#!/usr/bin/env python # -*- coding: utf-8 -*- ''' ################################################## ## Build csv from mot and osim files ## ################################################## Build a csv file which stores locations and orientations of all bodies calculated from a .mot motion file and a .osim model file. Equivalent to OpenSim Analysis -> BodyKinematics but without the bugs in orientations due to their use of Euler angle instead of homography matrices Transforms from OpenSim's yup to Blender's zup unless you set direction = 'yup' Usage: from Pose2Sim.Utilities import bodykin_from_mot_osim; bodykin_from_mot_osim.bodykin_from_mot_osim_func(r'', r'', r'') python -m bodykin_from_mot_osim -m input_mot_file -o input_osim_file python -m bodykin_from_mot_osim -m input_mot_file -o input_osim_file -c output_csv_file ''' ## INIT import os import numpy as np import opensim as osim import argparse direction = 'zup' # 'zup' or 'yup' ## AUTHORSHIP INFORMATION __author__ = "David Pagnon, Jonathan Camargo" __copyright__ = "Copyright 2023, BlendOSim & Sim2Blend" __credits__ = ["David Pagnon", "Jonathan Camargo"] __license__ = "MIT License" __version__ = "0.0.1" __maintainer__ = "David Pagnon" __email__ = "contact@david-pagnon.com" __status__ = "Development" def bodykin_from_mot_osim_func(*args): ''' Build a csv file which stores locations and orientations of all bodies calculated from a .mot motion file and a .osim model file. Equivalent to OpenSim Analysis -> BodyKinematics but without the bugs in orientations due to their use of Euler angle instead of homography matrices Usage: from Pose2Sim.Utilities import bodykin_from_mot_osim; bodykin_from_mot_osim.bodykin_from_mot_osim_func(r'', r'', r'') python -m bodykin_from_mot_osim -m input_mot_file -o input_osim_file python -m bodykin_from_mot_osim -m input_mot_file -o input_osim_file -t output_csv_file ''' try: motion_path = args[0]['input_mot_file'] # invoked with argparse osim_path = args[0]['input_osim_file'] if args[0]['csv_output_file'] == None: output_csv_file = motion_path.replace('.mot', '.csv') else: output_csv_file = args[0]['csv_output_file'] except: motion_path = args[0] # invoked as a function osim_path = args[1] try: output_csv_file = args[2] except: output_csv_file = motion_path.replace('.mot', '.csv') # Read model and motion files model = osim.Model(osim_path) motion_data = osim.TimeSeriesTable(motion_path) # Model: get model coordinates and bodies model_coordSet = model.getCoordinateSet() coordinates = [model_coordSet.get(i) for i in range(model_coordSet.getSize())] coordinateNames = [c.getName() for c in coordinates] model_bodySet = model.getBodySet() bodies = [model_bodySet.get(i) for i in range(model_bodySet.getSize())] bodyNames = [b.getName() for b in bodies] # Motion: read coordinates and convert to radians times = motion_data.getIndependentColumn() motion_data_np = motion_data.getMatrix().to_numpy() for i in range(len(coordinates)): if coordinates[i].getMotionType() == 1: # 1: rotation, 2: translation, 3: coupled motion_data_np[:,i] = motion_data_np[:,i] * np.pi/180 # if rotation, convert to radians # Animate model state = model.initSystem() loc_rot_frame_all = [] H_zup = np.array([[1,0,0,0], [0,0,-1,0], [0,1,0,0], [0,0,0,1]]) for n in range(motion_data.getNumRows()): # Set model struct in each time state for c, coord in enumerate(coordinateNames): model.getCoordinateSet().get(coord).setValue(state, motion_data_np[n,c]) # Use state of model to get body coordinates in ground loc_rot_frame = [] for b in bodies: H_swig = b.getTransformInGround(state) T = H_swig.T().to_numpy() R_swig = H_swig.R() R = np.array([[R_swig.get(0,0), R_swig.get(0,1), R_swig.get(0,2)], [R_swig.get(1,0), R_swig.get(1,1), R_swig.get(1,2)], [R_swig.get(2,0), R_swig.get(2,1), R_swig.get(2,2)]]) H = np.block([ [R,T.reshape(3,1)], [np.zeros(3), 1] ]) # y-up to z-up if direction=='zup': H = H_zup @ H # Convert matrix to loc and rot, and export to csv loc_x, loc_y, loc_z = H[0:3,3] R_mat = H[0:3,0:3] sy = np.sqrt(R_mat[1,0]**2 + R_mat[0,0]**2) # singularity when y angle is +/- pi/2 if sy>1e-6: rot_x = np.arctan2(R_mat[2,1], R_mat[2,2]) rot_y = np.arctan2(-R_mat[2,0], sy) rot_z = np.arctan2(R_mat[1,0], R_mat[0,0]) else: # to be verified rot_x = np.arctan2(-R_mat[1,2], R_mat[1,1]) rot_y = np.arctan2(-R[2,0], sy) rot_z = 0 loc_rot_frame.extend([loc_x, loc_y, loc_z, rot_x, rot_y, rot_z]) loc_rot_frame_all.append(loc_rot_frame) # Export to csv loc_rot_frame_all_np = np.array(loc_rot_frame_all) loc_rot_frame_all_np = np.insert(loc_rot_frame_all_np, 0, times, axis=1) # insert time column bodyHeader = 'times, ' + ''.join([f'{b}_x, {b}_y, {b}_z, {b}_rotx, {b}_roty, {b}_rotz, ' for b in bodyNames])[:-2] np.savetxt(os.path.splitext(output_csv_file)[0]+'.csv', loc_rot_frame_all_np, delimiter=',', header=bodyHeader) 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('-c', '--csv_output_file', required=False, help='csv output file') args = vars(parser.parse_args()) bodykin_from_mot_osim_func(args)