Modules

Anomaly

Anomaly Filter

This module contains pyCGM2 anomaly filters to deal with either an anomaly detector procedure or an anomaly correction procedure

check out the script : Teststest_anomalies.py for examples

class pyCGM2.Anomaly.anomalyFilters.AnomalyCorrectionFilter(acq, filename, procedure)

anomaly corrector filter

Parameters

acq (btk.Acquisition) – a btk acquisition instance
filename (str) – filename
procedure (pyCGM2.Anomaly.anomalyDetectionProcedures.AnomalyDetectionProcedure) – a procedure instance

class pyCGM2.Anomaly.anomalyFilters.AnomalyDetectionFilter(acq, filename, procedure, **kwargs)

Anomaly detector filter

Parameters

acq (btk.Acquisition) – a btk acquisition instance
filename (str) – filename
procedure (pyCGM2.Anomaly.anomalyDetectionProcedures.AnomalyDetectionProcedure) – a procedure instance

Kwargs:: frameRange (list): frame boundaries

AnomalyDetectionProcedure

This module gathers anomaly detectors on markers, events, force plate signals and anthropometric data

check out the script : Teststest_anomalies.py for example

class pyCGM2.Anomaly.anomalyDetectionProcedures.AnomalyDetectionProcedure: abstract marker detector procedure

class pyCGM2.Anomaly.anomalyDetectionProcedures.AnthropoDataAnomalyProcedure(mp)

atnthropometric data anomaly detector

run(acq, filename, options)

run the procedure

Parameters

acq (btk.Acquisition) – a btk acquisition instantce
filename (str) – filename
options (dict) – passed options ( Not used so far)

class pyCGM2.Anomaly.anomalyDetectionProcedures.ForcePlateAnomalyProcedure

force plate anomaly detector

run(acq, filename, options)

run the procedure

Parameters

acq (btk.Acquisition) – a btk acquisition instantce
filename (str) – filename
options (dict) – passed options

Note: frameRange ([int, int]) is one key of the options argument

class pyCGM2.Anomaly.anomalyDetectionProcedures.GaitEventAnomalyProcedure

gait event anomaly detector

run(acq, filename, options)

run the procedure

Parameters

acq (btk.Acquisition) – a btk acquisition instantce
filename (str) – filename
options (dict) – passed options ( Not used so far)

class pyCGM2.Anomaly.anomalyDetectionProcedures.MarkerAnomalyDetectionRollingProcedure(markers, plot=False, **kwargs)

marker anomaly detection from rolling statistics

Parameters

markers (list) – marker labels;
plot (bool) – enable plot

Kwargs:: aprioriError (double): a priori error on the marker trajectory window (int): size of the rolling windows treshold (int) : detector threshold assoiated to the standard deviation method (str) : mean or median

run(acq, filename, options)

run the procedure

Parameters

acq (btk.Acquisition) – a btk acquisition instantce
filename (str) – filename
options (dict) – passed options from the filter

AnomalyCorrectionProcedure

class pyCGM2.Anomaly.anomalyCorrectionProcedures.MarkerAnomalyCorrectionProcedure(markers, anomalyIndexes, plot=False, **kwargs)

procedure to correct marker anomaly

Parameters

markers (list) – marker labels
anomalyIndexes (list) – indexes of the detected anomalies
plot (bool) – enable plot

Keyword Arguments

distance_threshold (float) – distance threshold between indexes

run(acq, filename)

run the procedure

Parameters

acq (btk.Acquisition) – a btk acquisition instantce
filename (str) – filename

EMG module

emgManager

class pyCGM2.EMG.emgManager.EmgManager(DATA_PATH, emgSettings=None)

Class to manage emg settings ( ie the emg.settings file)

Parameters

DATA_PATH (str) – data folder path
emgSettings (str,Optional[None]) – content of the emg.settings file

getChannelSection(): return the channel section of the emg settings

getChannels(): return the channel labels

getMuscles(): return the muscles

getNormalActivity(): return the normal activity muscle reference

getProcessingSection(): return the processing section of the emg settings

getSides(): return side of each emg

emgFilters

coactivationProcedures

This module contains co-activation procedures

check out the script : Tests est_EMG.py for examples

class pyCGM2.EMG.coactivationProcedures.FalconerCoActivationProcedure

Coactivation index according falconer and Winter

Falconer K, Winter DA. Quantitative assessment of cocontraction at the ankle joint in walking. Electromyogr Clin Neurophysiol. 1985;25:135–149. [PubMed] [Google Scholar]

run(emg1, emg2)

run the procedure.

Parameters

emg1 (str) – emg label .
emg2 (str) – emg label

Returns

list – Coactivation index

class pyCGM2.EMG.coactivationProcedures.UnithanCoActivationProcedure

Coactivation procedure according Unithan et al, 1996

Unnithan VB, Dowling JJ, Frost G, Volpe Ayub B, Bar-Or O. Cocontraction and phasic activity during GAIT in children with cerebral palsy. Electromyogr Clin Neurophysiol. 1996;36:487–494.

run(emg1, emg2)

run the procedure.

Parameters

emg1 (str) – emg label .
emg2 (str) – emg label

Returns

list – Coactivation index

discreteEmgProcedures

Module containes Filter and Procedure for extracting discrete value ( e.g : amplitude) from each emg signal

class pyCGM2.EMG.discreteEmgProcedures.AmplitudesProcedure

This procedure computes EMG amplitude for each gait phases

detect(analysisInstance, emgLabels, emgMuscles, emgContexts)

Compute amplitudes

Parameters

analysis (pyCGM2.Processing.analysis.Analysis) – A pycgm2 analysis instance
emgLabels (list) – emg labels
emgMuscles (list) – muscle matching emg labels
emgContexts (list) – side of each eamg labels

normalActivation

The module contains convenient function for getting the normal emg activity of the muscles listed in the file (pyCGM2/Data/normativeData/emg/normalActivation.json).

pyCGM2.EMG.normalActivation.getNormalBurstActivity(muscle, fo)

get onsets and offsets of a specific muscle.

Parameters

muscle (str) – muscle label listed in normalActivation.json
fo (int) – foot off frame

pyCGM2.EMG.normalActivation.getNormalBurstActivity_fromCycles(muscle, ff, begin, fo, end, apf)

get onsets and offsets of a specific muscle from .

Parameters

muscle (str) – muscle label listed in normalActivation.json
ff (int) – first frame of the btk.acquisition
begin (int) – initial frame of cycle
fo (int) – foot off frame
end (int) – final frame of the cycle
apf (int) – nNumber of analog sample per frame

Event

eventFilters

The module contains filter for detecting foot contact events.

check out the script : Tests est_events.py for examples

class pyCGM2.Events.eventFilters.EventFilter(procedure, acq)

Event filter to handle an event procedure

detect(): Run the motion filter

eventProcedures

force Plates module

forcePlates

Gap

GapFilters

The module contains filter and procedure for filling gap

check out the script : Tests est_gap.py for examples

class pyCGM2.Gap.gapFilters.GapFillingFilter(procedure, acq)

Gap filter

Parameters

procedure (pyCGM2.Gap.gapFillingProcedures.GapProcedure) – a gap filling procedure instance
acq (Btk.Acquisition) – a btk acquisition instance

fill(markers=None): fill gap according the specified procedure

GapProcedures

Inspector

inspectorFilters

Module contain the filter for running inspector procedure.

class pyCGM2.Inspector.inspectorFilters.InspectorFilter(acq, filename, procedure, **kwargs): pyCGM2 filter

inspectorProcedures

Model

anthropometricMeasurement

bodySegmentParameters

class pyCGM2.Model.bodySegmentParameters.Bsp(iModel)

Body Segment Parameter of the lower limb according Dempster 1995

Reference

Dempster. (1955). Body Segment Parameter Data for 2-D Studies

compute(): Compute body segment parameters of a Model

classmethod setParameters(bspSegmentLabel, segmentLength, bodymass)

Compute body parameter of a selected lower limb segment

Parameters

bspSegmentLabel (str) – segment label defined in the class object TABLE
segmentLength (double) – length of the segment
bodymass (double) – mass of the subject

pyCGM2.Model.bodySegmentParameters.updateFromcustomMp(model, custom_mp)

update the anthropometric parameters fo your model

Parameters

model (pyCGM2.Model) – a model instance.
custom_mp (dict) – mp from the file mp.settings

frame

this module gathers two classes (Node and Frame), important for the construction of a model

A Frame is a representation of a coordinate system at a specific time. Its main attributes are the rotation matrix and the translation vectors.

A Frame can collect Node instances. A Node represents a 3d point expressed in a local coordinate system

class pyCGM2.Model.frame.Frame

A Frame represents a coordinate system

addNode(nodeLabel, position, positionType='Global', desc='')

Append a Node to a Frame

Parameters

nodeLabel (str) – node label
position (array(3,)) – a translation vector
positionType (str,Optional) – two choice Global or Local
desc (str,Optional) – description

copyNode(nodeLabel, nodeToCopy)

Copy a node and add it or update a existant node

Parameters

nodeLabel (str) – the node label
nodeToCopy (str) – the label of the node to copy

eraseNodes(): Erase all nodes

getAngleAxis(): Get the angle axis

getGlobalPosition(nodeLabel)

Return the global position

Parameters: nodeLabel (str) – the node label

getNodeIndex(nodeLabel)

Get the node index

Parameters: nodeLabel (str) – the node label

getNodeLabels(display=True): Display all node labels

getNode_byIndex(index)

Get a node from its index

Parameters: index (int) – index of the node within the list

getNode_byLabel(label)

Get a node from its label

Args:
label(str): the node label

getNodes(): Return all node instances

getRotation()

Get rotation matrix

Returns: array ((3,3) – a rotation matrix

getTranslation(): Get translation vector

isNodeExist(nodeLabel)

Check if a node exists from its label

Parameters: nodeLabel (str) – the node label

setRotation(R)

Set the rotation matrix

Parameters: R (array(3,3) – a rotation matrix

setTranslation(t)

Set the translation vector

Parameters: t (array(3,)) – a translation vector

update(R, t)

Update both the rotation matrix and the translation vector

Parameters

R (array(3,3) – a rotation matrix
t (array(3,)) – a translation vector

updateAxisFromRotation(R)

Update the rotation matrix

Parameters: R (array(3,3) – a rotation matrix

updateNode(nodeLabel, localArray, globalArray, desc='')

Update a node

Parameters

nodeLabel (str) – the node label
localArray (array(3)) – local position
globalArray (array(3)) – global position
desc (str,Optional) – description

class pyCGM2.Model.frame.Node(label, desc='')

A node is a local position of a 3D point in a coordinate system

Note

Automatically, the suffix “_node” ends the node label

Parameters

label (str) – desired label of the node
desc (str,Optional) – description

computeGlobal(rot, t)

Compute global position from local

Parameters

rot (array((3,3)) – a rotation matrix
t (array((1,3)) – a translation vector

computeLocal(rot, t)

Compute local position from global position

Parameters

rot (array(3,3)) – a rotation matrix
t (array((1,3))) – a translation vector

getDescription(): Get the node description

getGlobal(): Get the global coordinates of the node

getLabel(): Get the node label

getLocal(): Get the local coordinates of the node

setDescription(description)

Set description of the node

Parameters: description (str) – description

pyCGM2.Model.frame.angleAxisFromQuaternion(Quaternion)

Calculates the AngleAxis representation from a quaternion

Parameters: Quaternion (array(4)) – a quaternion

pyCGM2.Model.frame.getQuaternionFromMatrix(RotMat)

Calculates the quaternion representation from a rotation matrix.

Algorithm in Ken Shoemake’s article in 1987 SIGGRAPH course notes article “Quaternion Calculus and Fast Animation”.

Parameters: RotMat (array(3,3)) – Rotation matrix

pyCGM2.Model.frame.setFrameData(a1, a2, sequence)

Set axes and rotation matrix of a coordinate system from 2 vectors and a sequence

The sequence can be all combinaison of XYZ. If the second letter is prefixed by i, the opposite vector to the cross product a1, a2 is considered

Parameters

a1 (array(1,3)) – first vector
a2 (array(1,3)) – second vector
sequence (str) – construction sequence (XYZ, XYiZ,…)

model

modelDecorator

modelFilters

modelQualityFilter

motion

This module contains pose algorithms

pyCGM2.Model.motion.segmentalLeastSquare(A, B)

Compute the transformation between two coordinate systems using SVD.

Parameters

A (numpy.array(n,3)) –
B (numpy.array(n,3)) –

CGM2

cgm2

decorators

Opensim

opensimFilters

osimProcessing

This module contains convenient functions and classes for working with opensim.

pyCGM2.Model.Opensim.osimProcessing.globalTransformationLabToOsim(acq, R_LAB_OSIM)

transform all markers into the the opensim global coordinate system

Parameters

acq (Btk.Acquisition) – an acquisition
R_LAB_OSIM (array(3,3)) – rotation matrix for passing from the lab to opensim coordinate sytem

pyCGM2.Model.Opensim.osimProcessing.mot2pointValues(motFilename, labels, orientation=[1, 1, 1])

convert an element of an opensim mot file into a btk-point values (ie array(n,3) with n: the number of frames)

Parameters

motFilename (str) – full filename of the mot file
label (str) – label to convert
orientation (list) – scales to apply before returning final values. Default is [1,1,1]

pyCGM2.Model.Opensim.osimProcessing.setGlobalTransormation_lab_osim(axis, forwardProgression)

return the rotation matrix expressing the opensim global coordinate system to the laboratory coordinate system

Parameters

axis (str) – defined progression axis (ie X or Y ).
forwardProgression (bool) – forward progression flag.
True ((if) –
of (the movement progression is along the positive value) –
) (your progression axis) –

pyCGM2.Model.Opensim.osimProcessing.smartTrcExport(acq, filenameNoExt)

save as a trc file

Parameters

acq (Btk.Acquisition) – an acquisition
filenameNoExt (str) – filename without extension

pyCGM2.Model.Opensim.osimProcessing.sto2pointValues(storageObject, label, R_LAB_OSIM)

transform an element of a storage instance into the Laboratory coordinate system.

Parameters

storageObject (opensim.Storage) – an opensim storage instance.
label (str) – label to extract from the storage instance
R_LAB_OSIM (array(3,3)) – rotation matrix for passing from the lab to opensim coordinate sytem

QTM

qtmTools

Module contains convenient functions dealing with the session.xml file generated from QTM.

pyCGM2.QTM.qtmTools.SubjectMp(soup)

return the antropometric parameters

Parameters: soup (bs4.soup) – content of the session.xml

pyCGM2.QTM.qtmTools.detectMeasurementType(soup)

return the type of each measurement section

Parameters: soup (bs4.soup) – content of the session.xml

pyCGM2.QTM.qtmTools.findDynamic(soup)

return the dynamic files from the bs4.soup instance representing the content of the session.xml

Parameters: soup (bs4.soup) – content of the session.xml

pyCGM2.QTM.qtmTools.findKneeCalibration(soup, side)

return the knee functional calibration file from the bs4.soup instance representing the content of the session.xml

Parameters

soup (bs4.soup) – content of the session.xml
side (str) – lower limb side

pyCGM2.QTM.qtmTools.findStatic(soup)

return the static file from the bs4.soup instance representing the content of the session.xml

Parameters: soup (bs4.soup) – content of the session.xml

pyCGM2.QTM.qtmTools.getFilename(measurement)

return the filename of the measurement section

Parameters: measurement (bs4.soup) – a measurement section of the session.xml file.

pyCGM2.QTM.qtmTools.getForcePlateAssigment(measurement)

return the force plate assigment from the measurement section

Parameters: measurement (bs4.soup) – a measurement section of the session.xml file.

pyCGM2.QTM.qtmTools.getKneeFunctionCalibMethod(measurement)

return the method used for the knee calibration

Parameters: measurement (bs4.soup) – a measurement section of the session.xml file.

pyCGM2.QTM.qtmTools.isType(measurement, type)

check type of measurement section

Parameters

measurement (bs4.soup) – a measurement section of the session.xml file.
type (str) – type

Processing

analysis

analysisHandler

pyCGM2.Processing.analysisHandler.getAnalysisSection(analysisInstance, label, context)

return the section ( ie kinematic, kinetic or emg) of a given label and its context

Parameters

analysisInstance (pyCGM2.Processing.analysis.Analysis) – an analysis instance
label (str) – givel ouput label (eg LKneeAngles)
context (str) – event context

pyCGM2.Processing.analysisHandler.getNumberOfCycle(analysisInstance, label, context)

return the number of cycle from a given ouput and its event context.

Parameters

analysisInstance (pyCGM2.Processing.analysis.Analysis) – an analysis instance
label (str) – givel ouput label (eg LKneeAngles)
context (str) – event context

pyCGM2.Processing.analysisHandler.getPhases(dataStats, context='Both')

get phases

Parameters

dataStats (pyCGM2.Processing.analysis.Analysis.kinematicStats.data) – data level
instance (of the kinematicStats or kineticStats attributes of an Analysis) –
context (str) – event context

pyCGM2.Processing.analysisHandler.getValues(analysisInstance, label, context)

return the values from a given ouput and its event context.

Parameters

analysisInstance (pyCGM2.Processing.analysis.Analysis) – an analysis instance
label (str) – givel ouput label (eg LKneeAngles)
context (str) – event context

pyCGM2.Processing.analysisHandler.isKeyExist(analysisInstance, label, context, exceptionMode=False)

check if the combinaison label/context exist in the analysis instance

Parameters

analysisInstance (pyCGM2.Processing.analysis.Analysis) – an analysis instance
label (str) – givel ouput label (eg LKneeAngles)
context (str) – event context
exceptionMode (bool) – enable exception raising

analysisProcessing

cycle

exporter

This module contains 2 classes (XlsAnalysisExportFilter and AnalysisExportFilter) for exporting an analysis instance in xls fomat and json respectively.

the class XlsExportDataFrameFilter is a generic filter for exporting Pandas.DataFrame in xls.

class pyCGM2.Processing.exporter.AnalysisExportFilter

Filter exporting an analysis instance as json.

export(outputName, path=None)

Export as json

Parameters

outputName (str) – filename without extension
path (str) – Path

setAnalysisInstance(analysisInstance)

set the analysis instance

Parameters: analysisInstance (pyCGM2.analysis.Analysis) – an analysis instance

class pyCGM2.Processing.exporter.XlsAnalysisExportFilter

Filter exporting an analysis instance as spreadheet.

Exported spreadsheet can organize either by row (Advanced mode) or column (basic mode). In Advanced mode, a row is made up of 101 columns representing a time normalized cycle.

export(outputName, path=None, excelFormat='xls', mode='Advanced')

Export spreadsheet

Parameters

outputName (str) – filename without extension
path (str) – Path
excelFormat (str) – format (xls,xlsx)
mode (str) – structure mode of the spreadsheet (Advanced,Basic)

setAnalysisInstance(analysisInstance)

set the analysis instance

Parameters: analysisInstance (pyCGM2.analysis.Analysis) – an analysis instance

class pyCGM2.Processing.exporter.XlsExportDataFrameFilter

Filter exporting a pandas.dataFrame or a list of pandas.dataFrame as xls spreadsheet(s)

export(outputName, path=None, excelFormat='xls')

Export spreadsheet

Parameters

outputName (str) – filename without extension
path (str) – Path
excelFormat (str) – format (xls,xlsx)

setDataFrames(dataframes)

Set the dataFrame

Parameters: dataframes (pandas.dataFrame or list) – dataframe or list of dataframe

c3dManager

c3dManagerFilters

c3dManagerProcedures

Classification

classificationFilters

classificationProcedures

DiscretePoints

discretePointFilters

A discrete point is a value at a specific frame of a cycle.

In this module, through the filter DiscretePointsFilter, the goal is to get series of discrete values extracted according a specific strategy (ie a procedure). For instance, the BenedettiProcedure extracts dicrete points recommanded in Benededdi et al (1998):

References:

Benedetti, M. G.; Catani, F.; Leardini, A.; Pignotti, E.; Giannini, S. (1998) Data management in gait analysis for clinical applications. In : Clinical biomechanics (Bristol, Avon), vol. 13, n° 3, p. 204–215. DOI: 10.1016/s0268-0033(97)00041-7.

class pyCGM2.Processing.DiscretePoints.discretePointFilters.DiscretePointsFilter(discretePointProcedure, analysis, modelInfo=None, subjInfo=None, condExpInfo=None)

Discrete point filter

Parameters

discretePointProcedure (pyCGM2.Processing.DiscrePoints.discretePointProcedures.DiscretePointProcedure) – a procedure
analysis (pyCGM2.Processing.analysis.Analysis) – an analysis instance
modelInfo (dict) – information about the model
subjInfo (dict) – information about the subject
condExpInfo (dict) – information about the experiment

getOutput(): get the output dataframe with all discrete values according to the procedure

setCondExpInf(condExpInfo)

Set experimental information

Parameters: condExpInfo (dict) – experimental information

setModelInfo(modelInfo)

Set model information

Parameters: modelInfo (dict) – model information

setSubjInfo(subjInfo)

Set subject information

Parameters: subjInfo (dict) – subject information

discretePointProcedures

class pyCGM2.Processing.DiscretePoints.discretePointProcedures.BenedettiProcedure(pointSuffix=None)

discrete points recommanded by benededdi et al(1998).

Parameters: pointSuffix (str) – suffix added to model ouputs

References:

Benedetti, M. G.; Catani, F.; Leardini, A.; Pignotti, E.; Giannini, S. (1998) Data management in gait analysis for clinical applications. In : Clinical biomechanics (Bristol, Avon), vol. 13, n° 3, p. 204–215. DOI: 10.1016/s0268-0033(97)00041-7.

detect(analysisInstance)

extract discrete points

Parameters: analysisInstance (pyCGM2.Processing.analysis.Analysis) – an analysis instance

class pyCGM2.Processing.DiscretePoints.discretePointProcedures.GoldbergProcedure(pointSuffix=None)

discrete points recommanded by Goldberg et al(1998).

Parameters: pointSuffix (str) – suffix added to model ouputs

References:

Goldberg, Saryn R.; Ounpuu, Sylvia; Arnold, Allison S.; Gage, James R.; Delp, Scott L. (2006) Kinematic and kinetic factors that correlate with improved knee flexion following treatment for stiff-knee gait. In : Journal of biomechanics, vol. 39, n° 4, p. 689–698. DOI: 10.1016/j.jbiomech.2005.01.015.

detect(analysisInstance)

extract discrete points

Parameters: analysisInstance (pyCGM2.Processing.analysis.Analysis) – an analysis instance

class pyCGM2.Processing.DiscretePoints.discretePointProcedures.MaxMinProcedure(pointSuffix=None)

extract extrema values.

Parameters: pointSuffix (str) – suffix added to model ouputs

detect(analysisInstance)

extract discrete points

Parameters: analysisInstance (pyCGM2.Processing.analysis.Analysis) – an analysis instance

JointPatterns

jointPatternFilters

class pyCGM2.Processing.JointPatterns.jointPatternFilters.JointPatternFilter(jointPatternProcedure, analysis)

jointPatternProcedures

ProgressionFrame

progressionFrameFilters

progressionFrameProcedures

Representative

representativeFilters

representativeProcedures

Scores

scoreFilters

This module is dedicated to the quantification of a Score, i e a Global index caracterizing the movement performed

The filter ScoreFilter calls a specific procedure, and return scores values.

class pyCGM2.Processing.Scores.scoreFilters.ScoreFilter(scoreProcedure, analysis, normativeDataSet)

the score filter

Parameters

scoreProcedure (pyCGM2.processing.Scores.scoreProcedures.ScoreProcedure) – a procedure instance
analysis (pyCGM2.Processing.analysis.Analysis) – and analysis instance
normativeDataSet (pyCGM2.Report.normativeDatasets.NormativeData) – normative data instance

scoreProcedures

class pyCGM2.Processing.Scores.scoreProcedures.CGM1_GPS(pointSuffix=None)

Gait profile score accordin Baker et al. 2009

Parameters: pointSuffix (str,Optional[None]) – suffix added to model ouputs

Reference

Baker, Richard; McGinley, Jennifer L.; Schwartz, Michael H.; Beynon, Sarah; Rozumalski, Adam; Graham, H. Kerr; Tirosh, Oren (2009) The gait profile score and movement analysis profile. In : Gait & posture, vol. 30, n° 3, p. 265–269. DOI: 10.1016/j.gaitpost.2009.05.020.

Report

normativeDatasets

Module deals with normative datasets.

Normative datasets are embedded in pyCGM2. they are placed in the folder pyCGM2/Data as a json file.

The construction of a NormativeData instance automatically populate its attribute data, an intuitive dictionary with model ouput as key, reporting mean and standard deviation as sub-key.

The NormativeSTP class replicates the process for the spatio-temporal excel file (normal_stp.xlsx) placed in the folder pyCGM2/Data/stp

class pyCGM2.Report.normativeDatasets.NormalSTP

Normative spatio-temporal dataset.

The instance contruction populates the attribute data which reports normative data as a dictionary

class pyCGM2.Report.normativeDatasets.NormativeData(filenameNoExt, modality)

Normative dataset.

The instance contruction populates the attribute data which reports normative data as a dictionary

Parameters

filenameNoExt (str) – filename of the targeted json file.
modality (str) – modality.

plot

plotFilters

plotUtils

Viewers

plotViewers

emgPlotViewers

comparisonPlotViewers

Signal

anomaly

pyCGM2.Signal.anomaly.anomaly_rolling(values, aprioriError=0, window=10, threshold=3, method='median', plot=False, label='Unknow', referenceValues=None)

anomaly detection from rolling windows

Parameters

values (np.array) – values
aprioriError (int,Optional[0]) – a priori error.
window (int,Optional[10]) – size of the window.
threshold (int,Optional[3]) – standard deviation factor
method (str,Optional[median]) – descriptive statistic method
plot (bool,Optional[False]) – enable plot
label (str,Optional[Unknown]) – Description of parameter label
referenceValues (np.array,Optional[None]) – values used as reference instead of the values computing from the rolling windows

detect_changes

The module only contains the function “detect_changes” implemenented by Marcos Duarte, available in [BMC](https://github.com/demotu/BMC)

see BMC documentation for details

pyCGM2.Signal.detect_changes.detect_cusum(x, threshold=1, drift=0, ending=False, show=True, ax=None): Cumulative sum algorithm (CUSUM) to detect abrupt changes in data

detect_onset

The module only contains the function “detect_onset” implemenented by Marcos Duarte, available in [BMC](https://github.com/demotu/BMC)

see BMC documentation for details

pyCGM2.Signal.detect_onset.detect_onset(x, threshold=0, n_above=1, n_below=0, threshold2=None, n_above2=1, show=False, ax=None): Detects onset in data based on amplitude threshold.

detect_peaks

The module only contains the function “detect_peaks” implemenented by Marcos Duarte, available in [BMC](https://github.com/demotu/BMC)

see BMC documentation for details

pyCGM2.Signal.detect_peaks.detect_peaks(x, mph=None, mpd=1, threshold=0, edge='rising', kpsh=False, valley=False, show=False, ax=None): Detect peaks in data based on their amplitude and other features.

signal_processing

The module only contains functions for filtering data

pyCGM2.Signal.signal_processing.arrayLowPassFiltering(valuesArray, freq, order=2, fc=6)

Low-pass filtering of a numpy.array

Parameters

valuesArray (numpy.array(n,n)) –
fc (float,Optional) – cut-off frequency. Default set to 6 Hz
order (int,optional) – order of the low-pass filter, Default set to 2

pyCGM2.Signal.signal_processing.enveloppe(array, fc, fa)

Get signal enveloppe from a low pass filter

Parameters

array (numpy.array(n,n)) – array
fc (float) – cut-off frequency
fa (float) – sample frequency

pyCGM2.Signal.signal_processing.forcePlateFiltering(btkAcq, order=4, fc=5)

Low-pass filtering of Force plate outputs

Parameters

btkAcq (btk.Acquisition) – btk acquisition instance
fc (float,Optional) – cut-off frequency. Default set to 5 Hz
order (int,optional) – order of the low-pass filter, Default set to 4

pyCGM2.Signal.signal_processing.highPass(array, lowerFreq, upperFreq, fa)

butterworth bandpass filter.

Parameters

array (numpy.array(n,n)) – array
lowerFreq (float) – lower frequency
upperFreq (float) – upper frequency
fa (float) – sample frequency

pyCGM2.Signal.signal_processing.markerFiltering(btkAcq, markers, order=2, fc=6, zerosFiltering=True)

Low-pass filtering of all points in an acquisition

Parameters

btkAcq (btk.Acquisition) – btk acquisition instance
fc (float,Optional) – cut-off frequency. Default set to 6 Hz
order (int,optional) – order of the low-pass filter, Default set to 2
zerosFiltering (bool,optional) – enable zero filtering, Default set to True

pyCGM2.Signal.signal_processing.rectify(array)

rectify a signal ( i.e get absolute values)

Parameters: array (numpy.array(n,n)) – array

pyCGM2.Signal.signal_processing.remove50hz(array, fa)

Remove the 50Hz signal

Args: array (array(n,n): array fa (float): sample frequency

Tools

btkTools

pythonTools

class pyCGM2.Tools.pythonTools.ordict(*args, **kwargs)

ordered dictionary

clear(): clear the dictionary

copy(): copy dict

items(): return items (key,value)

iteritems(): iterator returning tuples (key, value)

iterkeys(): iterator returning key

itervalues(): iterator returning value

keys(): get keys

pop(key, value=None): remove a key and return its value

popitem(): remove a key an return the key an its value

setdefault(key, value=None): set a default item

update(*args, **kwargs): update the dictionary

values(): return values

Utils

files

pyCGM2.Utils.files.copyPaste(src, dst)

file copy/paste

Parameters

src (str) – source
dst (str) – destination

pyCGM2.Utils.files.copyPasteDirectory(src, dst)

folder copy/paste

Parameters

src (str) – source
dst (str) – destination

pyCGM2.Utils.files.copySessionFolder(folderPath, folder2copy, newFolder, selectedFiles=None)

copy a vicon-session folder

Parameters

folderPath (str) – new session folder path
folder2copy (str) – session folder path to copy
selectedFiles (str,Optional[none]) – selected files to copy

pyCGM2.Utils.files.createDir(fullPathName)

Create a folder

Parameters: fullPathName (str) – path

pyCGM2.Utils.files.deleteDirectory(dir)

Delete a folder

Parameters: dir (str) – folder path

pyCGM2.Utils.files.getC3dFiles(path, text='', ignore=None)

get all c3d files in a folder

Parameters

path (str) – folder path
text (str,Optional[""]) – included text in the filename

pyCGM2.Utils.files.getDirs(folderPath)

get all folders

Parameters: folderPath (str) – folder path

pyCGM2.Utils.files.getFileCreationDate(file)

return file creation date

Parameters: file (str) – full filename (path+filename)

pyCGM2.Utils.files.getFiles(path, extension, ignore=None, raiseFlag=False)

get all files in a folder

Parameters

path (str) – folder path
extension (str) – file extension
ignore (str,Optional[None]) – ignored filenames
raiseFlag (bool,Optional[False]) – raise exception

pyCGM2.Utils.files.getIKweightSet(DATA_PATH, ikwf)

get marker weights for kinematic fitting

Parameters

DATA_PATH (str) – data folder path
ikwf (str) – weights filename

pyCGM2.Utils.files.getMp(mpInfo, resetFlag=True)

return required and optional anthropometric parameters

Parameters

mpInfo (dict) – global mp dictionary
resetFlag (bool,Optional[True]) – reset optional parameters

pyCGM2.Utils.files.getMpFileContent(DATA_PATH, file, subject)

get anthropometric data

Parameters

DATA_PATH (str) – data folder path
file (str) – Filename
subject (str) – subject name

pyCGM2.Utils.files.getTranslators(DATA_PATH, translatorType='CGM1.translators')

get CGM marker translators

Parameters

DATA_PATH (str) – data folder path
translatorType (str,Optional[CGM1.translators]) – translator filename

pyCGM2.Utils.files.loadAnalysis(path, FilenameNoExt)

load an analysis instance

Parameters

path (str) – data folder path
FilenameNoExt (str) – analysis filename without extension

pyCGM2.Utils.files.loadModel(path, FilenameNoExt)

load a pyCGM2 model instance

Parameters

path (str) – data folder path
FilenameNoExt (str) – model filename wthout extension

pyCGM2.Utils.files.loadModelSettings(DATA_PATH, expertsettings_filename)

Load a pyCGM2 model settings.

Parameters

DATA_PATH (str) – data folder path
expertsettings_filename (str) – setting filename

pyCGM2.Utils.files.loadMp(path, filename)

load a mp file.

Parameters

path (str) – data folder path
filename (str) – filename with Extension

pyCGM2.Utils.files.openFile(path, filename)

open a json/yaml file.

Parameters

path (str) – data folder path
filename (str) – filename with Extension

pyCGM2.Utils.files.openPickleFile(path, filename)

open a serialized file.

Parameters

path (str) – data folder path
filename (str) – filename with Extension

pyCGM2.Utils.files.readContent(stringContent)

read a json/yaml content

Parameters: stringContent (str) – json or yaml content

pyCGM2.Utils.files.readXml(DATA_PATH, filename)

Read a xml file

Parameters

DATA_PATH (str) – folder path
filename (str) – xlm filename

pyCGM2.Utils.files.saveAnalysis(analysisInstance, path, FilenameNoExt)

save a pyCGM2 analysis instance

Parameters

pyCGM2.Processing.analysis.Analysis) (model) – an analysis instance
path (str) – data folder path
FilenameNoExt (str) – model filename wthout extension

pyCGM2.Utils.files.saveJson(path, filename, content, ensure_ascii=False)

save as json file

Parameters

path (str) – data folder path
filename (str) – json filename
content (dict) – dictionary to save

pyCGM2.Utils.files.saveModel(model, path, FilenameNoExt)

save a pyCGM2 model instance

Parameters

pyCGM2.Model.model.Model) (model) – a model instance
path (str) – data folder path
FilenameNoExt (str) – model filename wthout extension

pyCGM2.Utils.files.saveMp(mpInfo, model, DATA_PATH, mpFilename)

Save anthropometric parameters as json

Parameters

mpInfo (dict) – global anthropometric parameters
model (pyCGM2.Model.model.Model) – a model instance
DATA_PATH (str) – data folder path
mpFilename (str) – filename

pyCGM2.Utils.files.savePickleFile(instance, path, filename)

serialized a pyCGM2 instance , then save it.

Parameters

instance (object) – a object instance
path (str) – data folder path
filename (str) – filename with Extension

pyCGM2.Utils.files.saveYaml(path, filename, content)

save as yaml file

Parameters

path (str) – data folder path
filename (str) – json filename
content (dict) – dictionary to save

Note: Do not work well with orderdict

utils

pyCGM2.Utils.utils.isInRange(val, min, max)

check if value is in range

Parameters

val (double) – value
min (double) – minimim value
max (double) – maximum value

pyCGM2.Utils.utils.toBool(text)

convert text to bool

Parameters: text (str) – text

Modules

Anomaly

Anomaly Filter

AnomalyDetectionProcedure

AnomalyCorrectionProcedure

EMG module

emgManager

emgFilters

coactivationProcedures

discreteEmgProcedures

normalActivation

Event

eventFilters

eventProcedures

force Plates module

forcePlates

Gap

GapFilters

GapProcedures

Inspector

inspectorFilters

inspectorProcedures

Model

anthropometricMeasurement

bodySegmentParameters

frame

model

modelDecorator

modelFilters

modelQualityFilter

motion

CGM2

cgm

cgm2

decorators

Opensim

opensimFilters

osimProcessing

QTM

qtmTools

Processing

analysis

analysisHandler

analysisProcessing

cycle

exporter

c3dManager

c3dManagerFilters

c3dManagerProcedures

Classification

classificationFilters

classificationProcedures

DiscretePoints

discretePointFilters

discretePointProcedures

JointPatterns

jointPatternFilters

jointPatternProcedures

ProgressionFrame

progressionFrameFilters

progressionFrameProcedures

Representative

representativeFilters

representativeProcedures

Scores

scoreFilters

scoreProcedures

Report

normativeDatasets

plot

plotFilters

plotUtils

Viewers

plotViewers

emgPlotViewers

comparisonPlotViewers

Signal

anomaly

detect_changes

detect_onset