ica.py 文件源码

def _detect_artifacts(ica, raw, start_find, stop_find, ecg_ch, ecg_score_func,
                      ecg_criterion, eog_ch, eog_score_func, eog_criterion,
                      skew_criterion, kurt_criterion, var_criterion,
                      add_nodes):
    """Aux Function"""
    from scipy import stats

    nodes = []
    if ecg_ch is not None:
        nodes += [_ica_node('ECG', ecg_ch, ecg_score_func, ecg_criterion)]

    if eog_ch not in [None, []]:
        if not isinstance(eog_ch, list):
            eog_ch = [eog_ch]
        for idx, ch in enumerate(eog_ch):
            nodes += [_ica_node('EOG %02d' % idx, ch, eog_score_func,
                      eog_criterion)]

    if skew_criterion is not None:
        nodes += [_ica_node('skewness', None, stats.skew, skew_criterion)]

    if kurt_criterion is not None:
        nodes += [_ica_node('kurtosis', None, stats.kurtosis, kurt_criterion)]

    if var_criterion is not None:
        nodes += [_ica_node('variance', None, np.var, var_criterion)]

    if add_nodes is not None:
        nodes.extend(add_nodes)

    for node in nodes:
        scores = ica.score_sources(raw, start=start_find, stop=stop_find,
                                   target=node.target,
                                   score_func=node.score_func)
        if isinstance(node.criterion, float):
            found = list(np.where(np.abs(scores) > node.criterion)[0])
        else:
            found = list(np.atleast_1d(abs(scores).argsort()[node.criterion]))

        case = (len(found), 's' if len(found) > 1 else '', node.name)
        logger.info('    found %s artifact%s by %s' % case)
        ica.exclude += found

    logger.info('Artifact indices found:\n    ' + str(ica.exclude).strip('[]'))
    if len(set(ica.exclude)) != len(ica.exclude):
        logger.info('    Removing duplicate indices...')
        ica.exclude = list(set(ica.exclude))

    logger.info('Ready.')