def METHOD_NAME(self):
    self._header_dict = open_biocam_file_header(self.filename)
    self._num_channels = self._header_dict["num_channels"]
    self._num_frames = self._header_dict["num_frames"]
    self._sampling_rate = self._header_dict["sampling_rate"]
    self._filehandle = self._header_dict["file_handle"]
    self._read_function = self._header_dict["read_function"]
    self._channels = self._header_dict["channels"]
    gain = self._header_dict["gain"]
    offset = self._header_dict["offset"]
    signal_streams = np.array([('Signals', '0')], dtype=_signal_stream_dtype)
    sig_channels = []
    for c, chan in enumerate(self._channels):
        ch_name = f'ch{chan[0]}-{chan[1]}'
        chan_id = str(c + 1)
        sr = self._sampling_rate  # Hz
        dtype = "uint16"
        units = 'uV'
        gain = gain
        offset = offset
        stream_id = '0'
        sig_channels.append((ch_name, chan_id, sr, dtype, units, gain, offset, stream_id))
    sig_channels = np.array(sig_channels, dtype=_signal_channel_dtype)
    # No events
    event_channels = []
    event_channels = np.array(event_channels, dtype=_event_channel_dtype)
    # No spikes
    spike_channels = []
    spike_channels = np.array(spike_channels, dtype=_spike_channel_dtype)
    self.header = {}
    self.header['nb_block'] = 1
    self.header['nb_segment'] = [1]
    self.header['signal_streams'] = signal_streams
    self.header['signal_channels'] = sig_channels
    self.header['spike_channels'] = spike_channels
    self.header['event_channels'] = event_channels
    self._generate_minimal_annotations()