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ensure labels are properly defined in backtesting
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@ -334,6 +334,7 @@ class IFreqaiModel(ABC):
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dataframe_train = dk.remove_special_chars_from_feature_names(dataframe_train)
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dataframe_backtest = dk.remove_special_chars_from_feature_names(dataframe_backtest)
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dk.get_unique_classes_from_labels(dataframe_train)
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if not self.model_exists(dk):
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dk.find_features(dataframe_train)
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@ -241,7 +241,6 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog)
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freqai = strategy.freqai
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freqai.live = False
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freqai.dk = FreqaiDataKitchen(freqai_conf)
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freqai.dk.live = True
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timerange = TimeRange.parse_timerange("20180110-20180130")
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freqai.dd.load_all_pair_histories(timerange, freqai.dk)
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sub_timerange = TimeRange.parse_timerange("20180110-20180130")
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@ -375,6 +374,9 @@ def test_backtesting_fit_live_predictions(mocker, freqai_conf, caplog):
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sub_timerange = TimeRange.parse_timerange("20180129-20180130")
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corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
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df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
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df = strategy.set_freqai_targets(df.copy(), metadata={"pair": "LTC/BTC"})
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df = freqai.dk.remove_special_chars_from_feature_names(df)
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freqai.dk.get_unique_classes_from_labels(df)
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freqai.dk.pair = "ADA/BTC"
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freqai.dk.full_df = df.fillna(0)
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freqai.dk.full_df
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