itc_condition_side_analysis.py

import numpy as np
# import glob
import mne
import pandas as pd

from my_settings import (epochs_folder, tf_folder, result_dir)

method = "dSPM"

subjects_select = [
    "0005", "0006", "0007", "0008", "0009", "0010", "0011", "0015", "0016",
    "0017", "0020", "0021", "0022", "0024", "0025"
]

epochs = mne.read_epochs(epochs_folder + "0005_target-epo.fif", preload=False)
times = epochs.times

conditions = ["ctl", "ent"]
sides = ["right", "left"]
ROIS = ["rh", "lh"]

from_time = np.abs(times + 0.08).argmin()
to_time = np.abs(times - 0.02).argmin()

df = pd.DataFrame()

for subject in subjects_select:
    for condition in conditions:
        for side in sides:
            for roi in ROIS:
                dat = np.load(tf_folder +
                              "%s_itc_%s_%s_%s_LOBE.OCCIPITAL-%s_target.npy" %
                              (subject, condition, side, method, roi))

                value = dat[:, :, from_time:to_time].mean(axis=0).mean(
                    axis=0).mean(axis=0)

                row = pd.DataFrame([{
                    "subject": subject,
                    "condition": condition,
                    "side": side,
                    "roi": roi,
                    "itc": value
                }])

                df = df.append(row, ignore_index=True)

df.to_csv(
    result_dir + "itc_condition_side_mean_%s_lobes.csv" % method, index=False)