pr review - refactoring backtesting freqai
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@@ -234,12 +234,12 @@ class IFreqaiModel(ABC):
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if self.backtest_prediction_exists(
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metadata["pair"], dk, trained_timestamp=trained_timestamp_int
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):
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prediction_filename, _ = self.get_backtesting_prediction_file_name(
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prediction_filename, root_prediction = self.get_backtesting_prediction_file_name(
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metadata["pair"],
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dk,
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trained_timestamp=int(trained_timestamp.stopts))
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append_df = dk.get_backtesting_prediction(prediction_filename)
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append_df = dk.get_backtesting_prediction(root_prediction, prediction_filename)
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dk.append_predictions(append_df)
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else:
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if not self.model_exists(
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@@ -680,10 +680,10 @@ class IFreqaiModel(ABC):
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:boolean: whether the prediction file exists or not.
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"""
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if not self.live:
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prediction_file_name, _ = self.get_backtesting_prediction_file_name(
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prediction_file_name, root_prediction = self.get_backtesting_prediction_file_name(
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pair, dk, trained_timestamp
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)
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path_to_predictionfile = Path(prediction_file_name)
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path_to_predictionfile = Path(dk.full_path / root_prediction / prediction_file_name)
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file_exists = path_to_predictionfile.is_file()
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if file_exists and not scanning:
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@@ -711,8 +711,8 @@ class IFreqaiModel(ABC):
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"""
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coin, _ = pair.split("/")
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prediction_base_filename = f"{coin.lower()}_{trained_timestamp}"
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root_prediction = f'{dk.full_path}/backtesting_predictions'
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prediction_file_name = f"{root_prediction}/{prediction_base_filename}_predictions.h5"
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root_prediction = 'backtesting_predictions'
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prediction_file_name = f"{prediction_base_filename}_predictions.h5"
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return prediction_file_name, root_prediction
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# Following methods which are overridden by user made prediction models.
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