motionsense.py 文件源码

def attachment_marker(raw_stream_id: uuid, stream_name: str, owner_id: uuid, dd_stream_name, CC: CerebralCortex,
                      config: dict):
    """
    Label sensor data as sensor-on-body, sensor-off-body, or improper-attachment.
    All the labeled data (st, et, label) with its metadata are then stored in a datastore

    """
    # TODO: quality streams could be multiple so find the one computed with CC
    # using stream_id, data-diagnostic-stream-id, and owner id to generate a unique stream ID for battery-marker
    attachment_marker_stream_id = uuid.uuid3(uuid.NAMESPACE_DNS, str(raw_stream_id + dd_stream_name + owner_id))

    stream_days = get_stream_days(raw_stream_id, attachment_marker_stream_id, CC)

    for day in stream_days:
        # load stream data to be diagnosed
        raw_stream = CC.get_datastream(raw_stream_id, day, data_type=DataSet.COMPLETE)

        if len(raw_stream.data) > 0:
            windowed_data = window(raw_stream.data, config['general']['window_size'], True)
            results = process_windows(windowed_data, config)
            merged_windows = merge_consective_windows(results)

            input_streams = [{"owner_id": owner_id, "id": str(raw_stream_id), "name": stream_name}]
            output_stream = {"id": attachment_marker_stream_id, "name": dd_stream_name,
                             "algo_type": config["algo_type"]["attachment_marker"]}
            metadata = get_metadata(dd_stream_name, input_streams, config)
            store(merged_windows, input_streams, output_stream, metadata, CC, config)