if age < 40 else '>45')
if params.excluded_trials:
db = db[~db['Trial_Name'].str.contains('|'.join(params.
excluded_trials))]
db['Trial'].apply(pre_fetch)
# relevant parameters
output_path = Path(params.output_dir)
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
db_elev = db.loc[db['Trial_Name'].str.contains('_CA_|_SA_|_FE_')].copy()
prepare_db(db_elev, params.torso_def, params.scap_lateral,
params.dtheta_fine, params.dtheta_coarse,
[params.min_elev, params.max_elev])
#%%
plt.rcParams['axes.prop_cycle'] = plt.cycler('color', plt.cm.tab20c.colors)
init_graphing(params.backend)
plt.close('all')
fig = plt.figure(figsize=(90 / 25.4, 190 / 25.4), dpi=params.dpi)
ax = fig.subplots(3, 1)
for i in range(3):
style_axes(ax[i], 'Humerothoracic Elevation (Deg)' if i == 2 else None,
'Axial Orientation (Deg)')
ax[i].xaxis.set_major_locator(ticker.MultipleLocator(base=20.0))
exc_trials = [
"O45_003_CA_t01", "O45_003_SA_t02", "O45_003_FE_t02",
"U35_010_FE_t01"
]
db = db[~db['Trial_Name'].str.contains('|'.join(exc_trials))]
db['Trial'].apply(pre_fetch)
# relevant parameters
output_path = Path(params.output_dir)
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
db_elev = db.loc[db['Trial_Name'].str.contains('_CA_|_SA_|_FE_')].copy()
prepare_db(db_elev, params.torso_def, 'GC', params.dtheta_fine,
params.dtheta_coarse, [params.min_elev, params.max_elev])
db_elev_equal = db_elev.loc[~db_elev['Trial_Name'].str.contains('U35_010'
)].copy()
#%%
if bool(distutils.util.strtobool(params.parametric)):
post_hoc_spm_test = spm1d.stats.ttest_paired
spm_test = spm1d.stats.ttest
infer_params = {}
else:
post_hoc_spm_test = spm1d.stats.nonparam.ttest_paired
spm_test = spm1d.stats.nonparam.ttest
infer_params = {'force_iterations': True}
alpha = 0.05
color_map = plt.get_cmap('Dark2')
import logging
config_dir = Path(
mod_arg_parser('Check U35_002_SA_t01 filling', __package__, __file__))
params = get_params(config_dir / 'parameters.json')
db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject)
db = db.loc[['U35_002_SA_t01']]
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
# compute min and max ht elevation for each subject
prepare_db(db,
params.torso_def,
params.scap_lateral,
params.dtheta_fine,
params.dtheta_coarse, [params.min_elev, params.max_elev],
should_clean=False)
(db['up_min_ht'], db['up_max_ht'], db['down_min_ht'],
db['down_max_ht']) = zip(
*(db['up_down_analysis'].apply(extract_up_down_min_max)))
plot_utils.init_graphing(params.backend)
plot_dirs = [['ht', 'ht_isb', 'HT'], ['gh', 'gh_isb', 'GH'],
['st', 'st_isb', 'ST']]
for plot_dir in plot_dirs:
traj = db.loc['U35_002_SA_t01', plot_dir[0]]
traj_euler = getattr(traj, 'euler')
fig = plt.figure(figsize=(14, 7), tight_layout=True)
ax = fig.subplots(2, 3)
for i in range(3):
if params.excluded_trials:
db = db[~db['Trial_Name'].str.contains('|'.join(params.
excluded_trials))]
db['Trial'].apply(pre_fetch)
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
# read Ludewig's data
ludewig_data = read_ludewig_data(params.ludewig_data)
ludewig_ht = ludewig_data['gh']['ca']['HT_Elev'].to_numpy()
# prepare database
db_elev = db.loc[db['Trial_Name'].str.contains('_CA_|_SA_|_FE_')].copy()
prepare_db(db_elev, params.torso_def, 'AC', params.dtheta_fine,
params.dtheta_coarse, [ludewig_ht[0], ludewig_ht[-1]])
#%%
# plot
color_map = plt.get_cmap('Dark2')
markers = ['^', 'o', 's', '*']
act_row = {'ca': 0, 'sa': 1, 'fe': 2}
ours_ht = db_elev.iloc[0]['traj_interp'].common_ht_range_coarse
init_graphing(params.backend)
plt.close('all')
# ############ EULER ANGLE COMPARISONS FOR GH ##################################
fig_std_hum = plt.figure(figsize=(190 / 25.4, 190 / 25.4))
axs_std_hum = fig_std_hum.subplots(3, 2)
db['age_group'] = db['Age'].map(lambda age: '<35' if age < 40 else '>45')
exc_trials = ["O45_003_CA_t01", "O45_003_SA_t02", "O45_003_FE_t02", "U35_010_FE_t01"]
db = db[~db['Trial_Name'].str.contains('|'.join(exc_trials))]
db['Trial'].apply(pre_fetch)
# relevant parameters
output_path = Path(params.output_dir)
# logging
fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False)
log = logging.getLogger(params.logger_name)
db_elev_gc = db.loc[db['Trial_Name'].str.contains('_CA_|_SA_|_FE_')].copy()
db_elev_ac = db.loc[db['Trial_Name'].str.contains('_CA_|_SA_|_FE_')].copy()
db_elev_aa = db.loc[db['Trial_Name'].str.contains('_CA_|_SA_|_FE_')].copy()
prepare_db(db_elev_gc, params.torso_def, 'GC', params.dtheta_fine, params.dtheta_coarse,
[params.min_elev, params.max_elev])
prepare_db(db_elev_ac, params.torso_def, 'AC', params.dtheta_fine, params.dtheta_coarse,
[params.min_elev, params.max_elev])
prepare_db(db_elev_aa, params.torso_def, 'PLA', params.dtheta_fine, params.dtheta_coarse,
[params.min_elev, params.max_elev])
#%%
alpha = 0.05
color_map = plt.get_cmap('Dark2')
markers = ['^', 'o', 's', 'd']
act_row = {'ca': 0, 'sa': 1, 'fe': 2}
x = db_elev_gc.iloc[0]['traj_interp'].common_ht_range_fine
init_graphing(params.backend)
plt.close('all')
