<filename>deepthought3/.experiments/bcmi2015/preprocessing.py<gh_stars>0
__author__ = "sstober"

import logging

log = logging.getLogger(__name__)

from deepthought3.datasets.openmiir.preprocessing.events import generate_beat_events
from deepthought3.datasets.openmiir.metadata import get_stimuli_version
import deepthought3.datasets.openmiir.preprocessing as preprocessing

# alias
preload = preprocessing.preload


def load_and_preprocess_raw(
    subject,
    # default preprocessing params for BCMI 2015 experiments
    onsets="audio",
    interpolate_bad_channels=True,
    reference_mastoids=True,
    l_freq=0.5,
    h_freq=30,
    sfreq=64,
    ica_cleaning=True,
    verbose=None,
):

    raw, trial_events = preprocessing.load_and_preprocess_raw(
        subject,
        onsets=onsets,
        interpolate_bad_channels=interpolate_bad_channels,
        reference_mastoids=reference_mastoids,
        l_freq=l_freq,
        h_freq=h_freq,
        sfreq=sfreq,
        ica_cleaning=ica_cleaning,
        verbose=verbose,
    )

    stimuli_version = get_stimuli_version(subject)

    # generate beat events - we need them to find the downbeat times
    beat_events = generate_beat_events(
        trial_events,
        include_cue_beats=False,  # IMPORTANT!!!
        #                                    beat_event_id_generator=simple_beat_event_id_generator, # -> event_id=10000
        exclude_stimulus_ids=[],
        exclude_condition_ids=[],
        verbose=verbose,
        version=stimuli_version,
    )

    if verbose:
        log.debug("beat events: {}".format(beat_events.shape))

    return raw, trial_events, beat_events
