How to get optimal params from optimize method?

[TomaszLakota]

Hi, how do I get optimal params from optimize method? It's not specified in docs. I'd like to know optimal params, so I can use them live or to test them on different dataset (train-test split). I know there's a walkaround using method = 'skopt' and return_optimization = True, but I want to do exhaustive search.
Edit: I'm using heatmaps to find optimal parameters, but I'd like to automatize it for testing.

[kernc]

You can pass Backtest.optimize(..., return_heatmap=True) to get back a series of all tried parameter combinations with their result values. See how to handle it in #101.
Alternatively, as the tutorial briefly mentions, you can access the best parameters as set on the strategy instance:

stats = bt.optimize(...)
my_param1 = stats._strategy.my_param1
...
all_params: dict = stats._strategy._params  # This is private API, may change

[TomaszLakota]

Thanks, I used the method of transforming heatmap into a dataframe to get the best params

[PilotGFX]

after returning stats and heatmap from the optimizer, you can use the heatmap to extract the parameters.

best_params = optiheatmap.idxmax()
var1 = best_params[0]
var2 = best_params[1]
var3= best_params[2]

You can then either pass these on to update your strategyclass, or just pass them to the backtest as parameters as kernc have explained how to in other threads.