@verbose
    def filter(self, l_freq, h_freq, picks=None, filter_length='10s',
               l_trans_bandwidth=0.5, h_trans_bandwidth=0.5, n_jobs=1,
               method='fft', iir_params=None, verbose=None):
        fs = float(self.info['sfreq'])
        if l_freq == 0:
            l_freq = None
        if h_freq is not None and h_freq > (fs / 2.):
            h_freq = None
        if l_freq is not None and not isinstance(l_freq, float):
            l_freq = float(l_freq)
        if h_freq is not None and not isinstance(h_freq, float):
            h_freq = float(h_freq)
        _check_preload(self, 'raw.filter')
        if picks is None:
            picks = _pick_data_or_ica(self.info)
            # let's be safe.
            if len(picks) < 1:
                raise RuntimeError('Could not find any valid channels for '
                                   'your Raw object. Please contact the '
                                   'MNE-Python developers.')

            # update info if filter is applied to all data channels,
            # and it's not a band-stop filter
            if h_freq is not None:
                if (l_freq is None or l_freq < h_freq) and \
                   (self.info["lowpass"] is None or
                   h_freq < self.info['lowpass']):
                        self.info['lowpass'] = h_freq
            if l_freq is not None:
                if (h_freq is None or l_freq < h_freq) and \
                   (self.info["highpass"] is None or
                   l_freq > self.info['highpass']):
                        self.info['highpass'] = l_freq
        else:
            if h_freq is not None or l_freq is not None:
                logger.info('Filtering a subset of channels. The highpass and '
                            'lowpass values in the measurement info will not '
                            'be updated.')

        if l_freq is None and h_freq is not None:
            logger.info('Low-pass filtering at %0.2g Hz' % h_freq)
            low_pass_filter(self._data, fs, h_freq,
                            filter_length=filter_length,
                            trans_bandwidth=h_trans_bandwidth, method=method,
                            iir_params=iir_params, picks=picks, n_jobs=n_jobs,
                            copy=False)
        if l_freq is not None and h_freq is None:
            logger.info('High-pass filtering at %0.2g Hz' % l_freq)
            high_pass_filter(self._data, fs, l_freq,
                             filter_length=filter_length,
                             trans_bandwidth=l_trans_bandwidth, method=method,
                             iir_params=iir_params, picks=picks, n_jobs=n_jobs,
                             copy=False)
        if l_freq is not None and h_freq is not None:
            if l_freq < h_freq:
                logger.info('Band-pass filtering from %0.2g - %0.2g Hz'
                            % (l_freq, h_freq))
                self._data = band_pass_filter(
                    self._data, fs, l_freq, h_freq,
                    filter_length=filter_length,
                    l_trans_bandwidth=l_trans_bandwidth,
                    h_trans_bandwidth=h_trans_bandwidth,
                    method=method, iir_params=iir_params, picks=picks,
                    n_jobs=n_jobs, copy=False)
            else:
                logger.info('Band-stop filtering from %0.2g - %0.2g Hz'
                            % (h_freq, l_freq))
                self._data = band_stop_filter(
                    self._data, fs, h_freq, l_freq,
                    filter_length=filter_length,
                    l_trans_bandwidth=h_trans_bandwidth,
                    h_trans_bandwidth=l_trans_bandwidth, method=method,
                    iir_params=iir_params, picks=picks, n_jobs=n_jobs,
                    copy=False)
        return self
Returns the maximum inconsistency coefficient for each
dataset/ETHPy150Open mne-tools/mne-python/mne/io/base.py/_BaseRaw.filter--crossover with--dataset/ETHPy150Open scipy/scipy/scipy/cluster/hierarchy.py/maxinconsts