update code to freqai_backtest_live_models only from historic predictions
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@@ -68,10 +68,6 @@ class IFreqaiModel(ABC):
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self.save_backtest_models: bool = self.freqai_info.get("save_backtest_models", True)
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if self.save_backtest_models:
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logger.info('Backtesting module configured to save all models.')
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self.backtest_using_historic_predictions: bool = self.freqai_info.get(
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"backtest_using_historic_predictions", True)
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if self.backtest_using_historic_predictions:
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logger.info('Backtesting live models configured to use historic predictions.')
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self.dd = FreqaiDataDrawer(Path(self.full_path), self.config, self.follow_mode)
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# set current candle to arbitrary historical date
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@@ -148,23 +144,18 @@ class IFreqaiModel(ABC):
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elif not self.follow_mode:
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self.dk = FreqaiDataKitchen(self.config, self.live, metadata["pair"])
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if self.dk.backtest_live_models:
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if self.backtest_using_historic_predictions:
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logger.info(
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"Backtesting using historic predictions (live models)")
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else:
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logger.info(
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f"Backtesting {len(self.dk.backtesting_timeranges)} "
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"timeranges (live models)")
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logger.info(
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"Backtesting using historic predictions (live models)")
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else:
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logger.info(f"Training {len(self.dk.training_timeranges)} timeranges")
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dataframe = self.dk.use_strategy_to_populate_indicators(
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strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
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)
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if not self.backtest_using_historic_predictions:
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if not self.config.get("freqai_backtest_live_models", False):
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dk = self.start_backtesting(dataframe, metadata, self.dk)
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dataframe = dk.remove_features_from_df(dk.return_dataframe)
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else:
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dk = self.start_backtesting_from_live_saved_files(
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dk = self.start_backtesting_from_historic_predictions(
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dataframe, metadata, self.dk)
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dataframe = dk.return_dataframe
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@@ -330,7 +321,7 @@ class IFreqaiModel(ABC):
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return dk
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def start_backtesting_from_live_saved_files(
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def start_backtesting_from_historic_predictions(
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self, dataframe: DataFrame, metadata: dict, dk: FreqaiDataKitchen
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) -> FreqaiDataKitchen:
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"""
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