data_tools.lap_tools.collect_lap_data

data_tools.lap_tools.collect_lap_data(query_func: Callable, client: DBClient, include_day_2=False, verbose=False) → ndarray

Higher order function - computes query_func for each lap in FSGP 2024 and returns the resulting array.

Set include_day_2 to True to include the day 2 laps, which were driven slowly & under heavy rain.

Example usage:

```python from data_tools.collections import collect_lap_data, TimeSeries from data_tools.query import DBClient import datetime import numpy as np

def get_average_speed(start_time: datetime.datetime, end_time: datetime.datetime, data_client: DBClient):

lap_speed: TimeSeries = data_client.query_time_series(start_time, end_time, “VehicleVelocity”) return np.mean(lap_speed)

client = DBClient()

average_speeds = collect_lap_data(get_average_speed, client) ```

Parameters:

• query_func (Callable) – must take in parameters (lap_start: datetime, lap_end:datetime, data_client:DBClient)

• client (DBClient) – client to use for querying

• include_day_2 – flag to include the three day 2 laps, driven slowly & under heavy rain

• verbose – if True, print out queried data during execution

Returns:

a NumPy ndarray of query_func results for all laps