def test_forceAnomalies(self): filename = pyCGM2.TEST_DATA_PATH + "/LowLevel/anomalies/gaitEvents/gait Trial 01-noAnomalies.c3d" acq = btkTools.smartReader(filename) madp = AnomalyDetectionProcedure.ForcePlateAnomalyProcedure() adf = AnomalyFilter.AnomalyDetectionFilter( acq, filename[filename.rfind("/") + 1:], madp) adf.run()
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
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