modified the CustomAlgorithm._data_updated()

[temph2020]

I’ve modified the CustomAlgorithm._data_updated() method to prevent recalculating the factors each time. Instead, it now extracts the required period’s factor data from the already obtained full-period factor data. The full-period factor data has already been calculated in SimulationEventManager.run_simulation_alg(). Does this approach seem reasonable, and are there any potential side effects?

Here are my modifications:

1 In SimulationEventManager.run_simulation_alg(), I store the full-period factor data in the algorithm’s factor_all attribute (which I added to the algorithm class) as follows: data, _ = run_engine(start, end, delay_factor) # Obtain the full-period factor data starting from 'start' alg.factor_all = data # I add this line

2 In CustomAlgorithm._data_updated(), instead of running run_engine each time to calculate the factors, I extract the required period’s factor data from factor_all. This improves performance. def _data_updated(self, event_source=None): # self._data, self._last_row = self.run_engine(None, None) # Original code

# The following is my code
start = self._current_dt - self._history_window
end = self._current_dt
# Extract records from self.factor_all for the period from 'start' to 'end'
self._data = self.factor_all.loc[start:end]
self._last_row = self._data.loc[end]