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


'''
    ##################################################
    ## Build trc from mot and osim files            ##
    ##################################################
    
    Build a trc file which stores all real and virtual markers 
    calculated from a .mot motion file and a .osim model file.
    
    Usage: 
    from Pose2Sim.Utilities import trc_from_mot_osim; trc_from_mot_osim.trc_from_mot_osim_func(r'<input_mot_file>', r'<output_osim_file>', r'<output_trc_file>')
    python -m trc_from_mot_osim -m input_mot_file -o input_osim_file
    python -m trc_from_mot_osim -m input_mot_file -o input_osim_file -t output_trc_file
'''


## INIT
import os
import pandas as pd
import numpy as np
import opensim as osim
import argparse


## AUTHORSHIP INFORMATION
__author__ = "David Pagnon"
__copyright__ = "Copyright 2021, Pose2Sim"
__credits__ = ["David Pagnon"]
__license__ = "BSD 3-Clause License"
__version__ = "0.4"
__maintainer__ = "David Pagnon"
__email__ = "contact@david-pagnon.com"
__status__ = "Development"


## FUNCTIONS
def get_marker_positions(motion_data, model):
    '''
    Get dataframe of marker positions
    
    INPUTS: 
    - motion_data: .mot file opened with osim.TimeSeriesTable
    - model: .osim file opened with osim.Model 
    
    OUTPUT:
    - marker_positions_pd: DataFrame of marker positions 
    '''
    
    # Markerset
    marker_set = model.getMarkerSet()
    marker_set_names = [mk.getName() for mk in list(marker_set)]
    marker_set_names_xyz = np.array([[m+'_x', m+'_y', m+'_z'] for m in marker_set_names]).flatten()

    # Data
    times = motion_data.getIndependentColumn()
    joint_angle_set_names = motion_data.getColumnLabels() # or [c.getName() for c in model.getCoordinateSet()]
    motion_data_pd = pd.DataFrame(motion_data.getMatrix().to_numpy(), columns=joint_angle_set_names)

    # Get marker positions at each state
    state = model.initSystem()
    marker_positions = []
    for n,t in enumerate(times):
        # put the model in the right position
        for coord in joint_angle_set_names:
            if not coord.endswith('_tx') and not coord.endswith('_ty') and not coord.endswith('_tz'):
                value = motion_data_pd.loc[n,coord]*np.pi/180
            else:
                value = motion_data_pd.loc[n,coord]
            model.getCoordinateSet().get(coord).setValue(state,value)
        # get marker positions
        marker_positions += [np.array([marker_set.get(mk_name).findLocationInFrame(state, model.getGround()).to_numpy() for mk_name in marker_set_names]).flatten()]
    marker_positions_pd = pd.DataFrame(marker_positions, columns=marker_set_names_xyz)
    marker_positions_pd.insert(0, 'time', times)
    marker_positions_pd.insert(0, 'frame', np.arange(len(times)))
    
    return marker_positions_pd
    
    
def trc_from_mot_osim_func(*args):
    '''
    Build a trc file which stores all real and virtual markers 
    calculated from a .mot motion file and a .osim model file.
    
    Usage: 
    from Pose2Sim.Utilities import trc_from_mot_osim; trc_from_mot_osim.trc_from_mot_osim_func(r'<input_mot_file>', r'<output_osim_file>', r'<trc_output_file>')
    python -m trc_from_mot_osim -m input_mot_file -o input_osim_file
    python -m trc_from_mot_osim -m input_mot_file -o input_osim_file -t trc_output_file
    '''

    try:
        motion_path = args[0]['input_mot_file'] # invoked with argparse
        osim_path = args[0]['input_osim_file']
        if args[0]['trc_output_file'] == None:
            trc_path = motion_path.replace('.mot', '.trc')
        else:
            trc_path = args[0]['trc_output_file']
    except:
        motion_path = args[0] # invoked as a function
        osim_path = args[1]
        try:
            trc_path = args[2]
        except:
            trc_path = motion_path.replace('.mot', '.trc')

    # Create dataframe with marker positions
    model = osim.Model(osim_path)
    motion_data = osim.TimeSeriesTable(motion_path)
    marker_positions_pd = get_marker_positions(motion_data, model)
    
    # Trc header
    times = motion_data.getIndependentColumn()
    marker_set = model.getMarkerSet()
    marker_set_names = [mk.getName() for mk in list(marker_set)]
    
    fps = str(int( 1/ (times[1]-times[0]) / (len(times)-1) ))
    nb_frames = str(len(times))
    nb_markers = str(len(marker_set_names))
    header0_str = 'PathFileType\t4\t(X/Y/Z)\t' + os.path.basename(trc_path)

    header1 = {}
    header1['DataRate'] = fps
    header1['CameraRate'] = fps
    header1['NumFrames'] = nb_frames
    header1['NumMarkers'] = nb_markers
    header1['Units'] = 'm'
    header1['OrigDataRate'] = fps
    header1['OrigDataStartFrame'] = '0'
    header1['OrigNumFrames'] = nb_frames
    header1_str1 = '\t'.join(header1.keys())
    header1_str2 = '\t'.join(header1.values())

    header2_str1 = 'Frame#\tTime\t' + '\t\t\t'.join([mk.strip() for mk in marker_set_names]) + '\t\t'
    header2_str2 = '\t\t'+'\t'.join(['X{i}\tY{i}\tZ{i}'.format(i=i+1) for i in range(int(header1['NumMarkers']))])

    header_trc = '\n'.join([header0_str, header1_str1, header1_str2, header2_str1, header2_str2])
    
    # write data
    with open(trc_path, 'w') as trc_o:
        trc_o.write(header_trc+'\n')
    marker_positions_pd.to_csv(trc_path, header=False, sep = '\t', mode='a', index=False)
    
    
if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('-m', '--input_mot_file', required = True, help='input mot file')
    parser.add_argument('-o', '--input_osim_file', required = True, help='input osim file')
    parser.add_argument('-t', '--trc_output_file', required=False, help='trc output file')
    args = vars(parser.parse_args())
    
    trc_from_mot_osim_func(args)