From 2894c13804d91afd5fe1b19d567d1a7aecf07c99 Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Wed, 6 Aug 2025 19:46:25 +0200 Subject: [PATCH] refactor(qav3): utils function namespace alignment MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- ReforceXY/user_data/freqaimodels/ReforceXY.py | 1 - ReforceXY/user_data/strategies/RLAgentStrategy.py | 1 - .../user_data/freqaimodels/QuickAdapterRegressorV3.py | 6 +++--- quickadapter/user_data/strategies/Utils.py | 3 +-- 4 files changed, 4 insertions(+), 7 deletions(-) diff --git a/ReforceXY/user_data/freqaimodels/ReforceXY.py b/ReforceXY/user_data/freqaimodels/ReforceXY.py index 0c315f0..147dccd 100644 --- a/ReforceXY/user_data/freqaimodels/ReforceXY.py +++ b/ReforceXY/user_data/freqaimodels/ReforceXY.py @@ -43,7 +43,6 @@ from freqtrade.freqai.RL.BaseReinforcementLearningModel import ( from freqtrade.freqai.tensorboard.TensorboardCallback import TensorboardCallback from freqtrade.strategy import timeframe_to_minutes - matplotlib.use("Agg") warnings.filterwarnings("ignore", category=UserWarning) warnings.filterwarnings("ignore", category=FutureWarning) diff --git a/ReforceXY/user_data/strategies/RLAgentStrategy.py b/ReforceXY/user_data/strategies/RLAgentStrategy.py index fa14346..6eb3c9d 100644 --- a/ReforceXY/user_data/strategies/RLAgentStrategy.py +++ b/ReforceXY/user_data/strategies/RLAgentStrategy.py @@ -7,7 +7,6 @@ from pandas import DataFrame from freqtrade.strategy import IStrategy - logger = logging.getLogger(__name__) ACTION_COLUMN = "&-action" diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index 934765e..98e7b01 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -21,7 +21,7 @@ from Utils import ( calculate_min_extrema, calculate_n_extrema, fit_regressor, - get_callbacks, + get_optuna_callbacks, get_optuna_study_model_parameters, largest_divisor, round_to_nearest_int, @@ -1279,7 +1279,7 @@ def train_objective( eval_set=[(X_test, y_test)], eval_weights=[test_weights], model_training_parameters=model_training_parameters, - callbacks=get_callbacks(trial, regressor), + callbacks=get_optuna_callbacks(trial, regressor), ) y_pred = model.predict(X_test) @@ -1314,7 +1314,7 @@ def hp_objective( eval_set=[(X_test, y_test)], eval_weights=[test_weights], model_training_parameters=model_training_parameters, - callbacks=get_callbacks(trial, regressor), + callbacks=get_optuna_callbacks(trial, regressor), ) y_pred = model.predict(X_test) diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py index 6eb70c2..6b8d5f4 100644 --- a/quickadapter/user_data/strategies/Utils.py +++ b/quickadapter/user_data/strategies/Utils.py @@ -13,7 +13,6 @@ import talib.abstract as ta from technical import qtpylib - T = TypeVar("T", pd.Series, float) @@ -631,7 +630,7 @@ def zigzag( regressors = {"xgboost", "lightgbm"} -def get_callbacks(trial: optuna.trial.Trial, regressor: str) -> list[Callable]: +def get_optuna_callbacks(trial: optuna.trial.Trial, regressor: str) -> list[Callable]: if regressor == "xgboost": callbacks = [ optuna.integration.XGBoostPruningCallback(trial, "validation_0-rmse") -- 2.43.0