refactor: refine typing

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/ReforceXY/user_data/freqaimodels/ReforceXY.py b/ReforceXY/user_data/freqaimodels/ReforceXY.py
index c2e37346852ea65e2cda6efe33866d0287ff017c..d9ef7fe4ae15587355b319fd511eb82d05d767f6 100644 (file)
--- a/ReforceXY/user_data/freqaimodels/ReforceXY.py
+++ b/ReforceXY/user_data/freqaimodels/ReforceXY.py
@@ -621,7 +621,7 @@ class ReforceXY(BaseReinforcementLearningModel):
         return {**self.model_training_parameters, **best_trial_params}
 
     def save_best_trial_params(
-        self, best_trial_params: Dict, pair: Optional[str] = None
+        self, best_trial_params: Dict[str, Any], pair: Optional[str] = None
     ) -> None:
         """
         Save the best trial hyperparameters found during hyperparameter optimization
@@ -650,7 +650,9 @@ class ReforceXY(BaseReinforcementLearningModel):
             )
             raise
 
-    def load_best_trial_params(self, pair: Optional[str] = None) -> Optional[Dict]:
+    def load_best_trial_params(
+        self, pair: Optional[str] = None
+    ) -> Optional[Dict[str, Any]]:
         """
         Load the best trial hyperparameters found and saved during hyperparameter optimization
         """

diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py
index a2fe46d52f6f3d410cff7d5bdf962bab329ff88e..0d69185e866b521b6c150502af42808d7bdf3c3f 100644 (file)
--- a/quickadapter/user_data/strategies/QuickAdapterV3.py
+++ b/quickadapter/user_data/strategies/QuickAdapterV3.py
@@ -99,7 +99,7 @@ class QuickAdapterV3(IStrategy):
         return self.is_short_allowed()
 
     @cached_property
-    def plot_config(self) -> dict:
+    def plot_config(self) -> dict[str, Any]:
         return {
             "main_plot": {},
             "subplots": {
@@ -936,7 +936,9 @@ class QuickAdapterV3(IStrategy):
             smoothing_methods["gaussian"],
         )
 
-    def optuna_load_best_params(self, pair: str, namespace: str) -> Optional[dict]:
+    def optuna_load_best_params(
+        self, pair: str, namespace: str
+    ) -> Optional[dict[str, Any]]:
         best_params_path = Path(
             self.models_full_path
             / f"optuna-{namespace}-best-params-{pair.split('/')[0]}.json"