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:
for i in range(1, tau_reference.shape[1]):
# find index
key = tau_reference.columns[i].replace('_moment', '').replace('_force', '')
j = tau_rt.columns.get_loc(key)
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)
# %%
d_q_total = []
with PdfPages(os.path.join(results_dir,
'marker_reconstruction_comparison.pdf')) as pdf:
reconstructed_markers.columns = [
c.replace('_1', '_x') for c in reconstructed_markers.columns
]
reconstructed_markers.columns = [
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:
for i in range(1, fm_rt.shape[1]):
# find index
key = fm_rt.columns[i]
j = fm_reference.columns.get_loc(key)
'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
d_jr_total = []
with PdfPages(output_dir + 'joint_reaction_comparison_fm.pdf') as pdf:
for i in range(1, jr_rt.shape[1]):
# find index
key = jr_rt.columns[i]
j = jr_reference.columns.get_loc(key)
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)
q_dot_reference = to_gait_cycle(q_dot_reference, t0, tf)
q_ddot_reference = to_gait_cycle(q_ddot_reference, t0, tf)
q_filtered = to_gait_cycle(q_filtered, t0, tf)
q_dot_filtered = to_gait_cycle(q_dot_filtered, t0, tf)
q_ddot_filtered = to_gait_cycle(q_ddot_filtered, t0, tf)
q_filtered_sp = to_gait_cycle(q_filtered_sp, t0, tf)
q_dot_filtered_sp = to_gait_cycle(q_dot_filtered_sp, t0, tf)
q_ddot_filtered_sp = to_gait_cycle(q_ddot_filtered_sp, t0, tf)
plot_sto_file(q_reference_file, q_reference_file + '.pdf', 2)
plot_sto_file(q_filtered_file, q_filtered_file + '.pdf', 2)
# %%
# compare
# %%
# convert zeros values to NaN for the CoP
right_wrench.p_x = right_wrench.p_x.replace(0.0, float('nan'))
right_wrench.p_y = right_wrench.p_y.replace(0.0, float('nan'))
right_wrench.p_z = right_wrench.p_z.replace(0.0, float('nan'))
left_wrench.p_x = left_wrench.p_x.replace(0.0, float('nan'))
left_wrench.p_y = left_wrench.p_y.replace(0.0, float('nan'))
left_wrench.p_z = left_wrench.p_z.replace(0.0, float('nan'))
# %%
if gait_cycle:
t0 = t0 + total_time # right heel strike
tf = tf + total_time # next right heel strike
experimental_grfm = to_gait_cycle(experimental_grfm, t0, tf)
right_wrench = to_gait_cycle(right_wrench, t0, tf)
left_wrench = to_gait_cycle(left_wrench, t0, tf)
# %%
def plot_helper(gt_data_frame, est_data_frame, id_gt, id_est, title, y_label):
''' Helper function for plotting forces/moments/cop.
'''
for i in range(3):
a = np.array(est_data_frame.iloc[:, i + id_est]) # estimate
b = np.array(gt_data_frame.iloc[:, i + id_gt]) # ground-truth
# compute error
# filter type
filter_type_ext = s[s.find('T') + 1:s.rfind('')]
if (filter_type_ext == 'lp'):
filt_type = 'low'
elif (filter_type_ext == 'hp'):
filt_type = 'high'
else:
raise RuntimeError('Wrong filter type.')
# %%
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_filtered = to_gait_cycle(q_filtered, t0, tf)
# %%
# compare
d_q_total = []
with PdfPages(output_dir + 'filter_comparison_' + s + '.pdf') as pdf:
for i in range(1, q_reference.shape[1]):
key = q_reference.columns[i]
j = q_filtered.columns.get_loc(key)
if key[-2::] in ['tx', 'ty', 'tz']:
scale = 1
else:
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:
t0 = 0.6 # right heel strike
tf = 1.83 # next right heel strike
q_reference = to_gait_cycle(q_reference, t0, tf)
q_pipeline = to_gait_cycle(q_pipeline, t0, tf)
tau_reference = to_gait_cycle(tau_reference, t0, tf)
tau_pipeline = to_gait_cycle(tau_pipeline, t0, tf)
fm_reference = to_gait_cycle(fm_reference, t0, tf)
fm_pipeline = to_gait_cycle(fm_pipeline, t0, tf)
jr_reference = to_gait_cycle(jr_reference, t0, tf)
jr_pipeline = to_gait_cycle(jr_pipeline, t0, tf)
# %%
# compare
d_q_total = []
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:
for i in range(1, q_reference.shape[1]):
# find index
j = q_rt.columns.get_loc(q_reference.columns[i])
# deg to rad for rotational degrees of freedom