added again feature check in BT from pred files
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@ -273,7 +273,7 @@ class IFreqaiModel(ABC):
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train_it = 0
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train_it = 0
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pair = metadata["pair"]
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pair = metadata["pair"]
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populate_indicators = True
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populate_indicators = True
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check_features = True
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# Loop enforcing the sliding window training/backtesting paradigm
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# Loop enforcing the sliding window training/backtesting paradigm
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# tr_train is the training time range e.g. 1 historical month
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# tr_train is the training time range e.g. 1 historical month
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# tr_backtest is the backtesting time range e.g. the week directly
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# tr_backtest is the backtesting time range e.g. the week directly
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@ -301,9 +301,14 @@ class IFreqaiModel(ABC):
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dk.set_new_model_names(pair, timestamp_model_id)
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dk.set_new_model_names(pair, timestamp_model_id)
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if dk.check_if_backtest_prediction_is_valid(len_backtest_df):
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if dk.check_if_backtest_prediction_is_valid(len_backtest_df):
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# self.dd.load_metadata(dk)
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if check_features:
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# dk.find_features(dataframe)
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self.dd.load_metadata(dk)
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# self.check_if_feature_list_matches_strategy(dk)
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dataframe_dummy_features = self.dk.use_strategy_to_populate_indicators(
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strategy, prediction_dataframe=dataframe.tail(1), pair=metadata["pair"]
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)
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dk.find_features(dataframe_dummy_features)
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self.check_if_feature_list_matches_strategy(dk)
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check_features = False
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append_df = dk.get_backtesting_prediction()
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append_df = dk.get_backtesting_prediction()
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dk.append_predictions(append_df)
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dk.append_predictions(append_df)
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else:
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else:
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