bring back auto DF resizing for okx
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@ -279,15 +279,15 @@ class FreqaiDataDrawer:
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# own return array in the same shape, we need to figure out how the size has changed
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# and adapt our stored/returned info accordingly.
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# length_difference = len(self.model_return_values[pair]) - len_df
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# i = 0
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length_difference = len(self.model_return_values[pair]) - len_df
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i = 0
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# if length_difference == 0:
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# i = 1
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# elif length_difference > 0:
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# i = length_difference + 1
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if length_difference == 0:
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i = 1
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elif length_difference > 0:
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i = length_difference + 1
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df = self.model_return_values[pair] = self.model_return_values[pair].shift(-1)
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df = self.model_return_values[pair] = self.model_return_values[pair].shift(-i)
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if pair in self.historic_predictions:
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hp_df = self.historic_predictions[pair]
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@ -320,11 +320,11 @@ class FreqaiDataDrawer:
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for key in df.keys():
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self.historic_predictions[pair][key].iloc[-1] = df[key].iloc[-1]
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# if length_difference < 0:
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# prepend_df = pd.DataFrame(
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# np.zeros((abs(length_difference) - 1, len(df.columns))), columns=df.columns
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# )
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# df = pd.concat([prepend_df, df], axis=0)
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if length_difference < 0:
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prepend_df = pd.DataFrame(
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np.zeros((abs(length_difference) - 1, len(df.columns))), columns=df.columns
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)
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df = pd.concat([prepend_df, df], axis=0)
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def attach_return_values_to_return_dataframe(
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self, pair: str, dataframe: DataFrame) -> DataFrame:
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@ -355,7 +355,6 @@ class FreqaiDataDrawer:
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dataframe[f"{label}_mean"] = 0
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dataframe[f"{label}_std"] = 0
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# dataframe['prediction'] = 0
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dataframe["do_predict"] = 0
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if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
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