in timeAlgorithms:
            pre_collector_path.add_module(coll_cog6)
    else:
        collector_managed_by_CAF = coll_cog6
 
    # calibration setup
    calibration = Calibration("SVDTime",
                              collector=collector_managed_by_CAF,  # The other collectors are in the pre_collector_path itself
                              algorithms=list_of_algorithms,
                              input_files=good_input_files,
                              pre_collector_path=pre_collector_path)
 
    calibration.strategies = strategies.SequentialBoundaries
 
    for algorithm in calibration.algorithms:
        algorithm.params = {"iov_coverage": output_iov}
 
    if "rawTimeCalibration" not in listOfMutedCalibrations:
        list_of_calibrations.append(calibration)
 
    
 
    SVDClustersOnTrackPrefix = "SVDClustersOnTrack"
 
    shift_clusterizers_onTracks = []
    for alg in timeAlgorithms:
        cluster = create_svd_clusterizer(
            name=f"ClusterReconstruction_{alg}",
            clusters=f"{SVDClustersOnTrackPrefix}_{alg}",
            shaper_digits=NEW_SHAPER_DIGITS_NAME,
            time_algorithm=alg,
            shiftSVDClusterTime=False)
        shift_clusterizers_onTracks.append(cluster)
 
    shift_pre_collector_path = create_pre_collector_path(
        clusterizers=shift_clusterizers_onTracks,
        isMC=isMC, max_events_per_run=max_events_per_run,
        max_events_per_file=max_events_per_file,
        useSVDGrouping=useSVDGrouping)
 
    shift_collector = b2.register_module("SVDClusterTimeShifterCollector")
    shift_collector.set_name("SVDClusterTimeShifterCollector")
    shift_collector.param("MaxClusterSize", 6)
    shift_collector.param("EventT0Name", "EventT0")
    shift_collector.param("SVDClustersOnTrackPrefix", f"{SVDClustersOnTrackPrefix}")
    shift_collector.param("TimeAlgorithms", timeAlgorithms)
 
    shift_algo = SVDClusterTimeShifterAlgorithm(f"{calType}_{now.isoformat()}_INFO:_"
                                                f"Exp{expNum}_runsFrom{firstRun}to{lastRun}")
    shift_algo.setMinEntries(100)
    shift_algo.setMaximumAllowedShift(15.)
    shift_algo.setTimeAlgorithm(timeAlgorithms)
 
    shift_calibration = Calibration("SVDClusterTimeShifter",
                                    collector=shift_collector,
                                    algorithms=shift_algo,
                                    input_files=good_input_files,
                                    pre_collector_path=shift_pre_collector_path)
 
    shift_calibration.strategies = strategies.SingleIOV
 
    for algorithm in shift_calibration.algorithms:
        algorithm.params = {"apply_iov": output_iov}
 
    if "timeShiftCalibration" not in listOfMutedCalibrations:
        list_of_calibrations.append(shift_calibration)
 
    
 
    SVDClustersOnTrackPrefix = "SVDClustersOnTrack"
 
    absolute_shift_clusterizers_onTracks = []
 
    for alg in timeAlgorithms:
        cluster = create_svd_clusterizer(
            name=f"ClusterReconstruction_{alg}",
            clusters=f"{SVDClustersOnTrackPrefix}_{alg}",
            shaper_digits=NEW_SHAPER_DIGITS_NAME,
            time_algorithm=alg,
            absoluteShiftSVDClusterTime=False,
            )
        absolute_shift_clusterizers_onTracks.append(cluster)
 
    absolute_shift_pre_collector_path = create_pre_collector_path(
        clusterizers=absolute_shift_clusterizers_onTracks,
        isMC=isMC, max_events_per_run=max_events_per_run,
        max_events_per_file=max_events_per_file,
        useSVDGrouping=useSVDGrouping)
 
    absolute_shift_collector = b2.register_module("SVDClusterAbsoluteTimeShifterCollector")
    absolute_shift_collector.set_name("SVDClusterAbsoluteTimeShifterCollector")
    absolute_shift_collector.param("EventT0Name", "EventT0")
    absolute_shift_collector.param("SVDClustersOnTrackPrefix", f"{SVDClustersOnTrackPrefix}")
    absolute_shift_collector.param("TimeAlgorithms", timeAlgorithms)
 
    absolute_shift_algo = SVDClusterAbsoluteTimeShifterAlgorithm(f"{calType}_{now.isoformat()}_INFO:_"
                                                                 f"Exp{expNum}_runsFrom{firstRun}to{lastRun}")
    absolute_shift_algo.setMinEntries(100)
    absolute_shift_algo.setMaximumAllowedShift(15.)
    absolute_shift_algo.setTimeAlgorithm(timeAlgorithms)
    print(f'Time algorithms for absolute shift: {timeAlgorithms}')
    absolute_shift_calibration = Calibration("SVDClusterAbsoluteTimeShift",
                                             collector=absolute_shift_collector,
                                             algorithms=absolute_shift_algo,
                                             input_files=good_input_files,
                                             pre_collector_path=absolute_shift_pre_collector_path)
 
    absolute_shift_calibration.strategies = strategies.SequentialBoundaries
 
    for algorithm in absolute_shift_calibration.algorithms:
        algorithm.params = {"apply_iov": output_iov}
        if "AbsoluteTimeShiftCalibration" not in listOfMutedCalibrations:
            list_of_calibrations.append(absolute_shift_calibration)
 
    
 
    val_cog6 = create_svd_clusterizer(
        name=f"ClusterReconstruction{cog6_suffix}",
        clusters=f"SVDClusters{cog6_suffix}",
        time_algorithm="CoG6")
 
    val_cog6_onTracks = create_svd_clusterizer(
        name=f"ClusterReconstruction{cog6_suffix}_onTracks",
        clusters=f"SVDClusters{cog6_suffix}_onTracks",
        reco_digits=NEW_RECO_DIGITS_NAME,
        shaper_digits=NEW_SHAPER_DIGITS_NAME,
        time_algorithm="CoG6")
 
    val_cog3 = create_svd_clusterizer(
        name=f"ClusterReconstruction{cog3_suffix}",
        clusters=f"SVDClusters{cog3_suffix}",
        time_algorithm="CoG3")
 
    val_cog3_onTracks = create_svd_clusterizer(
        name=f"ClusterReconstruction{cog3_suffix}_onTracks",
        clusters=f"SVDClusters{cog3_suffix}_onTracks",
        reco_digits=NEW_RECO_DIGITS_NAME,
        shaper_digits=NEW_SHAPER_DIGITS_NAME,
        time_algorithm="CoG3")
 
    val_els3 = create_svd_clusterizer(
        name=f"ClusterReconstruction{els3_suffix}",
        clusters=f"SVDClusters{els3_suffix}",
        time_algorithm="ELS3")
 
    val_els3_onTracks = create_svd_clusterizer(
        name=f"ClusterReconstruction{els3_suffix}_onTracks",
        clusters=f"SVDClusters{els3_suffix}_onTracks",
        reco_digits=NEW_RECO_DIGITS_NAME,
        shaper_digits=NEW_SHAPER_DIGITS_NAME,
        time_algorithm="ELS3")
 
    val_coll_cog6 = create_validation_collector(
        name=f"SVDTimeValidationCollector{cog6_suffix}",
        clusters=f"SVDClusters{cog6_suffix}",
        clusters_onTracks=f"SVDClusters{cog6_suffix}_onTracks",
        event_t0="EventT0",
        time_algorithm="CoG6")
 
    val_algo_cog6 = create_validation_algorithm(
        prefix=val_coll_cog6.name(),
        min_entries=10000)
 
    val_coll_cog3 = create_validation_collector(
        name=f"SVDTimeValidationCollector{cog3_suffix}",
        clusters=f"SVDClusters{cog3_suffix}",
        clusters_onTracks=f"SVDClusters{cog3_suffix}_onTracks",
        event_t0="EventT0",
        time_algorithm="CoG3")
 
    val_algo_cog3 = create_validation_algorithm(
        prefix=val_coll_cog3.name(),
        min_entries=10000)
 
    val_coll_els3 = create_validation_collector(
        name=f"SVDTimeValidationCollector{els3_suffix}",
        clusters=f"SVDClusters{els3_suffix}",
        clusters_onTracks=f"SVDClusters{els3_suffix}_onTracks",
        event_t0="EventT0",
        time_algorithm="ELS3")
 
    val_algo_els3 = create_validation_algorithm(
        prefix=val_coll_els3.name(),
        min_entries=10000)
 
    list_of_val_clusterizers = []
    list_of_val_algorithms = []
    for a in timeAlgorithms:
        if a == "CoG3":
            list_of_val_clusterizers.append(val_cog3)
            list_of_val_clusterizers.append(val_cog3_onTracks)
            list_of_val_algorithms.append(val_algo_cog3)
        if a == "CoG6":
            list_of_val_clusterizers.append(val_cog6)
            list_of_val_clusterizers.append(val_cog6_onTracks)
            list_of_val_algorithms.append(val_algo_cog6)
        if a == "ELS3":
            list_of_val_clusterizers.append(val_els3)
            list_of_val_clusterizers.append(val_els3_onTracks)
            list_of_val_algorithms.append(val_algo_els3)
 
    val_pre_collector_path = create_pre_collector_path(
        clusterizers=list_of_val_clusterizers,
        isMC=isMC, max_events_per_run=max_events_per_run,
        max_events_per_file=max_events_per_file,
        useSVDGrouping=useSVDGrouping, useRawtimeForTracking=useRawtimeForTracking,
        is_validation=True)
 
    val_collector_managed_by_CAF = val_coll_els3
    if "ELS3" in timeAlgorithms:
        val_collector_managed_by_CAF = val_coll_els3
        if "CoG6" in timeAlgorithms:
            val_pre_collector_path.add_module(val_coll_cog6)
        if "CoG3" in timeAlgorithms:
            val_pre_collector_path.add_module(val_coll_cog3)
    elif "CoG3" in timeAlgorithms:
        val_collector_managed_by_CAF = val_coll_cog3
        if "CoG6" in timeAlgorithms:
            val_pre_collector_path.add_module(val_coll_cog6)
    else:
        val_collector_managed_by_CAF = val_coll_cog6
 
    val_calibration = Calibration("SVDTimeValidation",
                                  collector=val_collector_managed_by_CAF,
                                  algorithms=list_of_val_algorithms,
                                  input_files=good_input_files,
                                  pre_collector_path=val_pre_collector_path)
 
    for algorithm in val_calibration.algorithms:
        algorithm.params = {"iov_coverage": output_iov}
 
    if "timeValidation" not in listOfMutedCalibrations:
        list_of_calibrations.append(val_calibration)
 
    print(f'List of calib: {list_of_calibrations}')
    for item in range(len(list_of_calibrations) - 1):
        # Absolute time shift calibration does not depend on any other calibration
        print(f'Item: {item}')
        print(f'calib item: {list_of_calibrations[item]}')
        print(f'name of calib item: {list_of_calibrations[item].name}')
 
        print(f'calibration name: {list_of_calibrations[item].name}')
        if "AbsoluteTimeShiftCalibration" in list_of_calibrations[item].name:
            if len(list_of_calibrations) > 1:
                print(" WARNING : AbsoluteTimeShiftCalibration should not depend on any other calibration.")
                print("Not setting dependencies to or from other calibrations.")
            continue
        #  and make sure no other calibration depends on it
        elif "AbsoluteTimeShiftCalibration" in list_of_calibrations[item + 1].name:
            # if item + 1 is not the last calibration in the list
            if item + 1 < len(list_of_calibrations) - 1:
                #  set the dependency to the next one
                list_of_calibrations[item + 2].depends_on(list_of_calibrations[item])
            #  no else because in this case it's the last calibration in the list
        else:
            list_of_calibrations[item + 1].depends_on(list_of_calibrations[item])
 
    return list_of_calibrations