refactor(qav3): refine typing

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 f5948e71d20354d3324c9a418ef955c3939ac543..fbea95e9c8083be2fcee0f1726716b1e3ea0cc15 100644 (file)
--- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
+++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
@@ -302,7 +302,9 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
         prediction_thresholds_smoothing = self.freqai_info.get(
             "prediction_thresholds_smoothing", "quantile"
         )
-        smoothing_methods: dict[str, Callable] = {
+        smoothing_methods: dict[
+            str, Callable[[pd.DataFrame, int, int], tuple[pd.Series, pd.Series]]
+        ] = {
             "quantile": self.quantile_min_max_pred,
             "mean": QuickAdapterRegressorV3.mean_min_max_pred,
             "median": QuickAdapterRegressorV3.median_min_max_pred,

diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py
index 8cad3a99a8f49ff7f1e9f12f8ebe2fc43617e104..9f62adf6a11b6f45bf4fd18c4ea0cda6170719ec 100644 (file)
--- a/quickadapter/user_data/strategies/QuickAdapterV3.py
+++ b/quickadapter/user_data/strategies/QuickAdapterV3.py
@@ -7,7 +7,7 @@ from pathlib import Path
 from statistics import harmonic_mean
 import talib.abstract as ta
 from pandas import DataFrame, Series, isna
-from typing import Callable, Optional
+from typing import Optional
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date
 from freqtrade.strategy.interface import IStrategy
 from freqtrade.strategy import stoploss_from_absolute
@@ -654,7 +654,7 @@ class QuickAdapterV3(IStrategy):
             std = derive_gaussian_std_from_window(window)
         gaussian_window = get_gaussian_window(std, True)
         odd_window = get_odd_window(window)
-        smoothing_methods: dict[str, Callable] = {
+        smoothing_methods: dict[str, Series] = {
             "gaussian": series.rolling(
                 window=gaussian_window,
                 win_type="gaussian",