I have some data which is trades data, and full order snapshots only. I've created a import and digest strategy based off of Tardis and BinanceFutures import regime.
Will the backtest function without DEPTH_EVENTs eg I only have DEPTH_CLEAR_EVENT, DEPTH_SNAPSHOT_EVENT and TRADE_EVENT? Or am I barking up a wrong tree here?
Everything seems to load in and the data structure and aggregation match what appears to be the desired output and example functions run, but what the backtester sees and what the data is aren't congruent.
Snapshot of 5 levels (which are consumed and produced into multiple rows with same execution timestamp and DEPTH_CLEAR_EVENT before DEPTH_SNAPSHOT_EVENT)
![Screenshot 2023-09-27 at 10 02 23 AM](https://private-user-images.githubusercontent.com/1007667/271005059-c00d5217-16e7-45b0-8660-34d994b436a6.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.AoRC-fEPnZ5PuOSWsutVyOOxQg8mawVhwE_u7-bnB04)
Example output from the data aggregation (and following the Data Preparation workbook)
data = create_last_snapshot(f"{DATA_FOLDER}{EXPORT_FILE_NAME}", tick_size=TICK_SIZE, lot_size=LOT_SIZE)
# Create snapshot for end of day.
np.savez(f"{DATA_FOLDER}{EXPORT_SNAPSHOT_FILE_NAME}", data=data)
data
array([[ 4.0000000e+00, 1.6833258e+15, -1.0000000e+00, 1.0000000e+00,
2.0612000e+03, 1.0000000e+00],
[ 4.0000000e+00, 1.6833258e+15, -1.0000000e+00, 1.0000000e+00,
2.0611000e+03, 9.0000000e+00],
[ 4.0000000e+00, 1.6833258e+15, -1.0000000e+00, 1.0000000e+00,
2.0610000e+03, 8.0000000e+00],
...,
[ 4.0000000e+00, 1.6833258e+15, -1.0000000e+00, -1.0000000e+00,
2.0615000e+03, 1.5000000e+01],
[ 4.0000000e+00, 1.6833258e+15, -1.0000000e+00, -1.0000000e+00,
2.0616000e+03, 6.0000000e+00],
[ 4.0000000e+00, 1.6833258e+15, -1.0000000e+00, -1.0000000e+00,
2.0617000e+03, 1.1000000e+01]])
Happy to provide more details and additional information, just wondering where I might start (as the only key difference is the lack of DEPTH_EVENTs when comparing the two datasets).