base_inv)
torso_kine_filled, _ = process_trial(stat_markers, filled_marker_pos,
compute_trajectory_continuous,
base_inv)
torso_kine_prev_filled, _ = process_trial(stat_markers,
prev_filled_marker_pos,
compute_trajectory, base_inv)
return TorsoTrajComparisonPlotter(trial.trial_name,
torso_kine_prev_filled,
torso_kine_smooth, torso_kine_filled,
torso_kine_sfs, trial.vicon_endpts)
# ready db
root_path = Path(params.output_dir)
db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject)
db['Plotter'] = db['Trial'].apply(
trial_plotter,
args=[
StaticTorsoSegment.TRACKING_MARKERS,
read_filling_directives(params.filling_directives), db.attrs['dt']
])
# create plots
init_graphing()
for subject_name, subject_df in db.groupby('Subject_Name'):
log.info('Outputting torso kinematics for subject %s', subject_name)
subject_pdf_file = root_path / (subject_name + '.pdf')
with PdfPages(subject_pdf_file) as subject_pdf:
for plotter in subject_df['Plotter']:
if plotter is not None:
from biplane_kine.database import create_db
from biplane_kine.database.biplane_vicon_db import ViconCsvSubject
from biplane_kine.misc.json_utils import Params
from biplane_kine.graphing.common_graph_utils import init_graphing
from ..parameters import read_smoothing_exceptions
from logging.config import fileConfig
# initialize
config_dir = Path(
mod_arg_parser('Batch smooth Vicon marker data using Kalman smoothing',
__package__, __file__))
params = Params.get_params(config_dir / 'parameters.json')
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
# ready db
root_path = Path(params.output_dir)
db = create_db(params.biplane_vicon_db_dir, ViconCsvSubject)
init_graphing()
all_exceptions = read_smoothing_exceptions(params.smoothing_exceptions)
# create plots
for subject_name, subject_df in db.groupby('Subject_Name'):
log.info('Smoothing subject %s', subject_name)
subject_dir = (root_path / subject_name)
subject_dir.mkdir(parents=True, exist_ok=True)
for t in subject_df['Trial']:
trial_plotter(t, db.attrs['dt'], subject_dir, all_exceptions)
params = Params.get_params(config_dir / 'parameters.json')
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
# ready db
class C3DSubjectEndptsPrePop(C3DSubjectEndpts):
"""Proxy for C3DSubjectEndpts where the labeled_base_dir and filled_base_dir are pre-populated."""
def __init__(self, subj_dir: Union[str, Path]):
super().__init__(subj_dir, labeled_base_dir=params.labeled_c3d_dir, filled_base_dir=params.filled_c3d_dir,
c3d_trial_cls=C3DTrialEndptsNonHom)
root_path = Path(params.output_dir)
db = create_db(params.biplane_vicon_db_dir, C3DSubjectEndptsPrePop)
# select trial
trial_row = db.loc[params.trial_name]
sel_trial = trial_row.Trial
log.info('Filtering trial %s marker %s', params.trial_name, params.marker_name)
# filter and plot
marker_exceptions = smoothing_exceptions_for_marker(params.smoothing_exceptions, params.trial_name,
params.marker_name)
init_graphing()
subject_dir = Path(params.output_dir) / trial_row.Subject_Name if \
bool(distutils.util.strtobool(params.print_to_file)) else None
try:
marker_plotter(sel_trial, params.marker_name, marker_exceptions, db.attrs['dt'], SmoothingOutputPlotter,
subject_dir)
from biplane_kine.graphing.common_graph_utils import init_graphing
from biplane_kine.misc.arg_parser import mod_arg_parser
import logging
from logging.config import fileConfig
# initialize
config_dir = Path(mod_arg_parser('Demonstrates the effect of smoothing for a specified trial/marker', __package__,
__file__))
params = Params.get_params(config_dir / 'parameters.json')
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
# ready db
db = create_db(params.accuracy_db_dir, BiplaneMarkerSubjectEndpts)
add_c3d_helper(db, params.labeled_c3d_dir, params.filled_c3d_dir)
# select trial
trial_row = db.loc[params.trial_name]
marker_exceptions = smoothing_exceptions_for_marker(params.smoothing_exceptions, params.trial_name,
params.marker_name)
# compute differences
try:
raw_smoothed_diff = marker_accuracy_diff(trial_row['Biplane_Marker_Trial'], trial_row['C3D_Trial'],
params.marker_name, marker_exceptions, db.attrs['dt'],
bool(distutils.util.strtobool(params.use_filled_portion)))
except InsufficientDataError as e:
log.error('Insufficient data for trial {} marker {}: {}'.format(params.trial_name, params.marker_name, e))
sys.exit(1)
__package__, __file__))
params = Params.get_params(config_dir / 'parameters.json')
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
# ready db
root_path = Path(params.output_dir)
anthro = anthro_db(params.biplane_vicon_db_dir)
def armpit_thickness(subject_name):
return anthro.loc[subject_name, 'Armpit_Thickness']
db = create_db(params.biplane_vicon_db_dir,
BiplaneViconSubjectV3D,
armpit_thickness=armpit_thickness)
# retrieve trial information
trial_row = db.loc[params.trial_name]
subject_id = trial_row['Subject_Name']
trial = trial_row['Trial']
tracking_markers = np.stack([
trial.filled[marker] for marker in StaticTorsoSegment.TRACKING_MARKERS
], 0)
torso_vicon = compute_trajectory(
trial.subject.torso.static_markers_intrinsic, tracking_markers)
torso_fluoro = change_cs(trial.subject.f_t_v, torso_vicon)
torso_truncated = torso_fluoro[trial.vicon_endpts[0]:trial.vicon_endpts[1]]
quat = quaternion.as_float_array(
quaternion.from_rotation_matrix(torso_truncated[:, :3, :3],