kraken/backend/signal_visualization.py

'''
Figures, ERSD map, tfr raw and cls
'''
import os
import argparse
import logging

import mne
import yaml
import numpy as np
import matplotlib.pyplot as plt

from dataloaders import neo
import bci_core.viz as bci_viz
from settings.config import settings


logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

config_info = settings.CONFIG_INFO


def parse_args():
    parser = argparse.ArgumentParser(
        description='Model validation'
    )
    parser.add_argument(
        '--subj',
        dest='subj',
        help='Subject name',
        default=None,
        type=str
    )
    return parser.parse_args()


if __name__ == '__main__':
    args = parse_args()
    subj_name = args.subj

    data_dir = os.path.join(settings.DATA_PATH, subj_name)
    
    with open(os.path.join(data_dir, 'val_info.yml'), 'r') as f:
        info = yaml.safe_load(f)
    sessions = info['sessions']
    
    ori_epoch_length = info.get('ori_epoch_length', 5.)

    # preprocess raw
    raw, event_id = neo.raw_loader(data_dir, sessions, 
                                ori_epoch_length=ori_epoch_length,
                                reref_method=config_info['reref'],
                                upsampled_epoch_length=None)
    
    fs = raw.info['sfreq']
    
    events, _ = mne.events_from_annotations(raw, event_id)

    # ersd map
    fig_erds = bci_viz.plot_ersd(raw.get_data(), events, fs, (0, 2.5), event_id, 0)

    # tfr plot
    fig_tfr = bci_viz.plot_cls_tfr(raw.get_data(), events, fs, np.arange(5, 200, 20), (-1, 4), {v: k for k, v in event_id.items()})

    # plot raw tfr
    fig_tfr_raw = bci_viz.plot_raw_tfr(raw.get_data(), fs, np.arange(5, 200, 10), n_cycles=20)

    # hg average line plot
    fig_hgs = {}
    for t in sessions.keys():
        fig_hg_1 = bci_viz.plot_hg_envelope(raw, events, event_id, fs, (55, 95), -1, 5, target_event=t)
        fig_hg_2 = bci_viz.plot_hg_envelope(raw, events, event_id, fs, (95, 155), -1, 5, t_smooth=0.6, target_event=t)
        fig_hgs[t] = (fig_hg_1, fig_hg_2)
    
    fig_erds.savefig(os.path.join(data_dir, 'erds.pdf'))
    fig_tfr.savefig(os.path.join(data_dir, 'tfr.pdf'))
    fig_tfr_raw.savefig(os.path.join(data_dir, 'tfr_raw.pdf'))

    plt.show()