def load_raw_data(subject, test=False):
    fnames_train = glob('../data/train/subj%d_series*_data.csv' % (subject))
    fnames_train.sort()
    if test:
        fnames_test = glob('../data/test/subj%d_series*_data.csv' % (subject))
        fnames_test.sort()
    else:
        fnames_test = fnames_train[-2:]
        fnames_train = fnames_train[:-2]

    # read and concatenate all the files
    raw_train = [creat_mne_raw_object(fname) for fname in fnames_train]
    raw_train = concatenate_raws(raw_train)
    # pick eeg signal
    picks = pick_types(raw_train.info, eeg=True)

    # get training data
    data_train = raw_train._data[picks].T
    labels_train = raw_train._data[32:].T

    raw_test = [creat_mne_raw_object(fname, read_events=not test) for fname in
                fnames_test]
    raw_test = concatenate_raws(raw_test)
    data_test = raw_test._data[picks].T

    # extract labels if validating on series 7&8
    labels_test = None
    if not test:
        labels_test = raw_test._data[32:].T

    return data_train, labels_train, data_test, labels_test
aMeth in dict lookup - without autocalling
dataset/ETHPy150Open alexandrebarachant/Grasp-and-lift-EEG-challenge/preprocessing/aux.py/load_raw_data--crossover with--dataset/ETHPy150Open skyostil/tracy/src/generator/Cheetah/Tests/NameMapper.py/VFN.test39