bcic_iv_2a.py 文件源码

def extract_data(self):
        raw_edf = mne.io.read_raw_edf(self.filename, stim_channel='auto')
        raw_edf.load_data()
        # correct nan values

        data = raw_edf.get_data()

        # do not correct stimulus channel
        assert raw_edf.ch_names[-1] == 'STI 014'
        for i_chan in range(data.shape[0] - 1):
            # first set to nan, than replace nans by nanmean.
            this_chan = data[i_chan]
            data[i_chan] = np.where(this_chan == np.min(this_chan),
                                    np.nan, this_chan)
            mask = np.isnan(data[i_chan])
            chan_mean = np.nanmean(data[i_chan])
            data[i_chan, mask] = chan_mean
        gdf_events = raw_edf.find_edf_events()
        raw_edf = mne.io.RawArray(data, raw_edf.info, verbose='WARNING')
        # remember gdf events
        raw_edf.info['gdf_events'] = gdf_events
        return raw_edf