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Whenever restarting or switching datasets (which includes a restart) in the simulator environment,
the kalman filter object retains its object state (state matrix, process covariance matrix, etc), although the object should be re-initialized.
Not reinitializing them actually makes the performance worse on a second run as compared to a first run
Not reinitializing upon switching environments can actually make the kalman filter code crash
I printed out the full messages being received from the websocket connection, but there doesnt seem to be one including a flag for either 'restart' or for 'switched datasets'.
Currently seemingly only solution is upon restart, also quit the Kalman filter code and restart the code, but this is cumbersome. Is there a way to make the kalman filter code more robust by receiving some event when the code has to be re-initialized?
The text was updated successfully, but these errors were encountered:
Thanks for reaching out @Anner-deJong! I think this is something we've had as a "like-to-have" for a bit, but haven't ever implemented. I'll keep this open so we can make sure it stays on the radar.
Whenever restarting or switching datasets (which includes a restart) in the simulator environment,
the kalman filter object retains its object state (state matrix, process covariance matrix, etc), although the object should be re-initialized.
I printed out the full messages being received from the websocket connection, but there doesnt seem to be one including a flag for either 'restart' or for 'switched datasets'.
Currently seemingly only solution is upon restart, also quit the Kalman filter code and restart the code, but this is cumbersome. Is there a way to make the kalman filter code more robust by receiving some event when the code has to be re-initialized?
The text was updated successfully, but these errors were encountered: