]> Piment Noir Git Repositories - freqai-strategies.git/commitdiff
refactor(qav3): refine typing
authorJérôme Benoit <jerome.benoit@piment-noir.org>
Wed, 25 Jun 2025 17:36:01 +0000 (19:36 +0200)
committerJérôme Benoit <jerome.benoit@piment-noir.org>
Wed, 25 Jun 2025 17:36:01 +0000 (19:36 +0200)
Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>
quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
quickadapter/user_data/strategies/QuickAdapterV3.py

index ec83444f7b810b09afada763ed4be9f1cb48f843..dc907f77fd09c41400dee2bf619e1beb7a2db508 100644 (file)
@@ -1144,9 +1144,9 @@ def train_objective(
     X_test = X_test.iloc[-test_window:]
     y_test = y_test.iloc[-test_window:]
     test_extrema = y_test.get(EXTREMA_COLUMN)
-    n_test_minima = sp.signal.find_peaks(-test_extrema)[0].size
-    n_test_maxima = sp.signal.find_peaks(test_extrema)[0].size
-    n_test_extrema = n_test_minima + n_test_maxima
+    n_test_minima: int = sp.signal.find_peaks(-test_extrema)[0].size
+    n_test_maxima: int = sp.signal.find_peaks(test_extrema)[0].size
+    n_test_extrema: int = n_test_minima + n_test_maxima
     min_test_extrema: int = calculate_min_extrema(
         test_window, fit_live_predictions_candles
     )
@@ -1182,9 +1182,9 @@ def train_objective(
     X = X.iloc[-train_window:]
     y = y.iloc[-train_window:]
     train_extrema = y.get(EXTREMA_COLUMN)
-    n_train_minima = sp.signal.find_peaks(-train_extrema)[0].size
-    n_train_maxima = sp.signal.find_peaks(train_extrema)[0].size
-    n_train_extrema = n_train_minima + n_train_maxima
+    n_train_minima: int = sp.signal.find_peaks(-train_extrema)[0].size
+    n_train_maxima: int = sp.signal.find_peaks(train_extrema)[0].size
+    n_train_extrema: int = n_train_minima + n_train_maxima
     min_train_extrema: int = calculate_min_extrema(
         train_window, fit_live_predictions_candles
     )
index 07a6bd57a5e2a08aa11305d34af1e68855bc9425..72e469598fec2f36e39185a2248eacd8c67aed64 100644 (file)
@@ -456,9 +456,9 @@ class QuickAdapterV3(IStrategy):
         )
         if debug:
             logger.info(f"{dataframe[EXTREMA_COLUMN].to_numpy()=}")
-            n_minima = sp.signal.find_peaks(-dataframe[EXTREMA_COLUMN])[0].size
-            n_maxima = sp.signal.find_peaks(dataframe[EXTREMA_COLUMN])[0].size
-            n_extrema = n_minima + n_maxima
+            n_minima: int = sp.signal.find_peaks(-dataframe[EXTREMA_COLUMN])[0].size
+            n_maxima: int = sp.signal.find_peaks(dataframe[EXTREMA_COLUMN])[0].size
+            n_extrema: int = n_minima + n_maxima
             logger.info(f"{n_extrema=}")
         return dataframe