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')