コード例 #1
0
ファイル: cgm2_1.py プロジェクト: sremm/pyCGM2
def fitting(model,DATA_PATH, reconstructFilenameLabelled,
    translators,
    markerDiameter,
    pointSuffix,
    mfpa,
    momentProjection,**kwargs):

    """
    Fitting of the CGM2.1

    :param model [str]: pyCGM2 model previously calibrated
    :param DATA_PATH [str]: path to your data
    :param reconstructFilenameLabelled [string list]: c3d files
    :param translators [dict]:  translators to apply
    :param mfpa [str]: manual force plate assignement
    :param markerDiameter [double]: marker diameter (mm)
    :param pointSuffix [str]: suffix to add to model outputs
    :param momentProjection [str]: Coordinate system in which joint moment is expressed
    """

    detectAnomaly = False
    if "anomalyException" in kwargs.keys():
        anomalyException = kwargs["anomalyException"]
    else:
        anomalyException=False
    # --------------------------ACQUISITION ------------------------------------

    # --- btk acquisition ----
    if "forceBtkAcq" in kwargs.keys():
        acqGait = kwargs["forceBtkAcq"]
    else:
        acqGait = btkTools.smartReader((DATA_PATH + reconstructFilenameLabelled))

    btkTools.checkMultipleSubject(acqGait)
    if btkTools.isPointExist(acqGait,"SACR"):
        translators["LPSI"] = "SACR"
        translators["RPSI"] = "SACR"
        LOGGER.logger.info("[pyCGM2] Sacrum marker detected")

    acqGait =  btkTools.applyTranslators(acqGait,translators)

    trackingMarkers = cgm.CGM1.LOWERLIMB_TRACKING_MARKERS + cgm.CGM1.THORAX_TRACKING_MARKERS+ cgm.CGM1.UPPERLIMB_TRACKING_MARKERS
    actual_trackingMarkers,phatoms_trackingMarkers = btkTools.createPhantoms(acqGait, trackingMarkers)

    vff,vlf = btkTools.getFrameBoundaries(acqGait,actual_trackingMarkers)
    if "frameInit" in kwargs.keys() and kwargs["frameInit"] is not None:
        vff = kwargs["frameInit"]
        LOGGER.logger.info("[pyCGM2]  first frame forced to frame [%s]"%(vff))
    if "frameEnd" in kwargs.keys() and kwargs["frameEnd"] is not None:
        vlf = kwargs["frameEnd"]
        LOGGER.logger.info("[pyCGM2]  end frame forced to frame [%s]"%(vlf))

    flag = btkTools.getValidFrames(acqGait,actual_trackingMarkers,frameBounds=[vff,vlf])

    LOGGER.logger.info("[pyCGM2]  Computation from frame [%s] to frame [%s]"%(vff,vlf))

    # --------------------ANOMALY------------------------------
    for marker in actual_trackingMarkers:
        if marker not in model.getStaticTrackingMarkers():
            LOGGER.logger.warning("[pyCGM2-Anomaly]  marker [%s] - not used during static calibration - wrong kinematic for the segment attached to this marker. "%(marker))

    # --marker presence
    markersets = [cgm.CGM1.LOWERLIMB_TRACKING_MARKERS, cgm.CGM1.THORAX_TRACKING_MARKERS, cgm.CGM1.UPPERLIMB_TRACKING_MARKERS]
    for markerset in markersets:
        ipdp = InspectorProcedure.MarkerPresenceDetectionProcedure( markerset)
        idf = InspectorFilter.InspectorFilter(acqGait,reconstructFilenameLabelled,ipdp)
        inspector = idf.run()

        # --marker outliers
        if inspector["In"] !=[]:
            madp = AnomalyDetectionProcedure.MarkerAnomalyDetectionRollingProcedure( inspector["In"], plot=False, window=5,threshold = 3)
            adf = AnomalyFilter.AnomalyDetectionFilter(acqGait,reconstructFilenameLabelled,madp, frameRange=[vff,vlf])
            anomaly = adf.run()
            anomalyIndexes = anomaly["Output"]
            if anomaly["ErrorState"]: detectAnomaly = True


    if btkTools.checkForcePlateExist(acqGait):
        afpp = AnomalyDetectionProcedure.ForcePlateAnomalyProcedure()
        adf = AnomalyFilter.AnomalyDetectionFilter(acqGait,reconstructFilenameLabelled,afpp, frameRange=[vff,vlf])
        anomaly = adf.run()
        if anomaly["ErrorState"]: detectAnomaly = True

    if detectAnomaly and anomalyException:
        raise Exception ("Anomalies has been detected - Check Warning message of the log file")

   # --------------------MODELLING------------------------------

    # filtering
    # -----------------------
    if "fc_lowPass_marker" in kwargs.keys() and kwargs["fc_lowPass_marker"]!=0 :
        fc = kwargs["fc_lowPass_marker"]
        order = 4
        if "order_lowPass_marker" in kwargs.keys():
            order = kwargs["order_lowPass_marker"]
        signal_processing.markerFiltering(acqGait,trackingMarkers,order=order, fc =fc)

    if "fc_lowPass_forcePlate" in kwargs.keys() and kwargs["fc_lowPass_forcePlate"]!=0 :
        fc = kwargs["fc_lowPass_forcePlate"]
        order = 4
        if "order_lowPass_forcePlate" in kwargs.keys():
            order = kwargs["order_lowPass_forcePlate"]
        signal_processing.forcePlateFiltering(acqGait,order=order, fc =fc)



    scp=modelFilters.StaticCalibrationProcedure(model)
    # ---Motion filter----
    modMotion=modelFilters.ModelMotionFilter(scp,acqGait,model,enums.motionMethod.Determinist,
                                              markerDiameter=markerDiameter)

    modMotion.compute()

    progressionFlag = False
    if btkTools.isPointExist(acqGait, 'LHEE',ignorePhantom=False) or btkTools.isPointExist(acqGait, 'RHEE',ignorePhantom=False):

        pfp = progressionFrame.PointProgressionFrameProcedure(marker="LHEE") \
            if btkTools.isPointExist(acqGait, 'LHEE',ignorePhantom=False) \
            else  progressionFrame.PointProgressionFrameProcedure(marker="RHEE")

        pff = progressionFrame.ProgressionFrameFilter(acqGait,pfp)
        pff.compute()
        progressionAxis = pff.outputs["progressionAxis"]
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]
        progressionFlag = True

    elif btkTools.isPointsExist(acqGait, ['LASI', 'RASI', 'RPSI', 'LPSI'],ignorePhantom=False) and not progressionFlag:
        LOGGER.logger.info("[pyCGM2] - progression axis detected from Pelvic markers ")
        pfp = progressionFrame.PelvisProgressionFrameProcedure()
        pff = progressionFrame.ProgressionFrameFilter(acqGait,pfp)
        pff.compute()
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]

        progressionFlag = True
    elif btkTools.isPointsExist(acqGait, ['C7', 'T10', 'CLAV', 'STRN'],ignorePhantom=False) and not progressionFlag:
        LOGGER.logger.info("[pyCGM2] - progression axis detected from Thoracic markers ")
        pfp = progressionFrame.ThoraxProgressionFrameProcedure()
        pff = progressionFrame.ProgressionFrameFilter(acqGait,pfp)
        pff.compute()
        progressionAxis = pff.outputs["progressionAxis"]
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]

    else:
        globalFrame = "XYZ"
        progressionAxis = "X"
        forwardProgression = True
        LOGGER.logger.error("[pyCGM2] - impossible to detect progression axis - neither pelvic nor thoracic markers are present. Progression set to +X by default ")

    if "displayCoordinateSystem" in kwargs.keys() and kwargs["displayCoordinateSystem"]:
        csp = modelFilters.ModelCoordinateSystemProcedure(model)
        csdf = modelFilters.CoordinateSystemDisplayFilter(csp,model,acqGait)
        csdf.setStatic(False)
        csdf.display()

    #---- Joint kinematics----
    # relative angles
    modelFilters.ModelJCSFilter(model,acqGait).compute(description="vectoriel", pointLabelSuffix=pointSuffix)

    modelFilters.ModelAbsoluteAnglesFilter(model,acqGait,
                                           segmentLabels=["Left Foot","Right Foot","Pelvis","Thorax","Head"],
                                            angleLabels=["LFootProgress", "RFootProgress","Pelvis","Thorax", "Head"],
                                            eulerSequences=["TOR","TOR", "ROT","YXZ","TOR"],
                                            globalFrameOrientation = globalFrame,
                                            forwardProgression = forwardProgression).compute(pointLabelSuffix=pointSuffix)

    #---- Body segment parameters----
    bspModel = bodySegmentParameters.Bsp(model)
    bspModel.compute()

    modelFilters.CentreOfMassFilter(model,acqGait).compute(pointLabelSuffix=pointSuffix)

    # Inverse dynamics
    if btkTools.checkForcePlateExist(acqGait):
        if model.m_bodypart != enums.BodyPart.UpperLimb:
            # --- force plate handling----
            # find foot  in contact
            mappedForcePlate = forceplates.matchingFootSideOnForceplate(acqGait,mfpa=mfpa)
            forceplates.addForcePlateGeneralEvents(acqGait,mappedForcePlate)
            LOGGER.logger.info("Manual Force plate assignment : %s" %mappedForcePlate)

            # assembly foot and force plate
            modelFilters.ForcePlateAssemblyFilter(model,acqGait,mappedForcePlate,
                                     leftSegmentLabel="Left Foot",
                                     rightSegmentLabel="Right Foot").compute(pointLabelSuffix=pointSuffix)

            #---- Joint kinetics----
            idp = modelFilters.CGMLowerlimbInverseDynamicProcedure()
            modelFilters.InverseDynamicFilter(model,
                                 acqGait,
                                 procedure = idp,
                                 projection = momentProjection,
                                 globalFrameOrientation = globalFrame,
                                 forwardProgression = forwardProgression
                                 ).compute(pointLabelSuffix=pointSuffix)


            #---- Joint energetics----
            modelFilters.JointPowerFilter(model,acqGait).compute(pointLabelSuffix=pointSuffix)

    btkTools.cleanAcq(acqGait)
    btkTools.applyOnValidFrames(acqGait,flag)

    if detectAnomaly and not anomalyException:
        LOGGER.logger.error("Anomalies has been detected - Check Warning messages of the log file")



    return acqGait,detectAnomaly
コード例 #2
0
def fitting(model, DATA_PATH, reconstructFilenameLabelled, translators,
            weights, ik_flag, markerDiameter, pointSuffix, mfpa,
            momentProjection, **kwargs):
    """
    Fitting of the CGM2.5

    :param model [str]: pyCGM2 model previously calibrated
    :param DATA_PATH [str]: path to your data
    :param reconstructFilenameLabelled [string list]: c3d files
    :param translators [dict]:  translators to apply
    :param ik_flag [bool]: enable the inverse kinematic solver
    :param mfpa [str]: manual force plate assignement
    :param markerDiameter [double]: marker diameter (mm)
    :param pointSuffix [str]: suffix to add to model outputs
    :param momentProjection [str]: Coordinate system in which joint moment is expressed
    """

    detectAnomaly = False

    if "anomalyException" in kwargs.keys():
        anomalyException = kwargs["anomalyException"]
    else:
        anomalyException = False

    if "forceFoot6DoF" in kwargs.keys() and kwargs["forceFoot6DoF"]:
        forceFoot6DoF_flag = True
    else:
        forceFoot6DoF_flag = False

    if "Fitting" in weights.keys():
        weights = weights["Fitting"]["Weight"]

    # --- btk acquisition ----
    if "forceBtkAcq" in kwargs.keys():
        acqGait = kwargs["forceBtkAcq"]
    else:
        acqGait = btkTools.smartReader(
            (DATA_PATH + reconstructFilenameLabelled))

    btkTools.checkMultipleSubject(acqGait)
    if btkTools.isPointExist(acqGait, "SACR"):
        translators["LPSI"] = "SACR"
        translators["RPSI"] = "SACR"
        LOGGER.logger.info("[pyCGM2] Sacrum marker detected")

    acqGait = btkTools.applyTranslators(acqGait, translators)
    trackingMarkers = cgm2.CGM2_5.LOWERLIMB_TRACKING_MARKERS + cgm2.CGM2_5.THORAX_TRACKING_MARKERS + cgm2.CGM2_5.UPPERLIMB_TRACKING_MARKERS
    actual_trackingMarkers, phatoms_trackingMarkers = btkTools.createPhantoms(
        acqGait, trackingMarkers)
    vff, vlf = btkTools.getFrameBoundaries(acqGait, actual_trackingMarkers)
    if "frameInit" in kwargs.keys() and kwargs["frameInit"] is not None:
        vff = kwargs["frameInit"]
        LOGGER.logger.info("[pyCGM2]  first frame forced to frame [%s]" %
                           (vff))
    if "frameEnd" in kwargs.keys() and kwargs["frameEnd"] is not None:
        vlf = kwargs["frameEnd"]
        LOGGER.logger.info("[pyCGM2]  end frame forced to frame [%s]" % (vlf))
    flag = btkTools.getValidFrames(acqGait,
                                   actual_trackingMarkers,
                                   frameBounds=[vff, vlf])

    LOGGER.logger.info("[pyCGM2]  Computation from frame [%s] to frame [%s]" %
                       (vff, vlf))
    # --------------------ANOMALY------------------------------
    for marker in actual_trackingMarkers:
        if marker not in model.getStaticTrackingMarkers():
            LOGGER.logger.warning(
                "[pyCGM2-Anomaly]  marker [%s] - not used during static calibration - wrong kinematic for the segment attached to this marker. "
                % (marker))

    # --marker presence
    markersets = [
        cgm2.CGM2_5.LOWERLIMB_TRACKING_MARKERS,
        cgm2.CGM2_5.THORAX_TRACKING_MARKERS,
        cgm2.CGM2_5.UPPERLIMB_TRACKING_MARKERS
    ]
    for markerset in markersets:
        ipdp = InspectorProcedure.MarkerPresenceDetectionProcedure(markerset)
        idf = InspectorFilter.InspectorFilter(acqGait,
                                              reconstructFilenameLabelled,
                                              ipdp)
        inspector = idf.run()

        # --marker outliers
        if inspector["In"] != []:
            madp = AnomalyDetectionProcedure.MarkerAnomalyDetectionRollingProcedure(
                inspector["In"], plot=False, window=5, threshold=3)
            adf = AnomalyFilter.AnomalyDetectionFilter(
                acqGait,
                reconstructFilenameLabelled,
                madp,
                frameRange=[vff, vlf])
            anomaly = adf.run()
            anomalyIndexes = anomaly["Output"]
            if anomaly["ErrorState"]: detectAnomaly = True

    if btkTools.checkForcePlateExist(acqGait):
        afpp = AnomalyDetectionProcedure.ForcePlateAnomalyProcedure()
        adf = AnomalyFilter.AnomalyDetectionFilter(acqGait,
                                                   reconstructFilenameLabelled,
                                                   afpp,
                                                   frameRange=[vff, vlf])
        anomaly = adf.run()
        if anomaly["ErrorState"]: detectAnomaly = True

    if detectAnomaly and anomalyException:
        raise Exception(
            "Anomalies has been detected - Check Warning message of the log file"
        )

    # --------------------MODELLING------------------------------

    # filtering
    # -----------------------
    if "fc_lowPass_marker" in kwargs.keys(
    ) and kwargs["fc_lowPass_marker"] != 0:
        fc = kwargs["fc_lowPass_marker"]
        order = 4
        if "order_lowPass_marker" in kwargs.keys():
            order = kwargs["order_lowPass_marker"]
        signal_processing.markerFiltering(acqGait,
                                          trackingMarkers,
                                          order=order,
                                          fc=fc)

    if "fc_lowPass_forcePlate" in kwargs.keys(
    ) and kwargs["fc_lowPass_forcePlate"] != 0:
        fc = kwargs["fc_lowPass_forcePlate"]
        order = 4
        if "order_lowPass_forcePlate" in kwargs.keys():
            order = kwargs["order_lowPass_forcePlate"]
        signal_processing.forcePlateFiltering(acqGait, order=order, fc=fc)

    # --- initial motion Filter ---
    scp = modelFilters.StaticCalibrationProcedure(model)
    modMotion = modelFilters.ModelMotionFilter(scp, acqGait, model,
                                               enums.motionMethod.Sodervisk)
    modMotion.compute()

    progressionFlag = False
    if btkTools.isPointExist(acqGait, 'LHEE',
                             ignorePhantom=False) or btkTools.isPointExist(
                                 acqGait, 'RHEE', ignorePhantom=False):

        pfp = progressionFrame.PointProgressionFrameProcedure(marker="LHEE") \
            if btkTools.isPointExist(acqGait, 'LHEE',ignorePhantom=False) \
            else  progressionFrame.PointProgressionFrameProcedure(marker="RHEE")

        pff = progressionFrame.ProgressionFrameFilter(acqGait, pfp)
        pff.compute()
        progressionAxis = pff.outputs["progressionAxis"]
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]
        progressionFlag = True

    elif btkTools.isPointsExist(acqGait, ['LASI', 'RASI', 'RPSI', 'LPSI'],
                                ignorePhantom=False) and not progressionFlag:
        LOGGER.logger.info(
            "[pyCGM2] - progression axis detected from Pelvic markers ")
        pfp = progressionFrame.PelvisProgressionFrameProcedure()
        pff = progressionFrame.ProgressionFrameFilter(acqGait, pfp)
        pff.compute()
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]

        progressionFlag = True
    elif btkTools.isPointsExist(acqGait, ['C7', 'T10', 'CLAV', 'STRN'],
                                ignorePhantom=False) and not progressionFlag:
        LOGGER.logger.info(
            "[pyCGM2] - progression axis detected from Thoracic markers ")
        pfp = progressionFrame.ThoraxProgressionFrameProcedure()
        pff = progressionFrame.ProgressionFrameFilter(acqGait, pfp)
        pff.compute()
        progressionAxis = pff.outputs["progressionAxis"]
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]

    else:
        globalFrame = "XYZ"
        progressionAxis = "X"
        forwardProgression = True
        LOGGER.logger.error(
            "[pyCGM2] - impossible to detect progression axis - neither pelvic nor thoracic markers are present. Progression set to +X by default "
        )

    for target in weights.keys():
        if target not in actual_trackingMarkers or target not in model.getStaticIkTargets(
        ):
            weights[target] = 0
            LOGGER.logger.warning(
                "[pyCGM2] - the IK targeted marker [%s] is not labelled in the acquisition [%s]"
                % (target, reconstructFilenameLabelled))

    if ik_flag:
        #                        ---OPENSIM IK---

        # --- opensim calibration Filter ---
        osimfile = pyCGM2.OPENSIM_PREBUILD_MODEL_PATH + "models\\osim\\lowerLimb_ballsJoints.osim"  # osimfile
        markersetFile = pyCGM2.OPENSIM_PREBUILD_MODEL_PATH + "models\\settings\\cgm2_4\\cgm2_4-markerset.xml"  # markerset
        cgmCalibrationprocedure = opensimFilters.CgmOpensimCalibrationProcedures(
            model)  # procedure

        oscf = opensimFilters.opensimCalibrationFilter(
            osimfile, model, cgmCalibrationprocedure, DATA_PATH)
        oscf.addMarkerSet(markersetFile)
        scalingOsim = oscf.build()

        # --- opensim Fitting Filter ---
        iksetupFile = pyCGM2.OPENSIM_PREBUILD_MODEL_PATH + "models\\settings\\cgm2_4\\cgm2_4-ikSetUp_template.xml"  # ik tl file

        cgmFittingProcedure = opensimFilters.CgmOpensimFittingProcedure(
            model)  # procedure
        cgmFittingProcedure.updateMarkerWeight("LASI", weights["LASI"])
        cgmFittingProcedure.updateMarkerWeight("RASI", weights["RASI"])
        cgmFittingProcedure.updateMarkerWeight("LPSI", weights["LPSI"])
        cgmFittingProcedure.updateMarkerWeight("RPSI", weights["RPSI"])
        cgmFittingProcedure.updateMarkerWeight("RTHI", weights["RTHI"])
        cgmFittingProcedure.updateMarkerWeight("RKNE", weights["RKNE"])
        cgmFittingProcedure.updateMarkerWeight("RTIB", weights["RTIB"])
        cgmFittingProcedure.updateMarkerWeight("RANK", weights["RANK"])
        cgmFittingProcedure.updateMarkerWeight("RHEE", weights["RHEE"])
        cgmFittingProcedure.updateMarkerWeight("RTOE", weights["RTOE"])

        cgmFittingProcedure.updateMarkerWeight("LTHI", weights["LTHI"])
        cgmFittingProcedure.updateMarkerWeight("LKNE", weights["LKNE"])
        cgmFittingProcedure.updateMarkerWeight("LTIB", weights["LTIB"])
        cgmFittingProcedure.updateMarkerWeight("LANK", weights["LANK"])
        cgmFittingProcedure.updateMarkerWeight("LHEE", weights["LHEE"])
        cgmFittingProcedure.updateMarkerWeight("LTOE", weights["LTOE"])

        cgmFittingProcedure.updateMarkerWeight("LTHAP", weights["LTHAP"])
        cgmFittingProcedure.updateMarkerWeight("LTHAD", weights["LTHAD"])
        cgmFittingProcedure.updateMarkerWeight("LTIAP", weights["LTIAP"])
        cgmFittingProcedure.updateMarkerWeight("LTIAD", weights["LTIAD"])
        cgmFittingProcedure.updateMarkerWeight("RTHAP", weights["RTHAP"])
        cgmFittingProcedure.updateMarkerWeight("RTHAD", weights["RTHAD"])
        cgmFittingProcedure.updateMarkerWeight("RTIAP", weights["RTIAP"])
        cgmFittingProcedure.updateMarkerWeight("RTIAD", weights["RTIAD"])

        cgmFittingProcedure.updateMarkerWeight("LSMH", weights["LSMH"])
        cgmFittingProcedure.updateMarkerWeight("LFMH", weights["LFMH"])
        cgmFittingProcedure.updateMarkerWeight("LVMH", weights["LVMH"])

        cgmFittingProcedure.updateMarkerWeight("RSMH", weights["RSMH"])
        cgmFittingProcedure.updateMarkerWeight("RFMH", weights["RFMH"])
        cgmFittingProcedure.updateMarkerWeight("RVMH", weights["RVMH"])

        #       cgmFittingProcedure.updateMarkerWeight("LTHL",weights["LTHL"])
        #       cgmFittingProcedure.updateMarkerWeight("LTHLD",weights["LTHLD"])
        #       cgmFittingProcedure.updateMarkerWeight("LPAT",weights["LPAT"])
        #       cgmFittingProcedure.updateMarkerWeight("LTIBL",weights["LTIBL"])
        #       cgmFittingProcedure.updateMarkerWeight("RTHL",weights["RTHL"])
        #       cgmFittingProcedure.updateMarkerWeight("RTHLD",weights["RTHLD"])
        #       cgmFittingProcedure.updateMarkerWeight("RPAT",weights["RPAT"])
        #       cgmFittingProcedure.updateMarkerWeight("RTIBL",weights["RTIBL"])

        osrf = opensimFilters.opensimFittingFilter(iksetupFile, scalingOsim,
                                                   cgmFittingProcedure,
                                                   DATA_PATH, acqGait)
        osrf.setTimeRange(acqGait, beginFrame=vff, lastFrame=vlf)
        if "ikAccuracy" in kwargs.keys():
            osrf.setAccuracy(kwargs["ikAccuracy"])

        LOGGER.logger.info("-------INVERSE KINEMATICS IN PROGRESS----------")
        try:
            acqIK = osrf.run(DATA_PATH + reconstructFilenameLabelled,
                             progressionAxis=progressionAxis,
                             forwardProgression=forwardProgression)
            LOGGER.logger.info("[pyCGM2] - IK solver complete")
        except:
            LOGGER.logger.error("[pyCGM2] - IK solver fails")
            acqIK = acqGait
            detectAnomaly = True
        LOGGER.logger.info(
            "---------------------------------------------------")

    # eventual gait acquisition to consider for joint kinematics
    finalAcqGait = acqIK if ik_flag else acqGait

    if "displayCoordinateSystem" in kwargs.keys(
    ) and kwargs["displayCoordinateSystem"]:
        csp = modelFilters.ModelCoordinateSystemProcedure(model)
        csdf = modelFilters.CoordinateSystemDisplayFilter(
            csp, model, finalAcqGait)
        csdf.setStatic(False)
        csdf.display()

    # --- final pyCGM2 model motion Filter ---
    # use fitted markers
    modMotionFitted = modelFilters.ModelMotionFilter(
        scp,
        finalAcqGait,
        model,
        enums.motionMethod.Sodervisk,
        markerDiameter=markerDiameter,
        forceFoot6DoF=forceFoot6DoF_flag)

    modMotionFitted.compute()

    #---- Joint kinematics----
    # relative angles
    modelFilters.ModelJCSFilter(model, finalAcqGait).compute(
        description="vectoriel", pointLabelSuffix=pointSuffix)

    modelFilters.ModelAbsoluteAnglesFilter(
        model,
        finalAcqGait,
        segmentLabels=["Left Foot", "Right Foot", "Pelvis", "Thorax", "Head"],
        angleLabels=[
            "LFootProgress", "RFootProgress", "Pelvis", "Thorax", "Head"
        ],
        eulerSequences=["TOR", "TOR", "ROT", "YXZ", "TOR"],
        globalFrameOrientation=globalFrame,
        forwardProgression=forwardProgression).compute(
            pointLabelSuffix=pointSuffix)

    #---- Body segment parameters----
    bspModel = bodySegmentParameters.Bsp(model)
    bspModel.compute()

    modelFilters.CentreOfMassFilter(
        model, finalAcqGait).compute(pointLabelSuffix=pointSuffix)

    # Inverse dynamics
    if btkTools.checkForcePlateExist(acqGait):
        # --- force plate handling----
        # find foot  in contact
        mappedForcePlate = forceplates.matchingFootSideOnForceplate(
            finalAcqGait, mfpa=mfpa)
        forceplates.addForcePlateGeneralEvents(finalAcqGait, mappedForcePlate)
        LOGGER.logger.warning("Manual Force plate assignment : %s" %
                              mappedForcePlate)

        # assembly foot and force plate
        modelFilters.ForcePlateAssemblyFilter(
            model,
            finalAcqGait,
            mappedForcePlate,
            leftSegmentLabel="Left Foot",
            rightSegmentLabel="Right Foot").compute(
                pointLabelSuffix=pointSuffix)

        #---- Joint kinetics----
        idp = modelFilters.CGMLowerlimbInverseDynamicProcedure()
        modelFilters.InverseDynamicFilter(
            model,
            finalAcqGait,
            procedure=idp,
            projection=momentProjection,
            globalFrameOrientation=globalFrame,
            forwardProgression=forwardProgression).compute(
                pointLabelSuffix=pointSuffix)

        #---- Joint energetics----
        modelFilters.JointPowerFilter(
            model, finalAcqGait).compute(pointLabelSuffix=pointSuffix)

    #---- zero unvalid frames ---
    btkTools.cleanAcq(finalAcqGait)
    btkTools.applyOnValidFrames(finalAcqGait, flag)

    if detectAnomaly and not anomalyException:
        LOGGER.logger.error(
            "Anomalies has been detected - Check Warning messages of the log file"
        )

    return finalAcqGait, detectAnomaly
コード例 #3
0
ファイル: cgm2_1.py プロジェクト: sremm/pyCGM2
def calibrate(DATA_PATH,calibrateFilenameLabelled,translators,
              required_mp,optional_mp,
              leftFlatFoot,rightFlatFoot,headFlat,
              markerDiameter,hjcMethod,
              pointSuffix,**kwargs):

    """
    Calibration of the CGM2.1

    :param DATA_PATH [str]: path to your data
    :param calibrateFilenameLabelled [str]: c3d file
    :param translators [dict]:  translators to apply
    :param required_mp [dict]: required anthropometric data
    :param optional_mp [dict]: optional anthropometric data (ex: LThighOffset,...)
    :param leftFlatFoot [bool]: enable of the flat foot option for the left foot
    :param rightFlatFoot [bool]: enable of the flat foot option for the right foot
    :param headFlat [bool]: enable of the head flat  option
    :param markerDiameter [double]: marker diameter (mm)
    :param hjcMethod [str or list of 3 float]: method for locating the hip joint centre
    :param pointSuffix [str]: suffix to add to model outputs

    """
    detectAnomaly = False
    if "anomalyException" in kwargs.keys():
        anomalyException = kwargs["anomalyException"]
    else:
        anomalyException=False
    # --------------------------ACQUISITION ------------------------------------

    # ---btk acquisition---
    if "forceBtkAcq" in kwargs.keys():
        acqStatic = kwargs["forceBtkAcq"]
    else:
        acqStatic = btkTools.smartReader((DATA_PATH+calibrateFilenameLabelled))

    btkTools.checkMultipleSubject(acqStatic)
    if btkTools.isPointExist(acqStatic,"SACR"):
        translators["LPSI"] = "SACR"
        translators["RPSI"] = "SACR"
        LOGGER.logger.info("[pyCGM2] Sacrum marker detected")

    acqStatic =  btkTools.applyTranslators(acqStatic,translators)

    trackingMarkers = cgm.CGM1.LOWERLIMB_TRACKING_MARKERS + cgm.CGM1.THORAX_TRACKING_MARKERS+ cgm.CGM1.UPPERLIMB_TRACKING_MARKERS
    actual_trackingMarkers,phatoms_trackingMarkers = btkTools.createPhantoms(acqStatic, trackingMarkers)

    vff = acqStatic.GetFirstFrame()
    vlf = acqStatic.GetLastFrame()
    # vff,vlf = btkTools.getFrameBoundaries(acqStatic,actual_trackingMarkers)
    flag = btkTools.getValidFrames(acqStatic,actual_trackingMarkers,frameBounds=[vff,vlf])

    gapFlag = btkTools.checkGap(acqStatic,actual_trackingMarkers,frameBounds=[vff,vlf])
    if gapFlag:
        raise Exception("[pyCGM2] Calibration aborted. Gap find during interval [%i-%i]. Crop your c3d " %(vff,vlf))

    # --------------------ANOMALY------------------------------
    # --Check MP
    adap = AnomalyDetectionProcedure.AnthropoDataAnomalyProcedure( required_mp)
    adf = AnomalyFilter.AnomalyDetectionFilter(None,None,adap)
    mp_anomaly = adf.run()
    if mp_anomaly["ErrorState"]: detectAnomaly = True

    # --marker presence
    markersets = [cgm.CGM1.LOWERLIMB_TRACKING_MARKERS, cgm.CGM1.THORAX_TRACKING_MARKERS, cgm.CGM1.UPPERLIMB_TRACKING_MARKERS]
    for markerset in markersets:
        ipdp = InspectorProcedure.MarkerPresenceDetectionProcedure( markerset)
        idf = InspectorFilter.InspectorFilter(acqStatic,calibrateFilenameLabelled,ipdp)
        inspector = idf.run()

        # # --marker outliers
        if inspector["In"] !=[]:
            madp = AnomalyDetectionProcedure.MarkerAnomalyDetectionRollingProcedure(inspector["In"], plot=False, window=4,threshold = 3)
            adf = AnomalyFilter.AnomalyDetectionFilter(acqStatic,calibrateFilenameLabelled,madp)
            anomaly = adf.run()
            anomalyIndexes = anomaly["Output"]
            if anomaly["ErrorState"]: detectAnomaly = True


    if detectAnomaly and anomalyException:
        raise Exception ("Anomalies has been detected - Check Warning message of the log file")


    # --------------------MODELLING------------------------------

    # ---check marker set used----
    dcm = cgm.CGM.detectCalibrationMethods(acqStatic)

    # ---definition---
    model=cgm2.CGM2_1()
    model.configure(detectedCalibrationMethods=dcm)
    model.addAnthropoInputParameters(required_mp,optional=optional_mp)

    if dcm["Left Knee"] == enums.JointCalibrationMethod.KAD: actual_trackingMarkers.append("LKNE")
    if dcm["Right Knee"] == enums.JointCalibrationMethod.KAD: actual_trackingMarkers.append("RKNE")
    model.setStaticTrackingMarkers(actual_trackingMarkers)


    # --store calibration parameters--
    model.setStaticFilename(calibrateFilenameLabelled)
    model.setCalibrationProperty("leftFlatFoot",leftFlatFoot)
    model.setCalibrationProperty("rightFlatFoot",rightFlatFoot)
    model.setCalibrationProperty("headFlat",headFlat)
    model.setCalibrationProperty("markerDiameter",markerDiameter)


    # --------------------------STATIC CALBRATION--------------------------
    scp=modelFilters.StaticCalibrationProcedure(model) # load calibration procedure

    # ---initial calibration filter----
    # use if all optional mp are zero
    modelFilters.ModelCalibrationFilter(scp,acqStatic,model,
                                        leftFlatFoot = leftFlatFoot, rightFlatFoot = rightFlatFoot,
                                        headFlat= headFlat,
                                        markerDiameter=markerDiameter,
                                        ).compute()

    # ---- Decorators -----
    decorators.applyBasicDecorators(dcm, model,acqStatic,optional_mp,markerDiameter)
    decorators.applyHJCDecorators(model,hjcMethod)


    # ----Final Calibration filter if model previously decorated -----
    if model.decoratedModel:
        # initial static filter
        modelFilters.ModelCalibrationFilter(scp,acqStatic,model,
                                            leftFlatFoot = leftFlatFoot,
                                            rightFlatFoot = rightFlatFoot,
                                            markerDiameter=markerDiameter,
                                            headFlat= headFlat,
                                            ).compute()

    modMotion=modelFilters.ModelMotionFilter(scp,acqStatic,model,enums.motionMethod.Determinist,
                                              markerDiameter=markerDiameter)

    modMotion.compute()

    # ----progression Frame----
    progressionFlag = False
    if btkTools.isPointsExist(acqStatic, ['LASI', 'RASI', 'RPSI', 'LPSI'],ignorePhantom=False):
        LOGGER.logger.info("[pyCGM2] - progression axis detected from Pelvic markers ")
        pfp = progressionFrame.PelvisProgressionFrameProcedure()
        pff = progressionFrame.ProgressionFrameFilter(acqStatic,pfp)
        pff.compute()
        progressionAxis = pff.outputs["progressionAxis"]
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]
        progressionFlag = True
    elif btkTools.isPointsExist(acqStatic, ['C7', 'T10', 'CLAV', 'STRN'],ignorePhantom=False) and not progressionFlag:
        LOGGER.logger.info("[pyCGM2] - progression axis detected from Thoracic markers ")
        pfp = progressionFrame.ThoraxProgressionFrameProcedure()
        pff = progressionFrame.ProgressionFrameFilter(acqStatic,pfp)
        pff.compute()
        progressionAxis = pff.outputs["progressionAxis"]
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]

    else:
        globalFrame = "XYZ"
        progressionAxis = "X"
        forwardProgression = True
        LOGGER.logger.error("[pyCGM2] - impossible to detect progression axis - neither pelvic nor thoracic markers are present. Progression set to +X by default ")


    if "displayCoordinateSystem" in kwargs.keys() and kwargs["displayCoordinateSystem"]:
        csp = modelFilters.ModelCoordinateSystemProcedure(model)
        csdf = modelFilters.CoordinateSystemDisplayFilter(csp,model,acqStatic)
        csdf.setStatic(False)
        csdf.display()


    # ----------------------CGM MODELLING----------------------------------
    # ----motion filter----
    # notice : viconCGM1compatible option duplicate error on Construction of the foot coordinate system

    if "noKinematicsCalculation" in kwargs.keys() and kwargs["noKinematicsCalculation"]:
        LOGGER.logger.warning("[pyCGM2] No Kinematic calculation done for the static file")
        return model, acqStatic
    else:

        #---- Joint kinematics----
        # relative angles
        modelFilters.ModelJCSFilter(model,acqStatic).compute(description="vectoriel", pointLabelSuffix=pointSuffix)

        modelFilters.ModelAbsoluteAnglesFilter(model,acqStatic,
                                               segmentLabels=["Left Foot","Right Foot","Pelvis","Thorax","Head"],
                                                angleLabels=["LFootProgress", "RFootProgress","Pelvis","Thorax", "Head"],
                                                eulerSequences=["TOR","TOR", "ROT","YXZ","TOR"],
                                                globalFrameOrientation = globalFrame,
                                                forwardProgression = forwardProgression).compute(pointLabelSuffix=pointSuffix)

        # BSP model
        bspModel = bodySegmentParameters.Bsp(model)
        bspModel.compute()

        modelFilters.CentreOfMassFilter(model,acqStatic).compute(pointLabelSuffix=pointSuffix)

        btkTools.cleanAcq(acqStatic)
        if detectAnomaly and not anomalyException:
            LOGGER.logger.error("Anomalies has been detected - Check Warning messages of the log file")

        return model, acqStatic,detectAnomaly
コード例 #4
0
def calibrate(DATA_PATH, calibrateFilenameLabelled, translators, weights,
              required_mp, optional_mp, ik_flag, leftFlatFoot, rightFlatFoot,
              headFlat, markerDiameter, hjcMethod, pointSuffix, **kwargs):
    """
    Calibration of the CGM2.5

    :param DATA_PATH [str]: path to your data
    :param calibrateFilenameLabelled [str]: c3d file
    :param translators [dict]:  translators to apply
    :param required_mp [dict]: required anthropometric data
    :param optional_mp [dict]: optional anthropometric data (ex: LThighOffset,...)
    :param ik_flag [bool]: enable the inverse kinematic solver
    :param leftFlatFoot [bool]: enable of the flat foot option for the left foot
    :param rightFlatFoot [bool]: enable of the flat foot option for the right foot
    :param headFlat [bool]: enable of the head flat  option
    :param markerDiameter [double]: marker diameter (mm)
    :param hjcMethod [str or list of 3 float]: method for locating the hip joint centre
    :param pointSuffix [str]: suffix to add to model outputs

    """
    detectAnomaly = False

    if "anomalyException" in kwargs.keys():
        anomalyException = kwargs["anomalyException"]
    else:
        anomalyException = False

    if "Fitting" in weights.keys():
        weights = weights["Fitting"]["Weight"]

    # ---btk acquisition---
    if "forceBtkAcq" in kwargs.keys():
        acqStatic = kwargs["forceBtkAcq"]
    else:
        acqStatic = btkTools.smartReader(
            (DATA_PATH + calibrateFilenameLabelled))

    btkTools.checkMultipleSubject(acqStatic)
    if btkTools.isPointExist(acqStatic, "SACR"):
        translators["LPSI"] = "SACR"
        translators["RPSI"] = "SACR"
        LOGGER.logger.info("[pyCGM2] Sacrum marker detected")

    acqStatic = btkTools.applyTranslators(acqStatic, translators)

    trackingMarkers = cgm2.CGM2_5.LOWERLIMB_TRACKING_MARKERS + cgm2.CGM2_5.THORAX_TRACKING_MARKERS + cgm2.CGM2_5.UPPERLIMB_TRACKING_MARKERS
    actual_trackingMarkers, phatoms_trackingMarkers = btkTools.createPhantoms(
        acqStatic, trackingMarkers)

    vff = acqStatic.GetFirstFrame()
    vlf = acqStatic.GetLastFrame()
    # vff,vlf = btkTools.getFrameBoundaries(acqStatic,actual_trackingMarkers)
    flag = btkTools.getValidFrames(acqStatic,
                                   actual_trackingMarkers,
                                   frameBounds=[vff, vlf])

    gapFlag = btkTools.checkGap(acqStatic,
                                actual_trackingMarkers,
                                frameBounds=[vff, vlf])
    if gapFlag:
        raise Exception(
            "[pyCGM2] Calibration aborted. Gap find during interval [%i-%i]. Crop your c3d "
            % (vff, vlf))

    # --------------------ANOMALY------------------------------
    # --Check MP
    adap = AnomalyDetectionProcedure.AnthropoDataAnomalyProcedure(required_mp)
    adf = AnomalyFilter.AnomalyDetectionFilter(None, None, adap)
    mp_anomaly = adf.run()
    if mp_anomaly["ErrorState"]: detectAnomaly = True

    # --marker presence
    markersets = [
        cgm2.CGM2_5.LOWERLIMB_TRACKING_MARKERS,
        cgm2.CGM2_5.THORAX_TRACKING_MARKERS,
        cgm2.CGM2_5.UPPERLIMB_TRACKING_MARKERS
    ]
    for markerset in markersets:
        ipdp = InspectorProcedure.MarkerPresenceDetectionProcedure(markerset)
        idf = InspectorFilter.InspectorFilter(acqStatic,
                                              calibrateFilenameLabelled, ipdp)
        inspector = idf.run()

        # # --marker outliers
        if inspector["In"] != []:
            madp = AnomalyDetectionProcedure.MarkerAnomalyDetectionRollingProcedure(
                inspector["In"], plot=False, window=4, threshold=3)
            adf = AnomalyFilter.AnomalyDetectionFilter(
                acqStatic, calibrateFilenameLabelled, madp)
            anomaly = adf.run()
            anomalyIndexes = anomaly["Output"]
            if anomaly["ErrorState"]: detectAnomaly = True

    if detectAnomaly and anomalyException:
        raise Exception(
            "Anomalies has been detected - Check Warning message of the log file"
        )

    # --------------------MODELLING------------------------------

    # ---check marker set used----
    dcm = cgm.CGM.detectCalibrationMethods(acqStatic)

    # --------------------------MODEL--------------------------------------
    # ---definition---
    model = cgm2.CGM2_5()
    model.configure(detectedCalibrationMethods=dcm)
    model.addAnthropoInputParameters(required_mp, optional=optional_mp)

    if dcm["Left Knee"] == enums.JointCalibrationMethod.KAD:
        actual_trackingMarkers.append("LKNE")
    if dcm["Right Knee"] == enums.JointCalibrationMethod.KAD:
        actual_trackingMarkers.append("RKNE")
    model.setStaticTrackingMarkers(actual_trackingMarkers)

    # --store calibration parameters--
    model.setStaticFilename(calibrateFilenameLabelled)
    model.setCalibrationProperty("leftFlatFoot", leftFlatFoot)
    model.setCalibrationProperty("rightFlatFoot", rightFlatFoot)
    model.setCalibrationProperty("headFlat", headFlat)
    model.setCalibrationProperty("markerDiameter", markerDiameter)

    # --------------------------STATIC CALBRATION--------------------------
    scp = modelFilters.StaticCalibrationProcedure(
        model)  # load calibration procedure

    # ---initial calibration filter----
    # use if all optional mp are zero
    modelFilters.ModelCalibrationFilter(
        scp,
        acqStatic,
        model,
        leftFlatFoot=leftFlatFoot,
        rightFlatFoot=rightFlatFoot,
        headFlat=headFlat,
        markerDiameter=markerDiameter,
    ).compute()

    # ---- Decorators -----
    decorators.applyBasicDecorators(dcm, model, acqStatic, optional_mp,
                                    markerDiameter)
    decorators.applyHJCDecorators(model, hjcMethod)

    # ----Final Calibration filter if model previously decorated -----
    if model.decoratedModel:
        # initial static filter
        modelFilters.ModelCalibrationFilter(
            scp,
            acqStatic,
            model,
            leftFlatFoot=leftFlatFoot,
            rightFlatFoot=rightFlatFoot,
            headFlat=headFlat,
            markerDiameter=markerDiameter).compute()

    # ----------------------CGM MODELLING----------------------------------
    # ----motion filter----
    modMotion = modelFilters.ModelMotionFilter(scp,
                                               acqStatic,
                                               model,
                                               enums.motionMethod.Sodervisk,
                                               markerDiameter=markerDiameter)

    modMotion.compute()

    # ----progression Frame----
    progressionFlag = False
    if btkTools.isPointsExist(acqStatic, ['LASI', 'RASI', 'RPSI', 'LPSI'],
                              ignorePhantom=False):
        LOGGER.logger.info(
            "[pyCGM2] - progression axis detected from Pelvic markers ")
        pfp = progressionFrame.PelvisProgressionFrameProcedure()
        pff = progressionFrame.ProgressionFrameFilter(acqStatic, pfp)
        pff.compute()
        progressionAxis = pff.outputs["progressionAxis"]
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]
        progressionFlag = True
    elif btkTools.isPointsExist(acqStatic, ['C7', 'T10', 'CLAV', 'STRN'],
                                ignorePhantom=False) and not progressionFlag:
        LOGGER.logger.info(
            "[pyCGM2] - progression axis detected from Thoracic markers ")
        pfp = progressionFrame.ThoraxProgressionFrameProcedure()
        pff = progressionFrame.ProgressionFrameFilter(acqStatic, pfp)
        pff.compute()
        progressionAxis = pff.outputs["progressionAxis"]
        globalFrame = pff.outputs["globalFrame"]
        forwardProgression = pff.outputs["forwardProgression"]

    else:
        globalFrame = "XYZ"
        progressionAxis = "X"
        forwardProgression = True
        LOGGER.logger.error(
            "[pyCGM2] - impossible to detect progression axis - neither pelvic nor thoracic markers are present. Progression set to +X by default "
        )

    # ----manage IK Targets----
    ikTargets = list()
    for target in weights.keys():
        if target not in actual_trackingMarkers:
            weights[target] = 0
            LOGGER.logger.warning(
                "[pyCGM2] - the IK targeted marker [%s] is not labelled in the acquisition [%s]"
                % (target, calibrateFilenameLabelled))
        else:
            ikTargets.append(target)
    model.setStaticIkTargets(ikTargets)

    if "noKinematicsCalculation" in kwargs.keys(
    ) and kwargs["noKinematicsCalculation"]:
        LOGGER.logger.warning(
            "[pyCGM2] No Kinematic calculation done for the static file")
        return model, acqStatic, detectAnomaly
    else:

        if ik_flag:
            #                        ---OPENSIM IK---

            # --- opensim calibration Filter ---
            osimfile = pyCGM2.OPENSIM_PREBUILD_MODEL_PATH + "models\\osim\\lowerLimb_ballsJoints.osim"  # osimfile
            markersetFile = pyCGM2.OPENSIM_PREBUILD_MODEL_PATH + "models\\settings\\cgm2_4\\cgm2_4-markerset.xml"  # markerset
            cgmCalibrationprocedure = opensimFilters.CgmOpensimCalibrationProcedures(
                model)  # procedure

            oscf = opensimFilters.opensimCalibrationFilter(
                osimfile, model, cgmCalibrationprocedure, DATA_PATH)
            oscf.addMarkerSet(markersetFile)
            scalingOsim = oscf.build()

            # --- opensim Fitting Filter ---
            iksetupFile = pyCGM2.OPENSIM_PREBUILD_MODEL_PATH + "models\\settings\\cgm2_4\\cgm2_4-ikSetUp_template.xml"  # ik tool file

            cgmFittingProcedure = opensimFilters.CgmOpensimFittingProcedure(
                model)  # procedure
            cgmFittingProcedure.updateMarkerWeight("LASI", weights["LASI"])
            cgmFittingProcedure.updateMarkerWeight("RASI", weights["RASI"])
            cgmFittingProcedure.updateMarkerWeight("LPSI", weights["LPSI"])
            cgmFittingProcedure.updateMarkerWeight("RPSI", weights["RPSI"])
            cgmFittingProcedure.updateMarkerWeight("RTHI", weights["RTHI"])
            cgmFittingProcedure.updateMarkerWeight("RKNE", weights["RKNE"])
            cgmFittingProcedure.updateMarkerWeight("RTIB", weights["RTIB"])
            cgmFittingProcedure.updateMarkerWeight("RANK", weights["RANK"])
            cgmFittingProcedure.updateMarkerWeight("RHEE", weights["RHEE"])
            cgmFittingProcedure.updateMarkerWeight("RTOE", weights["RTOE"])

            cgmFittingProcedure.updateMarkerWeight("LTHI", weights["LTHI"])
            cgmFittingProcedure.updateMarkerWeight("LKNE", weights["LKNE"])
            cgmFittingProcedure.updateMarkerWeight("LTIB", weights["LTIB"])
            cgmFittingProcedure.updateMarkerWeight("LANK", weights["LANK"])
            cgmFittingProcedure.updateMarkerWeight("LHEE", weights["LHEE"])
            cgmFittingProcedure.updateMarkerWeight("LTOE", weights["LTOE"])

            cgmFittingProcedure.updateMarkerWeight("LTHAP", weights["LTHAP"])
            cgmFittingProcedure.updateMarkerWeight("LTHAD", weights["LTHAD"])
            cgmFittingProcedure.updateMarkerWeight("LTIAP", weights["LTIAP"])
            cgmFittingProcedure.updateMarkerWeight("LTIAD", weights["LTIAD"])
            cgmFittingProcedure.updateMarkerWeight("RTHAP", weights["RTHAP"])
            cgmFittingProcedure.updateMarkerWeight("RTHAD", weights["RTHAD"])
            cgmFittingProcedure.updateMarkerWeight("RTIAP", weights["RTIAP"])
            cgmFittingProcedure.updateMarkerWeight("RTIAD", weights["RTIAD"])

            cgmFittingProcedure.updateMarkerWeight("LSMH", weights["LSMH"])
            cgmFittingProcedure.updateMarkerWeight("LFMH", weights["LFMH"])
            cgmFittingProcedure.updateMarkerWeight("LVMH", weights["LVMH"])

            cgmFittingProcedure.updateMarkerWeight("RSMH", weights["RSMH"])
            cgmFittingProcedure.updateMarkerWeight("RFMH", weights["RFMH"])
            cgmFittingProcedure.updateMarkerWeight("RVMH", weights["RVMH"])

            #            cgmFittingProcedure.updateMarkerWeight("LTHL",weights["LTHL"])
            #            cgmFittingProcedure.updateMarkerWeight("LTHLD",weights["LTHLD"])
            #            cgmFittingProcedure.updateMarkerWeight("LPAT",weights["LPAT"])
            #            cgmFittingProcedure.updateMarkerWeight("LTIBL",weights["LTIBL"])
            #            cgmFittingProcedure.updateMarkerWeight("RTHL",weights["RTHL"])
            #            cgmFittingProcedure.updateMarkerWeight("RTHLD",weights["RTHLD"])
            #            cgmFittingProcedure.updateMarkerWeight("RPAT",weights["RPAT"])
            #            cgmFittingProcedure.updateMarkerWeight("RTIBL",weights["RTIBL"])

            osrf = opensimFilters.opensimFittingFilter(iksetupFile,
                                                       scalingOsim,
                                                       cgmFittingProcedure,
                                                       DATA_PATH,
                                                       acqStatic,
                                                       accuracy=1e-5)

            LOGGER.logger.info(
                "-------INVERSE KINEMATICS IN PROGRESS----------")
            try:
                acqStaticIK = osrf.run(DATA_PATH + calibrateFilenameLabelled,
                                       progressionAxis=progressionAxis,
                                       forwardProgression=forwardProgression)
                LOGGER.logger.info("[pyCGM2] - IK solver complete")
            except:
                LOGGER.logger.error("[pyCGM2] - IK solver fails")
                acqStaticIK = acqStatic
                detectAnomaly = True
            LOGGER.logger.info(
                "-----------------------------------------------")

        # eventual static acquisition to consider for joint kinematics
        finalAcqStatic = acqStaticIK if ik_flag else acqStatic

        # --- final pyCGM2 model motion Filter ---
        # use fitted markers
        modMotionFitted = modelFilters.ModelMotionFilter(
            scp, finalAcqStatic, model, enums.motionMethod.Sodervisk)
        modMotionFitted.compute()

        if "displayCoordinateSystem" in kwargs.keys(
        ) and kwargs["displayCoordinateSystem"]:
            csp = modelFilters.ModelCoordinateSystemProcedure(model)
            csdf = modelFilters.CoordinateSystemDisplayFilter(
                csp, model, finalAcqStatic)
            csdf.setStatic(False)
            csdf.display()

        #---- Joint kinematics----
        # relative angles
        modelFilters.ModelJCSFilter(model, finalAcqStatic).compute(
            description="vectoriel", pointLabelSuffix=pointSuffix)

        modelFilters.ModelAbsoluteAnglesFilter(
            model,
            finalAcqStatic,
            segmentLabels=[
                "Left Foot", "Right Foot", "Pelvis", "Thorax", "Head"
            ],
            angleLabels=[
                "LFootProgress", "RFootProgress", "Pelvis", "Thorax", "Head"
            ],
            eulerSequences=["TOR", "TOR", "ROT", "YXZ", "TOR"],
            globalFrameOrientation=globalFrame,
            forwardProgression=forwardProgression).compute(
                pointLabelSuffix=pointSuffix)
        # BSP model
        bspModel = bodySegmentParameters.Bsp(model)
        bspModel.compute()

        modelFilters.CentreOfMassFilter(
            model, finalAcqStatic).compute(pointLabelSuffix=pointSuffix)

        btkTools.cleanAcq(finalAcqStatic)
        if detectAnomaly and not anomalyException:
            LOGGER.logger.error(
                "Anomalies has been detected - Check Warning messages of the log file"
            )

        return model, finalAcqStatic, detectAnomaly