pose2sim/Pose2Sim/Utilities/trc_gaitevents.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-


'''
    ##################################################
    ## GAIT EVENTS DETECTION                        ##
    ##################################################
    
    Determine gait on and off from a TRC file of point coordinates.
    
    N.B.: Could implement the methods listed there in the future. 
          Please feel free to make a pull-request or keep me informed if you do so!

    Three available methods, each of them with their own pros and cons: 

    - "forward_coordinates": 
        on =  max(XHeel - Xsacrum)
        off = min(XToe - XSacrum)
        ++: Works well for walking (Zeni et al., 2008)
        ++: No argument nor tuning necessary
        --: Not suitable for running
        --: does not work if the person is not going on a straight line

    - "height_coordinates": 
        on =  YToe < height_threshold
        off = YToe > height_threshold
        ++: Best results for running and walking
        ++: Works if the person is not going on a straight line
        --: Does not work is the person is grazing the ground
        --: Does not work if the field is not flat
        --: height_threshold might need to be tuned
        --: Heel point might be more accurate than toe point for walking

    - "forward_velocity": 
        on =  VToe < forward_velocity_threshold
        off = VToe > forward_velocity_threshold
        ++: Works for running
        --: More sensitive to noise
        --: Tends to anticipate off if the marker is not at the tip of the toe
        --: forward_velocity_threshold might need to be tuned
        --: Does not work if the person is not going on a straight line
    
    Usage: 
    List of available arguments:
        python -m trc_gaitevents -h

        import trc_gaitevents; trc_gaitevents.trc_gaitevents_func(trc_path=r'<input_trc_file>')
        OR import trc_gaitevents; trc_gaitevents.trc_gaitevents_func(trc_path=r'<input_trc_file>', method='forward_coordinates', gait_direction='-X', plot=True, save_output=True, output_file='gaitevents.txt')
        OR import trc_gaitevents; trc_gaitevents.trc_gaitevents_func(trc_path=r'<input_trc_file>', method='height_coordinates', up_direction='Y', height_threshold=6, right_toe_marker='RBigToe', left_toe_marker='LBigToe')
        OR import trc_gaitevents; trc_gaitevents.trc_gaitevents_func(trc_path=r'<input_trc_file>', method='forward_velocity', gait_direction='-Z', forward_velocity_threshold=1, right_toe_marker='RBigToe', left_toe_marker='LBigToe')
        
        python -m trc_gaitevents -i input_trc_file
        OR python -m trc_gaitevents -i input_trc_file --method forward_coordinates --gait_direction=-X --plot True --save_output True --output_file gaitevents.txt
        OR python -m trc_gaitevents -i input_trc_file --method height_coordinates --up_direction=Y --height_threshold 6 --right_toe_marker RBigToe --left_toe_marker LBigToe
        OR python -m trc_gaitevents -i input_trc_file --method forward_velocity --gait_direction=-Z --forward_velocity_threshold 1 --right_toe_marker RBigToe --left_toe_marker LBigToe
'''


## INIT
import os
import argparse
import pandas as pd
import numpy as np
from scipy import signal
from scipy.ndimage import gaussian_filter1d
import matplotlib.pyplot as plt


## AUTHORSHIP INFORMATION
__author__ = "David Pagnon"
__copyright__ = "Copyright 2021, Pose2Sim"
__credits__ = ["David Pagnon"]
__license__ = "BSD 3-Clause License"
__version__ = "0.9.4"
__maintainer__ = "David Pagnon"
__email__ = "contact@david-pagnon.com"
__status__ = "Development"


## FUNCTIONS
def start_end_true_seq(series):
    '''
    Find starts and ends of sequences of True values in a pandas Series

    INPUTS:
    - series: pandas Series of boolean values

    OUTPUTS:
    - start_indices: list of start indices
    - end_indices: list of end indices
    '''

    diff = series.ne(series.shift())
    start_indices = series.index[diff & series].tolist()
    end_indices = (series.index[diff & ~series]-1).tolist()
    if end_indices[0] == -1: end_indices.pop(0)

    return start_indices, end_indices


def read_trc(trc_path):
    '''
    Read trc file

    INPUTS:
    - trc_path: path to the trc file

    OUTPUTS:
    - Q_coords: dataframe of coordinates
    - frames_col: series of frames
    - time_col: series of time
    - markers: list of marker names
    - header: list of header lines
    '''
    
    with open(trc_path, 'r') as trc_file:
        header = [next(trc_file) for line in range(5)]
    markers = header[3].split('\t')[2::3]
    
    trc_df = pd.read_csv(trc_path, sep="\t", skiprows=4)
    frames_col, time_col = pd.Series(trc_df.iloc[:,0], name='frames'), pd.Series(trc_df.iloc[:,1], name='time')
    Q_coords = trc_df.drop(trc_df.columns[[0, 1]], axis=1)

    return Q_coords, frames_col, time_col, markers, header


def first_step_side(Ron, Lon):
    '''
    Get first step side

    INPUTS:
    - Ron: list of right on times or frames
    - Lon: list of left on times or frames

    OUTPUTS:
    - first_side: 'R' if right first, 'L' if left first
    '''

    if Ron[0]<Lon[0]: 
        first_side = 'R'
    else:
        first_side = 'L'

    return first_side


def clean_gait_events(gait_events):
    '''
    Clean gait events to only keep right-left alternating and full contact pairs

    INPUTS:
    - gait_events: tuple of lists (Ron, Lon, Roff, Loff)

    OUTPUTS:
    - Ron, Lon, Roff, Loff = cleaned gait events
    '''

    Ron, Lon, Roff, Loff = gait_events

    # Remove incomplete pairs at the start and end
    if Ron[0]>Roff[0]: Roff.pop(0)
    if Lon[0]>Loff[0]: Loff.pop(0)

    if Ron[-1]>Roff[-1]: Ron.pop(-1)
    if Lon[-1]>Loff[-1]: Lon.pop(-1)

    # Remove lonely pairs that are not alternating with the other side at the beginning or the end
    if Ron[0]<Lon[0]: # Right first
        while Ron[1]<Lon[0]: Ron.pop(0)
        while Lon[-2]>Ron[-1]: Lon.pop(-1)
        while Roff[1]<Loff[0]: Roff.pop(0)
        while Loff[-2]>Roff[-1]: Loff.pop(-1)
        
    else: # Left first
        while Lon[1]<Ron[0]: Lon.pop(0)
        while Ron[-2]>Lon[-1]: Ron.pop(-1)
        while Loff[1]<Roff[0]: Loff.pop(0)
        while Roff[-2]>Loff[-1]: Roff.pop(-1)
        

    return Ron, Lon, Roff, Loff


def gait_events_fwd_coords(trc_path, gait_direction, markers=['RHeel', 'RBigToe', 'LHeel', 'LBigToe', 'Hip'], plot=True):
    '''
    Determine gait on and off with "forward_coordinates" method
    
    on =  max(XHeel - Xsacrum)
    off = min(XToe - XSacrum)
    ++: Works well for walking (Zeni et al., 2008)
    ++: No argument nor tuning necessary
    --: Not suitable for running
    --: does not work if the person is not going on a straight line

    INPUTS:
    - trc_path: path to the trc file
    - gait_direction: tuple (sign, direction) with sign in {-1, 1} and direction in {'X', 'Y', 'Z'}
    - markers: list of marker names in the following order: [right_heel_marker, right_toe_marker, left_heel_marker, left_toe_marker, sacrum_marker]
    - plot: plot results or not (boolean)

    OUTPUTS:
    - t_Ron: list of right on times
    - t_Lon: list of left on times
    - t_Roff: list of right off times
    - t_Loff: list of left off times
    '''

    # Retrieve gait direction
    sign, direction = gait_direction
    axis = ['X', 'Y', 'Z'].index(direction)

    # Read trc file
    Q_coords, _, time_col, trc_markers, header = read_trc(trc_path)

    unit = header[2].split('\t')[4]
    peak_prominence = .1 if unit=='m' else 1 if unit=='dm' else 10 if unit=='cm' else 100 if unit=='mm' else np.inf

    RHeel_idx, RBigToe_idx, LHeel_idx, LBigToe_idx, Hip_idx = [trc_markers.index(m) for m in markers]
    RHeel_df, RBigToe_df, LHeel_df, LBigToe_df, Hip_df = (Q_coords.iloc[:,axis+idx*3] for idx in [RHeel_idx, RBigToe_idx, LHeel_idx, LBigToe_idx, Hip_idx])

    # Find gait events
    max_r_heel_hip_proj = sign*(RHeel_df-Hip_df)
    frame_Ron = signal.find_peaks(max_r_heel_hip_proj, prominence=peak_prominence)[0].tolist()
    t_Ron = time_col[frame_Ron].tolist()

    max_l_heel_hip_proj = sign*(LHeel_df-Hip_df)
    frame_Lon = signal.find_peaks(max_l_heel_hip_proj, prominence=peak_prominence)[0].tolist()
    t_Lon = time_col[frame_Lon].tolist()

    max_r_hip_toe_proj = sign*(Hip_df-RBigToe_df)
    frame_Roff = signal.find_peaks(max_r_hip_toe_proj, prominence=peak_prominence)[0].tolist()
    t_Roff = time_col[frame_Roff].tolist()

    max_l_hip_toe_proj = sign*(Hip_df-LBigToe_df)
    frame_Loff = signal.find_peaks(max_l_hip_toe_proj, prominence=peak_prominence)[0].tolist()
    t_Loff = time_col[frame_Loff].tolist()

    # Clean gait events
    frame_Ron, frame_Lon, frame_Roff, frame_Loff = clean_gait_events((frame_Ron, frame_Lon, frame_Roff, frame_Loff))
    t_Ron, t_Lon, t_Roff, t_Loff = clean_gait_events((t_Ron, t_Lon, t_Roff, t_Loff))

    # Plot
    if plot:
        plt.plot(time_col, max_r_heel_hip_proj, 'C0', label='Right on')
        plt.plot(time_col[frame_Ron], max_r_heel_hip_proj[frame_Ron], 'g+')

        plt.plot(time_col, max_l_heel_hip_proj, 'C1', label='Left on')
        plt.plot(time_col[frame_Lon], max_l_heel_hip_proj[frame_Lon], 'g+')

        plt.plot(time_col, max_r_hip_toe_proj, 'C0', label='Right off')
        plt.plot(time_col[frame_Roff], max_r_hip_toe_proj[frame_Roff], 'r+')

        plt.plot(time_col, max_l_hip_toe_proj, 'C1', label='Left off')
        plt.plot(time_col[frame_Loff], max_l_hip_toe_proj[frame_Loff], 'r+')

        plt.title('Gait events')
        plt.xlabel('Time (s)')
        plt.ylabel('Distance (cm)')
        plt.legend()
        plt.show()

    print('Times:')
    print('Right on:', t_Ron)
    print('Right off:', t_Roff)
    print('Left on:', t_Lon)
    print('Left off:', t_Loff)
    print('\nFrames:')
    print('Right on:', frame_Ron)
    print('Right off:', frame_Roff)
    print('Left on:', frame_Lon)
    print('Left off:', frame_Loff)

    return (t_Ron, t_Lon, t_Roff, t_Loff), (frame_Ron, frame_Lon, frame_Roff, frame_Loff)


def gait_events_height_coords(trc_path, up_direction, height_threshold=6, filter_fs=10, markers=['RBigToe', 'LBigToe'], plot=True):
    '''
    Determine gait on and off with "height_coordinates" method
    
    on =  YToe < height_threshold
    off = YToe > height_threshold
    ++: Best results for running and walking
    ++: Works if the person is not going on a straight line
    --: Does not work is the person is grazing the ground
    --: Does not work if the field is not flat
    --: height_threshold might need to be tuned
    --: Heel point might be more accurate than toe point for walking

    INPUTS:
    - trc_path: path to the trc file
    - up_direction: tuple (sign, direction) with sign in {-1, 1} and direction in {'X', 'Y', 'Z'}
    - height_threshold: height below which the foot is considered to have touched the ground (cm)
    - filter_fs: butterworth filter cutoff frequency (Hz)
    - markers: list of marker names in the following order: [right_toe_marker, left_toe_marker]
    - plot: plot results or not (boolean)

    OUTPUTS:
    - t_Ron: list of right on times
    - t_Lon: list of left on times
    - t_Roff: list of right off times
    - t_Loff: list of left off times
    '''

    # Retrieve gait direction
    sign, direction = up_direction
    axis = ['X', 'Y', 'Z'].index(direction)

    # Read trc file
    Q_coords, _, time_col, trc_markers, header = read_trc(trc_path)
    unit = header[2].split('\t')[4]
    unit_factor = 100 if unit=='m' else 10 if unit=='dm' else 1 if unit=='cm' else .1 if unit=='mm' else np.inf
    Q_coords *= unit_factor

    # Calculate height
    Y_height = Q_coords.iloc[:,axis::3]
    Y_height.columns = trc_markers
    Rfoot_height, Lfoot_height = (Y_height[m] for m in markers)

    dt = time_col.diff().mean()
    b, a = signal.butter(4/2, filter_fs*dt*2, 'low', analog=False)
    Rfoot_height_filtered = pd.Series(signal.filtfilt(b, a, Rfoot_height[1:]), name=Rfoot_height.name)
    Lfoot_height_filtered = pd.Series(signal.filtfilt(b, a, Lfoot_height[1:]), name=Lfoot_height.name)

    # Find gait events
    low_Rfoot_height = Rfoot_height_filtered<height_threshold
    frame_Ron, frame_Roff = start_end_true_seq(low_Rfoot_height)
    if 0 in frame_Ron: frame_Ron.remove(0)
    t_Ron, t_Roff = time_col[frame_Ron].tolist(), time_col[frame_Roff].tolist()

    low_Lfoot_height = Lfoot_height_filtered<height_threshold
    frame_Lon, frame_Loff = start_end_true_seq(low_Lfoot_height)
    if 0 in frame_Lon: frame_Lon.remove(0)
    t_Lon, t_Loff = time_col[frame_Lon].tolist(), time_col[frame_Loff].tolist()

    # Clean gait events
    frame_Ron, frame_Lon, frame_Roff, frame_Loff = clean_gait_events((frame_Ron, frame_Lon, frame_Roff, frame_Loff))
    t_Ron, t_Lon, t_Roff, t_Loff = clean_gait_events((t_Ron, t_Lon, t_Roff, t_Loff))

    # Plot
    if plot:
        plt.plot(time_col[1:], Rfoot_height_filtered, 'C0', label='Right foot height filtered')
        plt.plot(time_col[1:][frame_Ron], Rfoot_height_filtered[frame_Ron], 'g+')
        plt.plot(time_col[1:][frame_Roff], Rfoot_height_filtered[frame_Roff], 'r+')

        plt.plot(time_col[1:], Lfoot_height_filtered, 'C1', label='Left foot height filtered')
        plt.plot(time_col[1:][frame_Lon], Lfoot_height_filtered[frame_Lon], 'g+')
        plt.plot(time_col[1:][frame_Loff], Lfoot_height_filtered[frame_Loff], 'r+')

        plt.title('Gait events')
        plt.xlabel('Time (s)')
        plt.ylabel('Height (cm)')
        plt.legend()
        plt.show()

    print('Times:')
    print('Right on:', t_Ron)
    print('Right off:', t_Roff)
    print('Left on:', t_Lon)
    print('Left off:', t_Loff)
    print('\nFrames:')
    print('Right on:', frame_Ron)
    print('Right off:', frame_Roff)
    print('Left on:', frame_Lon)
    print('Left off:', frame_Loff)

    return (t_Ron, t_Lon, t_Roff, t_Loff), (frame_Ron, frame_Lon, frame_Roff, frame_Loff)


def gait_events_fwd_vel(trc_path, gait_direction, forward_velocity_threshold=1, filter_fs=10, markers=['RBigToe', 'LBigToe'], plot=True):
    '''
    Determine gait on and off with "forward_velocity" method
    
    on =  VToe < forward_velocity_threshold
    off = VToe > forward_velocity_threshold
    ++: Works for running and walking
    --: Tends to anticipate off if marker is not at the tip of the toe
    --: forward_velocity_threshold might need to be tuned
    --: does not work if the person is not going on a straight line
    
    INPUTS:
    - trc_path: path to the trc file
    - gait_direction: tuple (sign, direction) with sign in {-1, 1} and direction in {'X', 'Y', 'Z'}
    - forward_velocity_threshold: forward velocity below which the foot is considered to have touched the ground (m/s)
    - filter_fs: butterworth filter cutoff frequency (Hz)
    - markers: list of marker names in the following order: [right_toe_marker, left_toe_marker]
    - plot: plot results or not (boolean)

    OUTPUTS:
    - t_Ron: list of right on times
    - t_Lon: list of left on times
    - t_Roff: list of right off times
    - t_Loff: list of left off times
    '''
    
    # Retrieve gait direction
    sign, direction = gait_direction
    axis = ['X', 'Y', 'Z'].index(direction)

    # Read trc file
    Q_coords, _, time_col, trc_markers, header = read_trc(trc_path)
    unit = header[2].split('\t')[4]
    unit_factor = 1 if unit=='m' else 10 if unit=='dm' else 100 if unit=='cm' else 1000 if unit=='mm' else np.inf
    forward_velocity_threshold *= unit_factor
    Q_coords *= unit_factor

    # Calculate speed
    dt = time_col.diff().mean()
    b, a = signal.butter(4/2, filter_fs*dt*2, 'low', analog=False)
    X_speed = Q_coords.iloc[:,axis::3].diff()/dt
    X_speed.columns = trc_markers
    Rfoot_speed, Lfoot_speed = (X_speed[m] for m in markers)

    Rfoot_speed = Rfoot_speed.where(Rfoot_speed<0, other=0) if sign==-1 else Rfoot_speed.where(Rfoot_speed>0, other=0)
    Rfoot_speed = Rfoot_speed.abs()
    # Rfoot_speed_filtered = pd.Series(signal.filtfilt(b, a, Rfoot_speed[1:]), name=Rfoot_speed.name)
    Rfoot_speed_filtered = pd.Series(gaussian_filter1d(Rfoot_speed[1:], 5), name=Rfoot_speed.name)
        
    Lfoot_speed = Lfoot_speed.where(Lfoot_speed<0, other=0) if sign==-1 else Lfoot_speed.where(Lfoot_speed>0, other=0)
    Lfoot_speed = Lfoot_speed.abs()
    # Lfoot_speed_filtered = pd.Series(signal.filtfilt(b, a, Lfoot_speed[1:]), name=Lfoot_speed.name)
    Lfoot_speed_filtered = pd.Series(gaussian_filter1d(Lfoot_speed[1:], 5), name=Lfoot_speed.name)

    # Find gait events
    low_Rfoot_speed = Rfoot_speed_filtered<forward_velocity_threshold
    frame_Ron, frame_Roff = start_end_true_seq(low_Rfoot_speed)
    if 0 in frame_Ron: frame_Ron.remove(0)
    t_Ron, t_Roff = time_col[frame_Ron].tolist(), time_col[frame_Roff].tolist()

    low_Lfoot_speed = Lfoot_speed_filtered<forward_velocity_threshold
    frame_Lon, frame_Loff = start_end_true_seq(low_Lfoot_speed)
    if 0 in frame_Lon: frame_Lon.remove(0)
    t_Lon, t_Loff = time_col[frame_Lon].tolist(), time_col[frame_Loff].tolist()

    # Clean gait events
    frame_Ron, frame_Lon, frame_Roff, frame_Loff = clean_gait_events((frame_Ron, frame_Lon, frame_Roff, frame_Loff))
    t_Ron, t_Lon, t_Roff, t_Loff = clean_gait_events((t_Ron, t_Lon, t_Roff, t_Loff))

    # Plot
    if plot:
        plt.plot(time_col[1:], Rfoot_speed_filtered, 'C0', label='Right foot speed filtered')
        plt.plot(time_col[1:][frame_Ron], Rfoot_speed_filtered[frame_Ron], 'g+')
        plt.plot(time_col[1:][frame_Roff], Rfoot_speed_filtered[frame_Roff], 'r+')

        plt.plot(time_col[1:], Lfoot_speed_filtered, 'C1', label='Left foot speed filtered')
        plt.plot(time_col[1:][frame_Lon], Lfoot_speed_filtered[frame_Lon], 'g+')
        plt.plot(time_col[1:][frame_Loff], Lfoot_speed_filtered[frame_Loff], 'r+')

        plt.title('Gait events')
        plt.xlabel('Time (s)')
        plt.ylabel('Speed (m/s)')
        plt.legend()
        plt.show()

    print('Times:')
    print('Right on:', t_Ron)
    print('Right off:', t_Roff)
    print('Left on:', t_Lon)
    print('Left off:', t_Loff)
    print('\nFrames:')
    print('Right on:', frame_Ron)
    print('Right off:', frame_Roff)
    print('Left on:', frame_Lon)
    print('Left off:', frame_Loff)

    return (t_Ron, t_Lon, t_Roff, t_Loff), (frame_Ron, frame_Lon, frame_Roff, frame_Loff)


def trc_gaitevents_func(**args):
    '''
    Determine gait on and off from a TRC file of point coordinates.
    Three available methods, each of them with their own pros and cons: 

    - "forward_coordinates": 
        on =  max(XHeel - Xsacrum)
        off = min(XToe - XSacrum)
        ++: Works well for walking (Zeni et al., 2008)
        ++: No argument nor tuning necessary
        --: Not suitable for running
        --: does not work if the person is not going on a straight line

    - "height_coordinates": 
        on =  YToe < height_threshold
        off = YToe > height_threshold
        ++: Best results for running and walking
        ++: Works if the person is not going on a straight line
        --: Does not work is the person is grazing the ground
        --: Does not work if the field is not flat
        --: height_threshold might need to be tuned
        --: Heel point might be more accurate than toe point for walking

    - "forward_velocity": 
        on =  VToe < forward_velocity_threshold
        off = VToe > forward_velocity_threshold
        ++: Works for running
        --: More sensitive to noise
        --: Tends to anticipate off if the marker is not at the tip of the toe
        --: forward_velocity_threshold might need to be tuned
        --: Does not work if the person is not going on a straight line
    
    Usage: 
    List of available arguments:
        python -m trc_gaitevents -h

        import trc_gaitevents; trc_gaitevents.trc_gaitevents_func(trc_path=r'<input_trc_file>')
        OR import trc_gaitevents; trc_gaitevents.trc_gaitevents_func(trc_path=r'<input_trc_file>', method='forward_coordinates', gait_direction='-X', plot=True, save_output=True, output_file='gaitevents.txt')
        OR import trc_gaitevents; trc_gaitevents.trc_gaitevents_func(trc_path=r'<input_trc_file>', method='height_coordinates', up_direction='Y', height_threshold=6, right_toe_marker='RBigToe', left_toe_marker='LBigToe')
        OR import trc_gaitevents; trc_gaitevents.trc_gaitevents_func(trc_path=r'<input_trc_file>', method='forward_velocity', gait_direction='-Z', forward_velocity_threshold=1, right_toe_marker='RBigToe', left_toe_marker='LBigToe')
        
        python -m trc_gaitevents -i input_trc_file
        OR python -m trc_gaitevents -i input_trc_file --method forward_coordinates --gait_direction=-X --plot True --save_output True --output_file gaitevents.txt
        OR python -m trc_gaitevents -i input_trc_file --method height_coordinates --up_direction=Y --height_threshold 6 --right_toe_marker RBigToe --left_toe_marker LBigToe
        OR python -m trc_gaitevents -i input_trc_file --method forward_velocity --gait_direction=-Z --forward_velocity_threshold 1 --right_toe_marker RBigToe --left_toe_marker LBigToe
    '''

    # Retrieve arguments
    trc_path = args.get('trc_path')
    gait_direction = args.get('gait_direction')
    up_direction = args.get('up_direction')
    method = args.get('method')
    forward_velocity_threshold = args.get('forward_velocity_threshold')
    height_threshold = args.get('height_threshold')
    sacrum_marker = args.get('sacrum_marker')
    right_heel_marker = args.get('right_heel_marker')
    right_toe_marker = args.get('right_toe_marker')
    left_heel_marker = args.get('left_heel_marker')
    left_toe_marker = args.get('left_toe_marker')
    plot = args.get('plot')
    save_output = args.get('save_output')
    output_file = args.get('output_file')

    filter_fs = 6

    # If invoked via a function
    if gait_direction == None: gait_direction = '+X'
    if up_direction == None: up_direction = '+Y'
    if method == None: method = 'height_coordinates'
    if forward_velocity_threshold == None: forward_velocity_threshold = 1
    if height_threshold == None: height_threshold = 6
    if sacrum_marker == None: sacrum_marker = 'Hip'
    if right_heel_marker == None: right_heel_marker = 'RHeel'
    if right_toe_marker == None: right_toe_marker = 'RBigToe'
    if left_heel_marker == None: left_heel_marker = 'LHeel'
    if left_toe_marker == None: left_toe_marker = 'LBigToe'
    if plot == None: plot = True
    if save_output == None: save_output = True
    if output_file == None: output_file = 'gaitevents.txt'

    # In case of a sign in direction (eg -X)
    if len(gait_direction)==1:
        gait_direction = +1, gait_direction
    elif len(gait_direction)==2:
        gait_direction = int(gait_direction[0]+'1'), gait_direction[1]
    if len(up_direction)==1:
        up_direction = +1, up_direction
    elif len(up_direction)==2:
        up_direction = int(up_direction[0]+'1'), up_direction

    if method not in ['forward_coordinates', 'height_coordinates', 'forward_velocity']:
        raise ValueError('Method must be "forward_coordinates", "height_coordinates", or "forward_velocity"')

    # Retrieve gait events
    if method == 'forward_coordinates':
        print('Method: forward_coordinates')
        markers = [right_heel_marker, right_toe_marker, left_heel_marker, left_toe_marker, sacrum_marker]
        (t_Ron, t_Lon, t_Roff, t_Loff), (frame_Ron, frame_Lon, frame_Roff, frame_Loff) \
                                = gait_events_fwd_coords(trc_path, gait_direction, markers=markers, plot=plot)
    elif method == 'height_coordinates':
        print(f'Method: height_coordinates. Height threshold: {height_threshold} cm')
        markers = [right_toe_marker, left_toe_marker]
        (t_Ron, t_Lon, t_Roff, t_Loff), (frame_Ron, frame_Lon, frame_Roff, frame_Loff) \
                                = gait_events_height_coords(trc_path, up_direction, height_threshold=height_threshold, filter_fs=filter_fs, markers=markers, plot=plot)
    elif method == 'forward_velocity':
        print(f'Method: forward_velocity. Forward velocity threshold: {forward_velocity_threshold} m/s')
        markers = [right_toe_marker, left_toe_marker]
        (t_Ron, t_Lon, t_Roff, t_Loff), (frame_Ron, frame_Lon, frame_Roff, frame_Loff) \
                                = gait_events_fwd_vel(trc_path, gait_direction, forward_velocity_threshold=forward_velocity_threshold, filter_fs=filter_fs, markers=markers, plot=plot)

    if save_output or save_output==None:
        trc_dir = os.path.dirname(trc_path)
        trc_name = os.path.basename(trc_path)
        if output_file == None: output_file = 'gaitevents.txt'
        with open(os.path.join(trc_dir, output_file), 'a') as gaitevents:
            L = trc_name + '\n'
            L += f'Method: {method}. '
            L+= f'Height threshold: {height_threshold}\n' if method=='height_coordinates' else f'Forward velovity threshold: {forward_velocity_threshold}\n' if method == 'forward_velocity' else '\n'
            L += 'Times:\n'
            L += '\tRight on: ' + str(t_Ron) + '\n'
            L += '\tLeft on: ' + str(t_Lon) + '\n'
            L += '\tRight off: ' + str(t_Roff) + '\n'
            L += '\tLeft off: ' + str(t_Loff) + '\n'
            L += 'Frames:\n'
            L += '\tRight on: ' + str(frame_Ron) + '\n'
            L += '\tLeft on: ' + str(frame_Lon) + '\n'
            L += '\tRight off: ' + str(frame_Roff) + '\n'
            L += '\tLeft off: ' + str(frame_Loff) + '\n\n'

            gaitevents.write(L)
    
    return (t_Ron, t_Lon, t_Roff, t_Loff), (frame_Ron, frame_Lon, frame_Roff, frame_Loff)


if __name__ == '__main__':
    parser = argparse.ArgumentParser(description='Determine gait on and off with "forward_coordinates", "height_coordinates", or "forward_velocity" method. More details in the file description.')
    parser.add_argument('-i', '--trc_path', required = True, help='Trc input file')
    parser.add_argument('-g', '--gait_direction', default = 'X', required = False, help='Direction of the gait. "X", "Y", "Z", "-X", "-Y", or "-Z". Default: "X". Requires an equal sign if negative, eg -g=-X')
    parser.add_argument('-u', '--up_direction', default = 'Y', required = False, help='Up direction. "X", "Y", or "Z", "-X", "-Y", or "-Z". Default: "Y"')
    parser.add_argument('-m', '--method', default = 'height_coordinates', required = False, help='Method to determine gait events. "forward_coordinates", "height_coordinates", or "forward_velocity". Default:"height_coordinates"')
    parser.add_argument('-V', '--forward_velocity_threshold', default = 1, type=float, required = False, help='Forward velocity below which the foot is considered to have touched the ground (m/s). Used if method is forward_velocity. Default: 1.5')
    parser.add_argument('-H', '--height_threshold', default = 6, type=float, required = False, help='Height below which the foot is considered to have touched the ground (cm). Used if method is height_coordinates. Default: 6')
    parser.add_argument('--sacrum_marker', default = 'Hip', required = False, help='Hip marker name. Default: "Hip"')
    parser.add_argument('--right_heel_marker', default = 'RHeel', required = False, help='Right heel marker name. Default: "RHeel"')
    parser.add_argument('--right_toe_marker', default = 'RBigToe', required = False, help='Right toe marker name. Default: "RBigToe"')
    parser.add_argument('--left_heel_marker', default = 'LHeel', required = False, help='Left heel marker name. Default: "LHeel"')
    parser.add_argument('--left_toe_marker', default = 'LBigToe', required = False, help='Left toe marker name. Default: "LBigToe"')
    parser.add_argument('-p', '--plot', default = True, required = False, help='Plot results. Default: True')
    parser.add_argument('-s', '--save_output', default = True, required = False, help='Save output in csv file. Default: True')
    parser.add_argument('-o', '--output_file', default = 'gaitevents.txt', required = False, help='Output file name. Default: "gaitevents.txt"')

    args = vars(parser.parse_args())
    
    trc_gaitevents_func(**args)