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)
