from pathlib import Path import numpy as np import matplotlib.pyplot as plt from st_generated_axial_rot.common.plot_utils import init_graphing, make_interactive, mean_sd_plot, style_axes from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import ( prepare_db, extract_sub_rot_norm, st_induced_axial_rot_fha, add_st_induced) from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Plot each component of ST induced HT axial rotation for each plane of elevation', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import matplotlib.pyplot as plt import spm1d from st_generated_axial_rot.common.plot_utils import ( init_graphing, make_interactive, mean_sd_plot, style_axes, sig_filter, extract_sig) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm, sub_rot_at_max_elev from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.analysis_er_utils import ready_er_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser('ST contributions to HT axial rotation by age group', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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
import matplotlib.pyplot as plt from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.plot_utils import (init_graphing, make_interactive, style_axes) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm, sub_rot_at_max_elev from st_generated_axial_rot.common.analysis_er_utils import ready_er_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Correlation between ST-generated and GH Axial Rotation', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
from pathlib import Path import numpy as np import matplotlib.pyplot as plt from matplotlib.backends.backend_pdf import PdfPages from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.analysis_er_utils import ready_er_db import matplotlib.ticker as plticker import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( "Create an overview of PoE, elevation, and axial rotation contributions for " "external rotation trials", __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import matplotlib.pyplot as plt import matplotlib.patches as patches import spm1d from st_generated_axial_rot.common.plot_utils import (init_graphing, make_interactive, mean_sd_plot, style_axes, update_yticks, update_ylabel, output_spm_p, retrieve_bp_stats, sig_filter, extract_sig) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import (prepare_db, extract_sub_rot_norm, sub_rot_at_max_elev) from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.analysis_er_utils import ready_er_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path(mod_arg_parser('Plot HT, ST, and GH contribution to axial rotation and compare ST against GH ' 'contributions', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import spm1d from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm, sub_rot_at_max_elev from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.plot_utils import ( style_axes, mean_sd_plot, make_interactive, sig_filter, extract_sig, output_spm_p) import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare contributions of the ST and GH joint to HT elevation using Euler angles ' 'and contributions', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import numpy as np import matplotlib.pyplot as plt import spm1d from st_generated_axial_rot.common.plot_utils import ( init_graphing, make_interactive, mean_sd_plot, spm_plot_alpha, HandlerTupleVertical, extract_sig, style_axes) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare HT, ST, and GH true axial rotation and measure against zero', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import numpy as np import matplotlib.pyplot as plt from matplotlib.backends.backend_pdf import PdfPages import matplotlib.ticker as plticker from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare contributions of the ST and GH joint to axial rotation on a per-trial ' 'basis', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import distutils.util from pathlib import Path import numpy as np from scipy.stats import linregress import matplotlib.pyplot as plt from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.plot_utils import (init_graphing, make_interactive, style_axes) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, sub_rot_at_max_elev from st_generated_axial_rot.common.analysis_er_utils import ready_er_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path(mod_arg_parser('Correlation of ST-generated Axial Rotation between Activities', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import matplotlib.pyplot as plt import matplotlib.ticker as plticker from st_generated_axial_rot.common.plot_utils import (init_graphing, make_interactive, mean_sd_plot, style_axes) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Contributions of ST and GH joints to PoE, elevation, and axial rotation by ' 'plane of elevation', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import distutils.util from pathlib import Path import numpy as np import matplotlib.pyplot as plt from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.plot_utils import init_graphing, make_interactive, mean_sd_plot, style_axes from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm, sub_rot_at_max_elev from st_generated_axial_rot.common.analysis_er_utils import ready_er_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser('ST and GH Contributions to HT PoE', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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
print('Use -m option to run this library module as a script.') import numpy as np import matplotlib.pyplot as plt from pathlib import Path from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject from st_generated_axial_rot.common.analysis_utils import prepare_db from st_generated_axial_rot.analysis.up_down_identify import extract_up_down_min_max from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from logging.config import fileConfig 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)
if __name__ == '__main__': if __package__ is None: print('Use -m option to run this library module as a script.') import os import distutils.util from pathlib import Path from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, add_st_induced, st_induced_axial_rot_fha from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from logging.config import fileConfig config_dir = Path( mod_arg_parser('Overview of elevations trials', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
from pathlib import Path import numpy as np import matplotlib.pyplot as plt import matplotlib.ticker as plticker from biokinepy.vec_ops import extended_dot from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib, compute_axial_axis from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.plot_utils import make_interactive import logging from logging.config import fileConfig config_dir = Path(mod_arg_parser('Compare ST and GH angular velocity alignment against HT longitudinal axis', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import numpy as np import matplotlib.pyplot as plt from matplotlib.backends.backend_pdf import PdfPages import matplotlib.ticker as plticker from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare contributions of the ST and GH joint to HT motion on a per-trial basis', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import distutils.util from pathlib import Path import numpy as np import matplotlib.pyplot as plt from matplotlib.backends.backend_pdf import PdfPages from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.analysis_er_utils import ready_er_db, plot_directives import matplotlib.ticker as plticker import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser("Create an overview of external rotation trials", __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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
import matplotlib.pyplot as plt import spm1d import matplotlib.ticker as plticker from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.plot_utils import style_axes, mean_sd_plot, make_interactive, sig_filter import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare differences by age group for contributions of the ST and GH joint to HT ' 'elevation using Euler angles and contributions', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import matplotlib.pyplot as plt import matplotlib.ticker as plticker from st_generated_axial_rot.common.plot_utils import (init_graphing, make_interactive, mean_sd_plot, style_axes) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.analysis_er_utils import ready_er_db import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Contributions of ST and GH joints to PoE, elevation, and axial rotation for ' 'external rotation trials by axis', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import matplotlib.ticker as plticker from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.analysis_er_utils import ready_er_db from st_generated_axial_rot.common.plot_utils import (mean_sd_plot, make_interactive, style_axes, sig_filter) import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( "Compare HT, ST, GH axial rotation for external rotation trials by age", __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.plot_utils import (init_graphing, make_interactive, mean_sd_plot, style_axes) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import ( prepare_db, extract_sub_rot, extract_sub_rot_norm, sub_rot_at_max_elev) from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Correlation of ST-generated Axial Rotation with Euler/Cardan angles', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import matplotlib.pyplot as plt import spm1d from st_generated_axial_rot.common.plot_utils import ( init_graphing, make_interactive, mean_sd_plot, spm_plot_alpha, HandlerTupleVertical, extract_sig, style_axes) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import ( prepare_db, extract_sub_rot_norm, st_induced_axial_rot_fha, add_st_induced) from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser('ST induced HT axial rotation comparison against zero', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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
import matplotlib.ticker as plticker from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.plot_utils import (init_graphing, make_interactive, mean_sd_plot, style_axes) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm, sub_rot_at_max_elev from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare contributions of the ST and GH joints towards Elevation, Axial Rotation, ' 'and PoE for elevation trials', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import os import distutils.util from pathlib import Path import numpy as np import matplotlib.pyplot as plt from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common.plot_utils import init_graphing, make_interactive, mean_sd_plot, style_axes from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm, sub_rot_at_max_elev from st_generated_axial_rot.common.analysis_er_utils import ready_er_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path(mod_arg_parser('ST and GH Contributions to HT Elevation', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import numpy as np import spm1d from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.plot_utils import style_axes, mean_sd_plot, make_interactive, sig_filter from st_generated_axial_rot.analysis.new_vs_old_st_gh_shr import shr_compute import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare SHR between age group using old SHR (GH Elev/ST UR) and new SHR based on ' 'contribution of GH and ST joint to HT elevation', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
from pathlib import Path import numpy as np import matplotlib.pyplot as plt from scipy.integrate import cumtrapz from biokinepy.vec_ops import extended_dot from st_generated_axial_rot.common.plot_utils import init_graphing from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject from st_generated_axial_rot.common.analysis_utils import prepare_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser('Verify intuition about ST axial rotation', __package__, __file__)) params = get_params(config_dir / 'parameters.json') # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' if age < 40 else '>45') if params.excluded_trials: db = db[~db['Trial_Name'].str.contains('|'.join(params.excluded_trials) )] db = db.loc[[params.trial_name]] # logging fileConfig(config_dir / 'logging.ini', disable_existing_loggers=False) log = logging.getLogger(params.logger_name)
from pathlib import Path import numpy as np from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db from st_generated_axial_rot.common.analysis_er_utils import ready_er_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.analysis_utils import ( st_induced_axial_rot_ang_vel, st_induced_axial_rot_fha, st_induced_axial_rot_swing_twist) import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare different methods of computing ST induced HT axial rotation', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
from pathlib import Path import matplotlib.pyplot as plt import spm1d from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.plot_utils import style_axes, mean_sd_plot, make_interactive, sig_filter import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare old SHR (GH Elev/ST UR) and new SHR based on contribution of GH and ST ' 'joint to HT elevation', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import distutils.util from pathlib import Path import numpy as np import matplotlib.pyplot as plt import matplotlib.ticker as plticker from st_generated_axial_rot.common.analysis_utils_contrib import add_st_gh_contrib from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser from st_generated_axial_rot.common.plot_utils import make_interactive import logging from logging.config import fileConfig config_dir = Path(mod_arg_parser('Compare contributions of the ST and GH joints towards Elevation, Axial Rotation, ' 'and PoE for elevation trials by subject', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
import spm1d from st_generated_axial_rot.common.plot_utils import (init_graphing, make_interactive, mean_sd_plot, style_axes, sig_filter) from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, extract_sub_rot_norm from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compare HT, ST, GH axial rotation for elevation trials by gender', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)
from pathlib import Path import numpy as np import matplotlib.pyplot as plt from matplotlib.backends.backend_pdf import PdfPages import matplotlib.ticker as plticker from st_generated_axial_rot.common import plot_utils from st_generated_axial_rot.common.database import create_db, BiplaneViconSubject, pre_fetch from st_generated_axial_rot.common.analysis_utils import prepare_db, quat_project from st_generated_axial_rot.common.json_utils import get_params from st_generated_axial_rot.common.arg_parser import mod_arg_parser import logging from logging.config import fileConfig config_dir = Path( mod_arg_parser( 'Compute remaining HT rotation after elevation has been removed ' 'for individual trials', __package__, __file__)) params = get_params(config_dir / 'parameters.json') if not bool(distutils.util.strtobool(os.getenv('VARS_RETAINED', 'False'))): # ready db db = create_db(params.biplane_vicon_db_dir, BiplaneViconSubject, include_anthro=True) db['age_group'] = db['Age'].map(lambda age: '<35' 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)