From d7850ba91381fb16d65d99ef109cc7e7c4a7218f Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Thu, 2 Oct 2025 19:24:55 +0200 Subject: [PATCH] refactor(reforcexy): align namespace for window conv width 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 | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/ReforceXY/user_data/freqaimodels/ReforceXY.py b/ReforceXY/user_data/freqaimodels/ReforceXY.py index 4bbdb8e..bcc1fc7 100644 --- a/ReforceXY/user_data/freqaimodels/ReforceXY.py +++ b/ReforceXY/user_data/freqaimodels/ReforceXY.py @@ -727,7 +727,7 @@ class ReforceXY(BaseReinforcementLearningModel): :param dk: FreqaiDatakitchen = data kitchen for the current pair :param model: Any = the trained model used to inference the features. """ - add_state_info = self.rl_config.get("add_state_info", False) + add_state_info: bool = self.rl_config.get("add_state_info", False) virtual_position: Positions = Positions.Neutral virtual_trade_duration: int = 0 if add_state_info and self.live: @@ -737,11 +737,11 @@ class ReforceXY(BaseReinforcementLearningModel): np_dataframe: NDArray[np.float32] = dataframe.to_numpy( dtype=np.float32, copy=False ) - n = int(np_dataframe.shape[0]) - window_length = int(self.CONV_WIDTH) - frame_stacking = self.frame_stacking - frame_stacking_activated = bool(frame_stacking) and frame_stacking > 1 - inference_masking = self.action_masking and self.inference_masking + n = np_dataframe.shape[0] + window_size: int = self.CONV_WIDTH + frame_stacking: int = self.frame_stacking + frame_stacking_activated: bool = bool(frame_stacking) and frame_stacking > 1 + inference_masking: bool = self.action_masking and self.inference_masking def _update_virtual_position(action: int, position: Positions) -> Positions: if action == Actions.Long_enter.value and position == Positions.Neutral: @@ -771,7 +771,7 @@ class ReforceXY(BaseReinforcementLearningModel): def _predict(start_idx: int) -> int: nonlocal zero_frame - end_idx = start_idx + window_length + end_idx: int = start_idx + window_size np_observation = np_dataframe[start_idx:end_idx, :] action_masks_param: Dict[str, Any] = {} @@ -832,7 +832,7 @@ class ReforceXY(BaseReinforcementLearningModel): return int(action) predicted_actions: List[int] = [] - for start_idx in range(0, n - window_length + 1): + for start_idx in range(0, n - window_size + 1): action = _predict(start_idx) predicted_actions.append(action) previous_virtual_position = virtual_position -- 2.43.0