style(quickadapter): wrap long lines

diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
index 4841aa71ceabc37ae98c2de2f8a15e465943cc2c..233abb4533f953684666f4a700b1cf57165b4df1 100644 (file)
--- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
+++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
@@ -381,7 +381,9 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
         unfiltered_df: pd.DataFrame,
     ) -> None:
         if not unfiltered_df.index.is_unique:
-            raise ValueError("unfiltered_df.index must be unique for causal split guards")
+            raise ValueError(
+                "unfiltered_df.index must be unique for causal split guards"
+            )
         if not filtered_dataframe.index.isin(unfiltered_df.index).all():
             raise ValueError(
                 "filtered_dataframe.index must be a subset of unfiltered_df.index"
@@ -395,7 +397,9 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
         QuickAdapterRegressorV3._validate_index_alignment(
             filtered_dataframe, unfiltered_df
         )
-        positions = pd.Series(np.arange(len(unfiltered_df), dtype=np.int64), index=unfiltered_df.index)
+        positions = pd.Series(
+            np.arange(len(unfiltered_df), dtype=np.int64), index=unfiltered_df.index
+        )
         return positions.loc[filtered_dataframe.index]
 
     @staticmethod
@@ -1593,9 +1597,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
                         known_at_train.to_numpy(dtype=np.int64) < first_test_position
                     )
                 else:
-                    _log_known_at_none_once(
-                        dk.pair, "train_test_split causal guard"
-                    )
+                    _log_known_at_none_once(dk.pair, "train_test_split causal guard")
                 train_features, train_labels, train_weights = (
                     QuickAdapterRegressorV3._filter_train_by_mask(
                         train_features,
@@ -1992,7 +1994,9 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
             )
             if known_at_index is not None:
                 known_at_train = known_at_index.iloc[train_idx]
-                keep_mask = known_at_train.to_numpy(dtype=np.int64) < first_test_position
+                keep_mask = (
+                    known_at_train.to_numpy(dtype=np.int64) < first_test_position
+                )
                 train_features, train_labels, train_weights = (
                     QuickAdapterRegressorV3._filter_train_by_mask(
                         train_features,
@@ -2003,9 +2007,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
                     )
                 )
             else:
-                _log_known_at_none_once(
-                    dk.pair, "timeseries_split causal guard"
-                )
+                _log_known_at_none_once(dk.pair, "timeseries_split causal guard")
 
         train_weights = sanitize_and_renormalize(
             train_weights, logger=logger, context="timeseries_split:train"

diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py
index 1a5af3f413b397b10ce864687be109af8d921fe3..3f01dd3e5321432dd8e7730b35a5b3fbe4c57d01 100644 (file)
--- a/quickadapter/user_data/strategies/QuickAdapterV3.py
+++ b/quickadapter/user_data/strategies/QuickAdapterV3.py
@@ -911,7 +911,9 @@ class QuickAdapterV3(IStrategy):
             dataframe[label_col] = label_data.series
 
             if label_data.known_at_index is not None:
-                dataframe[label_known_at_column_name(label_col)] = label_data.known_at_index
+                dataframe[label_known_at_column_name(label_col)] = (
+                    label_data.known_at_index
+                )
 
             label_weight_col = label_weight_column_name(label_col)
             if is_weighting_active:

diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py
index 925ab90aeb422b723de71bfa8c6e3d09aac5e819..67735ae79733cd8ea652a948f9d716e2aa87257d 100644 (file)
--- a/quickadapter/user_data/strategies/Utils.py
+++ b/quickadapter/user_data/strategies/Utils.py
@@ -3136,9 +3136,7 @@ def _validate_optuna_label_best_params(
         }
     if not isinstance(best_params, dict):
         if logger is not None:
-            logger.warning(
-                f"[{pair}] Ignoring Optuna label best-params: not a dict"
-            )
+            logger.warning(f"[{pair}] Ignoring Optuna label best-params: not a dict")
         return None
     schema_version = best_params.get("schema_version")
     if schema_version is None: