missing_marker_labels = [
"R.ASIS", "R.Thigh.Rear", "R.Toe.Tip", "R.Shank.Upper", "L.Shank.Upper",
"L.Thigh.Rear", "L.Toe.Tip"
]
subject_dir = os.path.abspath('../')
results_dir = os.path.join(subject_dir, 'real_time/marker_reconstruction')
original_markers_file = os.path.join(subject_dir, 'experimental_data/task.trc')
reconstructed_markers_file = os.path.join(results_dir,
'reconstructed_markers.sto')
if not (os.path.isfile(original_markers_file)
and os.path.isfile(reconstructed_markers_file)):
raise RuntimeError('Required files do not exist.')
original_markers = read_from_storage(original_markers_file)
reconstructed_markers = read_from_storage(reconstructed_markers_file)
# %%
if gait_cycle:
t0 = 0.6 # right heel strike
tf = 1.83 # next right heel strike
original_markers = to_gait_cycle(original_markers, t0, tf)
reconstructed_markers = to_gait_cycle(reconstructed_markers, t0, tf)
occlusion_start_perc = 100.0 / (tf - t0) * (occlusion_start_time - t0)
occlusion_stop_perc = 100.0 / (tf - t0) * (occlusion_start_time +
occlusion_duration - t0)
# %%
# %%
# data
gait_cycle = True
subject_dir = os.path.abspath('../')
output_dir = os.path.join(subject_dir, 'real_time/inverse_dynamics/')
tau_reference_file = os.path.join(subject_dir,
'inverse_dynamics/task_InverseDynamics.sto')
tau_rt_file = os.path.join(output_dir, 'tau.sto')
# %%
# read data
tau_reference = read_from_storage(tau_reference_file)
tau_rt = read_from_storage(tau_rt_file)
if gait_cycle:
t0 = 0.6 # right heel strike
tf = 1.83 # next right heel strike
tau_reference = to_gait_cycle(tau_reference, t0, tf)
tau_rt = to_gait_cycle(tau_rt, t0, tf)
plot_sto_file(tau_rt_file, tau_rt_file + '.pdf', 3)
# %%
# compare
d_tau_total = []
with PdfPages(output_dir + 'inverse_dynamics_comparison.pdf') as pdf:
ensemble_right = []
ensemble_left = []
for directory in subject_dirs:
# file path
ik_file_path = os.path.join(working_dir,
directory,
'inverse_kinematics/'
'task_InverseKinematics.mot')
c3d_file_path = os.path.join(working_dir,
directory,
'experimental_data/'
'task.c3d')
# load kinematics
kinematics_df = read_from_storage(ik_file_path, 0.01, True)
# extract gait cycle
right_intervals, left_intervals = extract_gait_cycle_intervals(c3d_file_path)
# partition trial on interval, normalize and collect into list
for interval in right_intervals:
df = kinematics_df[(kinematics_df.time >= interval[0]) &
(kinematics_df.time <= interval[1])]
df_norm = normalize_interpolate_dataframe(df)
ensemble_right.append(df_norm)
for interval in left_intervals:
df = kinematics_df[(kinematics_df.time >= interval[0]) &
(kinematics_df.time <= interval[1])]
df_norm = normalize_interpolate_dataframe(df)
subject_dir = os.path.abspath('../')
output_dir = os.path.join(subject_dir, 'real_time/muscle_optimization/')
fm_reference_file = os.path.join(
subject_dir, 'static_optimization/task_StaticOptimization_force.sto')
fm_rt_file = os.path.join(output_dir, 'fm.sto')
am_rt_file = os.path.join(output_dir, 'am.sto')
tauRes_rt_file = os.path.join(output_dir, 'tauRes.sto')
plot_sto_file(am_rt_file, am_rt_file + '.pdf', 3)
plot_sto_file(tauRes_rt_file, tauRes_rt_file + '.pdf', 3)
# %%
# read data
fm_reference = read_from_storage(fm_reference_file)
fm_rt = read_from_storage(fm_rt_file)
if gait_cycle:
t0 = 0.6 # right heel strike
tf = 1.83 # next right heel strike
fm_reference = to_gait_cycle(fm_reference, t0, tf)
fm_rt = to_gait_cycle(fm_rt, t0, tf)
plot_sto_file(fm_rt_file, fm_rt_file + '.pdf', 3)
# %%
# compare
d_fm_total = []
with PdfPages(output_dir + 'muscle_optimization_comparison.pdf') as pdf:
# data
gait_cycle = True
subject_dir = os.path.abspath('../')
output_dir = os.path.join(subject_dir, 'real_time/joint_reaction_analysis/')
jr_reference_file = os.path.join(
subject_dir,
'joint_reaction_analysis/task_JointReaction_ReactionLoads.sto')
jr_rt_file = os.path.join(output_dir, 'jr.sto')
# %%
# read data
jr_reference = read_from_storage(jr_reference_file)
jr_rt = read_from_storage(jr_rt_file)
# make very small number zero before plotting
jr_reference[jr_reference.abs() < 1e-9] = 0
jr_rt[jr_reference.abs() < 1e-9] = 0
if gait_cycle:
t0 = 0.6 # right heel strike
tf = 1.83 # next right heel strike
jr_reference = to_gait_cycle(jr_reference, t0, tf)
jr_rt = to_gait_cycle(jr_rt, t0, tf)
plot_sto_file(jr_rt_file, jr_rt_file + '.pdf', 3)
# %%
# compare
subject_dir = os.path.abspath('../')
results_dir = os.path.join(subject_dir,
'real_time/grfm_prediction/force_based/')
experimental_dir = os.path.join(subject_dir, 'experimental_data/')
right_wrench_rt_file = os.path.join(results_dir, 'wrench_right.sto')
left_wrench_rt_file = os.path.join(results_dir, 'wrench_left.sto')
experimental_grfm_file = os.path.join(experimental_dir, 'task_grf.mot')
if not (os.path.isfile(right_wrench_rt_file)
and os.path.isfile(left_wrench_rt_file)
and os.path.isfile(experimental_grfm_file)):
raise RuntimeError('required files do not exist')
# read data
right_wrench = read_from_storage(right_wrench_rt_file).round(10)
left_wrench = read_from_storage(left_wrench_rt_file).round(10)
experimental_grfm = read_from_storage(experimental_grfm_file, True)
# %%
gait_cycle = True
simulation_loops = 2
n = 5 # remove last n rows in experimental_grfm_file
t0 = 0.6
tf = 1.83
r_grf_prefix = 'ground_'
l_grf_prefix = '1_ground_'
# %%
q_filtered_file = os.path.join(output_dir, folder, 'q_filtered.sto')
q_dot_filtered_file = os.path.join(output_dir, folder, 'qDot_filtered.sto')
q_ddot_filtered_file = os.path.join(output_dir, folder, 'qDDot_filtered.sto')
q_filtered_sp_file = os.path.join(output_dir, 'spatial_filter/q_filtered.sto')
q_dot_filtered_sp_file = os.path.join(output_dir,
'spatial_filter/qDot_filtered.sto')
q_ddot_filtered_sp_file = os.path.join(output_dir,
'spatial_filter/qDDot_filtered.sto')
# %%
# read data
gait_cycle = True
q_reference = read_from_storage(q_reference_file, True)
q_dot_reference = read_from_storage(q_dot_reference_file, True)
q_ddot_reference = read_from_storage(q_ddot_reference_file, True)
q_filtered = read_from_storage(q_filtered_file)
q_dot_filtered = read_from_storage(q_dot_filtered_file)
q_ddot_filtered = read_from_storage(q_ddot_filtered_file)
q_filtered_sp = read_from_storage(q_filtered_sp_file)
q_dot_filtered_sp = read_from_storage(q_dot_filtered_sp_file)
q_ddot_filtered_sp = read_from_storage(q_ddot_filtered_sp_file)
if gait_cycle:
t0 = 0.6 # right heel strike
tf = 1.83 # next right heel strike
q_reference = to_gait_cycle(q_reference, t0, tf)
absFilePath = os.path.abspath(__file__)
fileDir = os.path.dirname(absFilePath)
parentDir = os.path.dirname(fileDir)
# model file
model_file = os.path.abspath(
os.path.join(parentDir, 'scale/model_scaled.osim'))
model = opensim.Model(model_file)
state = model.initSystem()
coordinate_set = model.updCoordinateSet()
pelvis = model.updBodySet().get('pelvis')
# model coordinates for this specific motion
inverse_kinematics_file = os.path.abspath(
os.path.join(parentDir, 'inverse_kinematics/task_InverseKinematics.mot'))
ik_data = read_from_storage(model_file, inverse_kinematics_file)
# this file contains the results from inverse dynamics ignoring the
# ground reaction forces in the calculation.
inverse_dynamics_file = os.path.abspath(
os.path.join(parentDir, 'inverse_dynamics/task_InverseDynamics.sto'))
id_data = read_from_storage(model_file, inverse_dynamics_file)
# this file contains the results from inverse dynamics ignoring the
# ground reaction forces in the calculation.
markers_file = os.path.abspath(
os.path.join(parentDir, 'inverse_kinematics/ik_model_marker_locations.sto'))
ik_marker = read_from_storage(model_file, markers_file)
assert(ik_data.shape == id_data.shape)
assert(ik_data.shape[0] == ik_marker.shape[0])
output_dir = os.path.join(subject_dir, 'real_time/filtering/bw_filter/')
q_reference_file = os.path.join(
subject_dir, 'residual_reduction_algorithm/task_Kinematics_q.sto')
q_filtered_files = [f for f in os.listdir(output_dir) if f.endswith('.sto')]
for q_filtered_file in q_filtered_files:
q_filtered_file = os.path.join(output_dir, q_filtered_file)
# %%
# read data
gait_cycle = True
q_reference = read_from_storage(q_reference_file, True)
q_filtered = read_from_storage(q_filtered_file)
# %% reference signal filter parameters
# get file extension with filter parameters
s = os.path.basename(os.path.splitext(q_filtered_file)[0]).replace(
'q_filtered_', '')
fs = 100 # signal freq
fc = int(s[s.find('F') + 1:s.rfind('O')]) # target cutoff freq
filter_order = int(s[s.find('O') + 1:s.rfind('T')]) # filter order
# filter type
filter_type_ext = s[s.find('T') + 1:s.rfind('')]
output_dir = os.path.join(subject_dir, 'pipeline/') q_reference_file = os.path.join(subject_dir, 'inverse_dynamics/q_filtered.sto') tau_reference_file = os.path.join(subject_dir, 'inverse_dynamics/tau.sto') fm_reference_file = os.path.join(subject_dir, 'muscle_optimization/fm.sto') jr_reference_file = os.path.join(subject_dir, 'joint_reaction_analysis/jr.sto') q_pipeline_file = os.path.join(output_dir, 'q.sto') tau_pipeline_file = os.path.join(output_dir, 'tau.sto') fm_pipeline_file = os.path.join(output_dir, 'fm.sto') jr_pipeline_file = os.path.join(output_dir, 'jr.sto') # %% # read data q_reference = read_from_storage(q_reference_file) q_pipeline = read_from_storage(q_pipeline_file) tau_reference = read_from_storage(tau_reference_file) tau_pipeline = read_from_storage(tau_pipeline_file) fm_reference = read_from_storage(fm_reference_file) fm_pipeline = read_from_storage(fm_pipeline_file) jr_reference = read_from_storage(jr_reference_file) jr_pipeline = read_from_storage(jr_pipeline_file) # make very small number zero before plotting jr_reference[jr_reference.abs() < 1e-9] = 0 jr_pipeline[jr_pipeline.abs() < 1e-9] = 0 if gait_cycle:
#
# author: Filip Konstantinos <*****@*****.**>
# %%
import os
import opensim as osim
from utils import read_from_storage
#%%
subject_dir = os.path.abspath('../')
output_dir = os.path.join(subject_dir, 'experimental_data')
trc_file = os.path.join(subject_dir, 'experimental_data/task.trc')
#%%
# load and resample markers at 0.01
df = read_from_storage(trc_file)
# create timeseries table
table = osim.TimeSeriesTable()
table.setColumnLabels(df.columns[1:])
table.addTableMetaDataString('DataRate', '100')
table.addTableMetaDataString('Units', 'mm')
# append data to table
for i in range(df.shape[0]):
table.appendRow(df.time.values[i], osim.RowVector(df.iloc[i, 1:].values))
# write table to file
osim.TRCFileAdapter.write(table.packVec3(),
os.path.join(output_dir, 'task_resampled.trc'))
# %%
# data
gait_cycle = True
subject_dir = os.path.abspath('../')
output_dir = os.path.join(subject_dir, 'real_time/inverse_kinematics/')
q_reference_file = os.path.join(subject_dir,
'inverse_kinematics/task_InverseKinematics.mot')
q_rt_file = os.path.join(output_dir, 'q.sto')
# %%
# read data
q_reference = read_from_storage(q_reference_file)
q_rt = read_from_storage(q_rt_file)
if gait_cycle:
t0 = 0.6 # right heel strike
tf = 1.83 # next right heel strike
q_reference = to_gait_cycle(q_reference, t0, tf)
q_rt = to_gait_cycle(q_rt, t0, tf)
plot_sto_file(q_rt_file, q_rt_file + '.pdf', 3)
# %%
# compare
d_q_total = []
with PdfPages(output_dir + 'inverse_kinematics_comparison.pdf') as pdf: