How to use the brainflow.board_shim.BoardIds.SYNTHETIC_BOARD function in brainflow

def main ():
    BoardShim.enable_dev_board_logger ()

    # use synthetic board for demo
    params = BrainFlowInputParams ()
    board_id = BoardIds.SYNTHETIC_BOARD.value
    board = BoardShim (board_id, params)
    board.prepare_session ()
    board.start_stream ()
    BoardShim.log_message (LogLevels.LEVEL_INFO.value, 'start sleeping in the main thread')
    time.sleep (10)
    data = board.get_board_data ()
    board.stop_stream ()
    board.release_session ()

    eeg_channels = BoardShim.get_eeg_channels (board_id)
    # demo for transforms
    for count, channel in enumerate (eeg_channels):
        print ('Original data for channel %d:' % channel)
        print (data[channel])
        # demo for wavelet transforms
        # wavelet_coeffs format is[A(J) D(J) D(J-1) ..... D(1)] where J is decomposition level, A - app coeffs, D - detailed coeffs

params.ip_port = args.ip_port
    params.serial_port = args.serial_port
    params.mac_address = args.mac_address
    params.other_info = args.other_info
    params.ip_address = args.ip_address
    params.ip_protocol = args.ip_protocol

    synth_params = BrainFlowInputParams ()

    if (args.log):
        BoardShim.enable_dev_board_logger ()
    else:
        BoardShim.disable_board_logger ()

    board = BoardShim (args.board_id, params)
    synth_board = BoardShim (brainflow.board_shim.BoardIds.SYNTHETIC_BOARD.value, synth_params)
    board.prepare_session ()
    synth_board.prepare_session ()

    board.start_stream ()
    synth_board.start_stream ()
    time.sleep (10)
    data = board.get_board_data ()
    synth_data = synth_board.get_board_data ()
    board.stop_stream ()
    synth_board.stop_stream ()
    board.release_session ()
    synth_board.release_session ()

def main():
    BoardShim.enable_dev_board_logger ()
    # use synthetic board for demo
    params = BrainFlowInputParams ()
    board = BoardShim (BoardIds.SYNTHETIC_BOARD.value, params)
    board.prepare_session ()
    board.start_stream ()
    time.sleep (10)
    data = board.get_board_data ()
    board.stop_stream ()
    board.release_session ()

    eeg_channels = BoardShim.get_eeg_channels (BoardIds.SYNTHETIC_BOARD.value)
    eeg_data = data[eeg_channels, :]
    eeg_data = eeg_data / 1000000 # BrainFlow returns uV, convert to V for MNE

    # Creating MNE objects from brainflow data arrays
    ch_types = ['eeg', 'eeg', 'eeg', 'eeg', 'eeg', 'eeg', 'eeg', 'eeg']
    ch_names = ['T7', 'CP5', 'FC5', 'C3', 'C4', 'FC6', 'CP6', 'T8']
    sfreq = BoardShim.get_sampling_rate (BoardIds.SYNTHETIC_BOARD.value)
    info = mne.create_info (ch_names = ch_names, sfreq = sfreq, ch_types = ch_types)

def main():
    BoardShim.enable_dev_board_logger ()
    # use synthetic board for demo
    params = BrainFlowInputParams ()
    board = BoardShim (BoardIds.SYNTHETIC_BOARD.value, params)
    board.prepare_session ()
    board.start_stream ()
    time.sleep (10)
    data = board.get_board_data ()
    board.stop_stream ()
    board.release_session ()

    eeg_channels = BoardShim.get_eeg_channels (BoardIds.SYNTHETIC_BOARD.value)
    eeg_data = data[eeg_channels, :]
    eeg_data = eeg_data / 1000000 # BrainFlow returns uV, convert to V for MNE

    # Creating MNE objects from brainflow data arrays
    ch_types = ['eeg', 'eeg', 'eeg', 'eeg', 'eeg', 'eeg', 'eeg', 'eeg']
    ch_names = ['T7', 'CP5', 'FC5', 'C3', 'C4', 'FC6', 'CP6', 'T8']
    sfreq = BoardShim.get_sampling_rate (BoardIds.SYNTHETIC_BOARD.value)
    info = mne.create_info (ch_names = ch_names, sfreq = sfreq, ch_types = ch_types)
    raw = mne.io.RawArray (eeg_data, info)
    # its time to plot something!
    raw.plot_psd (average = True)
    plt.savefig ('psd.png')