'Aux method.'

def _fit_raw(self, raw, picks, start, stop, decim, reject, flat, tstep, reject_by_annotation, verbose):

    if (self.current_fit != 'unfitted'):
        self._reset()
    if (picks is None):
        picks = _pick_data_channels(raw.info, exclude='bads', with_ref_meg=False)
    logger.info(('Fitting    ICA    to    data    using    %i    channels.    \nPlease    be    patient,    this    may    take    some    time' % len(picks)))
    if (self.max_pca_components is None):
        self.max_pca_components = len(picks)
        logger.info('Inferring    max_pca_components    from    picks.')
    self.info = pick_info(raw.info, picks)
    if self.info['comps']:
        self.info['comps'] = []
    self.ch_names = self.info['ch_names']
    (start, stop) = _check_start_stop(raw, start, stop)
    reject_by_annotation = ('omit' if reject_by_annotation else None)
    data = raw.get_data(picks, start, stop, reject_by_annotation)
    if (decim is not None):
        data = data[:, ::decim]
    if ((reject is not None) or (flat is not None)):
        (data, self.drop_inds_) = _reject_data_segments(data, reject, flat, decim, self.info, tstep)
    self.n_samples_ = data.shape[1]
    (data, self._pre_whitener) = self._pre_whiten(data, raw.info, picks)
    self._fit(data, self.max_pca_components, 'raw')
    return self
