Main loop for speed inference data preparation.

speed_prep_main.py

def main():
    config = get_config(tile_extract='./valhalla/custom_files/valhalla_tiles.tar', 
                        verbose=True)

    trips = get_all_trips()

    for traj_id, vehicle_id, trip_id in trips:
        print(f"Vehicle {vehicle_id}, trip {trip_id}, trajectory: {traj_id}")

        trip_df = get_trip_signals(vehicle_id, trip_id)
        lat_array = trip_df["match_latitude"].values
        lon_array = trip_df["match_longitude"].values
        time_stamps = trip_df["time_stamp"].values
        day_num = float(trip_df["day_num"].values[0])

        trajectory = Trajectory(lat=lat_array, lon=lon_array, time=time_stamps)

        try:
            actor = Actor(config)
            encoded_line = map_match(actor, list(zip(lon_array, lat_array)))
        except RuntimeError as e:
            print(e)
            continue

        polyline = np.array(decode_polyline(encoded_line, order="latlng"))

        compound = CompoundTrajectory(trajectory, polyline[:,0], polyline[:,1])
        converted = compound.to_trajectory()

        segments = generate_segments(converted, day_num, traj_id)
        if len(segments):
            insert_segments(segments)