refactor(qav3): align optuna results handling namespace

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

diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
index f6878e520f1bab1874c9b71d49cfc9f5805f15ec..414610df9e9db52548f83a2b69d62eaa6dccf83e 100644 (file)
--- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
+++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
@@ -86,15 +86,15 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
             and self._optuna_config.get("enabled")
             and self.data_split_parameters.get("test_size", TEST_SIZE) > 0
         )
-        self._optuna_hp_rmse: dict[str, float] = {}
-        self._optuna_train_rmse: dict[str, float] = {}
+        self._optuna_hp_value: dict[str, float] = {}
+        self._optuna_train_value: dict[str, float] = {}
         self._optuna_label_values: dict[str, dict] = {}
         self._optuna_hp_params: dict[str, dict] = {}
         self._optuna_train_params: dict[str, dict] = {}
         self._optuna_label_params: dict[str, dict] = {}
         for pair in self.pairs:
-            self._optuna_hp_rmse[pair] = -1
-            self._optuna_train_rmse[pair] = -1
+            self._optuna_hp_value[pair] = -1
+            self._optuna_train_value[pair] = -1
             self._optuna_label_values[pair] = [-1, -1]
             self._optuna_hp_params[pair] = (
                 self.optuna_load_best_params(pair, "hp")
@@ -141,20 +141,20 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
         else:
             raise ValueError(f"Invalid namespace: {namespace}")
 
-    def get_optuna_rmse(self, pair: str, namespace: str) -> float:
+    def get_optuna_value(self, pair: str, namespace: str) -> float:
         if namespace == "hp":
-            rmse = self._optuna_hp_rmse.get(pair)
+            rmse = self._optuna_hp_value.get(pair)
         elif namespace == "train":
-            rmse = self._optuna_train_rmse.get(pair)
+            rmse = self._optuna_train_value.get(pair)
         else:
             raise ValueError(f"Invalid namespace: {namespace}")
         return rmse
 
-    def set_optuna_rmse(self, pair: str, namespace: str, rmse: float) -> None:
+    def set_optuna_value(self, pair: str, namespace: str, value: float) -> None:
         if namespace == "hp":
-            self._optuna_hp_rmse[pair] = rmse
+            self._optuna_hp_value[pair] = value
         elif namespace == "train":
-            self._optuna_train_rmse[pair] = rmse
+            self._optuna_train_value[pair] = value
         else:
             raise ValueError(f"Invalid namespace: {namespace}")
 
@@ -351,8 +351,10 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
             pair, "label"
         ).get("label_natr_ratio")
 
-        dk.data["extra_returns_per_train"]["hp_rmse"] = self.get_optuna_rmse(pair, "hp")
-        dk.data["extra_returns_per_train"]["train_rmse"] = self.get_optuna_rmse(
+        dk.data["extra_returns_per_train"]["hp_rmse"] = self.get_optuna_value(
+            pair, "hp"
+        )
+        dk.data["extra_returns_per_train"]["train_rmse"] = self.get_optuna_value(
             pair, "train"
         )
 
@@ -488,10 +490,10 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
                     f"Optuna {pair} {namespace} {objective_type} hyperopt failed ({time_spent:.2f} secs): no study best trial found"
                 )
                 return
-            self.set_optuna_rmse(pair, namespace, study.best_value)
+            self.set_optuna_value(pair, namespace, study.best_value)
             self.set_optuna_params(pair, namespace, study.best_params)
             study_results = {
-                "rmse": self.get_optuna_rmse(pair, namespace),
+                "value": self.get_optuna_value(pair, namespace),
                 **self.get_optuna_params(pair, namespace),
             }
         else: