utils.py

"""Helper functions and constants."""
from pathlib import Path
import warnings

import pandas as pd
import numpy as np

PROJECT_ROOT = Path.cwd()


def cliff_delta(X, Y):
    """Calculate the effect size using the Cliff's delta."""
    lx = len(X)
    ly = len(Y)
    mat = np.zeros((lx, ly))
    for i in range(0, lx):
        for j in range(0, ly):
            if X[i] > Y[j]:
                mat[i, j] = 1
            elif Y[j] > X[i]:
                mat[i, j] = -1

    return (np.sum(mat)) / (lx * ly)


def load_dataset(demographic_path, ids_path, freesurfer_path):
    """Load dataset."""
    demographic_data = load_demographic_data(demographic_path, ids_path)

    freesurfer_df = pd.read_csv(freesurfer_path)

    dataset_df = pd.merge(freesurfer_df, demographic_data, on='Image_ID')

    return dataset_df


def load_demographic_data(demographic_path, ids_path):
    """Load dataset using selected ids."""

    demographic_df = pd.read_csv(demographic_path, sep='\t')
    demographic_df = demographic_df.dropna()

    ids_df = pd.read_csv(ids_path, usecols=['Image_ID'])

    if 'Run_ID' in demographic_df.columns:
        demographic_df['uid'] = demographic_df['participant_id'] + '_' + demographic_df['Session_ID'] + '_run-' + \
                                demographic_df['Run_ID'].apply(str)

        ids_df['uid'] = ids_df['Image_ID'].str.split('_').str[0] + '_' + ids_df['Image_ID'].str.split('_').str[1]+ '_' + ids_df['Image_ID'].str.split('_').str[2]

        dataset_df = pd.merge(ids_df, demographic_df, on='uid')
        dataset_df = dataset_df.drop(columns=['uid'])

    elif 'Session_ID' in demographic_df.columns:
        demographic_df['uid'] = demographic_df['participant_id'] + '_' + demographic_df['Session_ID']

        ids_df['uid'] = ids_df['Image_ID'].str.split('_').str[0] + '_' + ids_df['Image_ID'].str.split('_').str[1]

        dataset_df = pd.merge(ids_df, demographic_df, on='uid')
        dataset_df = dataset_df.drop(columns=['uid'])

    else:
        ids_df['participant_id'] = ids_df['Image_ID'].str.split('_').str[0]

        dataset_df = pd.merge(ids_df, demographic_df, on='participant_id')

    return dataset_df


COLUMNS_NAME = ['Left-Lateral-Ventricle',
                'Left-Inf-Lat-Vent',
                'Left-Cerebellum-White-Matter',
                'Left-Cerebellum-Cortex',
                'Left-Thalamus-Proper',
                'Left-Caudate',
                'Left-Putamen',
                'Left-Pallidum',
                '3rd-Ventricle',
                '4th-Ventricle',
                'Brain-Stem',
                'Left-Hippocampus',
                'Left-Amygdala',
                'CSF',
                'Left-Accumbens-area',
                'Left-VentralDC',
                'Right-Lateral-Ventricle',
                'Right-Inf-Lat-Vent',
                'Right-Cerebellum-White-Matter',
                'Right-Cerebellum-Cortex',
                'Right-Thalamus-Proper',
                'Right-Caudate',
                'Right-Putamen',
                'Right-Pallidum',
                'Right-Hippocampus',
                'Right-Amygdala',
                'Right-Accumbens-area',
                'Right-VentralDC',
                'CC_Posterior',
                'CC_Mid_Posterior',
                'CC_Central',
                'CC_Mid_Anterior',
                'CC_Anterior',
                'lh_bankssts_volume',
                'lh_caudalanteriorcingulate_volume',
                'lh_caudalmiddlefrontal_volume',
                'lh_cuneus_volume',
                'lh_entorhinal_volume',
                'lh_fusiform_volume',
                'lh_inferiorparietal_volume',
                'lh_inferiortemporal_volume',
                'lh_isthmuscingulate_volume',
                'lh_lateraloccipital_volume',
                'lh_lateralorbitofrontal_volume',
                'lh_lingual_volume',
                'lh_medialorbitofrontal_volume',
                'lh_middletemporal_volume',
                'lh_parahippocampal_volume',
                'lh_paracentral_volume',
                'lh_parsopercularis_volume',
                'lh_parsorbitalis_volume',
                'lh_parstriangularis_volume',
                'lh_pericalcarine_volume',
                'lh_postcentral_volume',
                'lh_posteriorcingulate_volume',
                'lh_precentral_volume',
                'lh_precuneus_volume',
                'lh_rostralanteriorcingulate_volume',
                'lh_rostralmiddlefrontal_volume',
                'lh_superiorfrontal_volume',
                'lh_superiorparietal_volume',
                'lh_superiortemporal_volume',
                'lh_supramarginal_volume',
                'lh_frontalpole_volume',
                'lh_temporalpole_volume',
                'lh_transversetemporal_volume',
                'lh_insula_volume',
                'rh_bankssts_volume',
                'rh_caudalanteriorcingulate_volume',
                'rh_caudalmiddlefrontal_volume',
                'rh_cuneus_volume',
                'rh_entorhinal_volume',
                'rh_fusiform_volume',
                'rh_inferiorparietal_volume',
                'rh_inferiortemporal_volume',
                'rh_isthmuscingulate_volume',
                'rh_lateraloccipital_volume',
                'rh_lateralorbitofrontal_volume',
                'rh_lingual_volume',
                'rh_medialorbitofrontal_volume',
                'rh_middletemporal_volume',
                'rh_parahippocampal_volume',
                'rh_paracentral_volume',
                'rh_parsopercularis_volume',
                'rh_parsorbitalis_volume',
                'rh_parstriangularis_volume',
                'rh_pericalcarine_volume',
                'rh_postcentral_volume',
                'rh_posteriorcingulate_volume',
                'rh_precentral_volume',
                'rh_precuneus_volume',
                'rh_rostralanteriorcingulate_volume',
                'rh_rostralmiddlefrontal_volume',
                'rh_superiorfrontal_volume',
                'rh_superiorparietal_volume',
                'rh_superiortemporal_volume',
                'rh_supramarginal_volume',
                'rh_frontalpole_volume',
                'rh_temporalpole_volume',
                'rh_transversetemporal_volume',
                'rh_insula_volume']