From 5957c64c24b093182c293a4064ac30592b44e57d Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Mon, 10 Feb 2025 20:48:27 +0100 Subject: [PATCH] =?utf8?q?fix(qav3):=20fix=20log=E2=80=91sum=E2=80=91exp?= =?utf8?q?=20computation?= MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- .../freqaimodels/LightGBMRegressorQuickAdapterV35.py | 4 ++-- .../user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py index 5726f8e..c1af399 100644 --- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py +++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py @@ -238,10 +238,10 @@ def min_max_pred( pred_df: pd.DataFrame, fit_live_predictions_candles: int, label_period_candles: int ): min_pred = pred_df.tail(label_period_candles).apply( - lambda col: smooth_min(col, beta=10) + lambda col: smooth_min(col, beta=10.0) ) max_pred = pred_df.tail(label_period_candles).apply( - lambda col: smooth_max(col, beta=10) + lambda col: smooth_max(col, beta=10.0) ) return min_pred, max_pred diff --git a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py index b2d1dbf..f2c28f8 100644 --- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py +++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py @@ -238,10 +238,10 @@ def min_max_pred( pred_df: pd.DataFrame, fit_live_predictions_candles: int, label_period_candles: int ): min_pred = pred_df.tail(label_period_candles).apply( - lambda col: smooth_min(col, beta=10) + lambda col: smooth_min(col, beta=10.0) ) max_pred = pred_df.tail(label_period_candles).apply( - lambda col: smooth_max(col, beta=10) + lambda col: smooth_max(col, beta=10.0) ) return min_pred, max_pred -- 2.43.0