()
| 5 | |
| 6 | |
| 7 | def main(): |
| 8 | BoardShim.enable_dev_board_logger() |
| 9 | |
| 10 | # use synthetic board for demo |
| 11 | params = BrainFlowInputParams() |
| 12 | board = BoardShim(BoardIds.SYNTHETIC_BOARD.value, params) |
| 13 | board.prepare_session() |
| 14 | board.start_stream() |
| 15 | BoardShim.log_message(LogLevels.LEVEL_INFO.value, 'start sleeping in the main thread') |
| 16 | time.sleep(10) |
| 17 | data = board.get_board_data(20) |
| 18 | board.stop_stream() |
| 19 | board.release_session() |
| 20 | |
| 21 | eeg_channels = BoardShim.get_eeg_channels(BoardIds.SYNTHETIC_BOARD.value) |
| 22 | # demo for downsampling, it just aggregates data |
| 23 | for count, channel in enumerate(eeg_channels): |
| 24 | print('Original data for channel %d:' % channel) |
| 25 | print(data[channel]) |
| 26 | if count == 0: |
| 27 | downsampled_data = DataFilter.perform_downsampling(data[channel], 3, AggOperations.MEDIAN.value) |
| 28 | elif count == 1: |
| 29 | downsampled_data = DataFilter.perform_downsampling(data[channel], 2, AggOperations.MEAN.value) |
| 30 | else: |
| 31 | downsampled_data = DataFilter.perform_downsampling(data[channel], 2, AggOperations.EACH.value) |
| 32 | print('Downsampled data for channel %d:' % channel) |
| 33 | print(downsampled_data) |
| 34 | |
| 35 | |
| 36 | if __name__ == "__main__": |
no test coverage detected