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add close price and date to historic_predictions

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This commit is contained in:
robcaulk 2022-10-02 18:33:39 +02:00
parent e686faf1bc
commit b70f18f4c3
2 changed files with 11 additions and 4 deletions
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6
freqtrade/freqai/data_drawer.py
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@ -257,7 +257,7 @@ class FreqaiDataDrawer:
def append_model_predictions(self, pair: str, predictions: DataFrame, def append_model_predictions(self, pair: str, predictions: DataFrame,
do_preds: NDArray[np.int_], do_preds: NDArray[np.int_],
dk: FreqaiDataKitchen, len_df: int) -> None: dk: FreqaiDataKitchen, strat_df: DataFrame) -> None:
""" """
Append model predictions to historic predictions dataframe, then set the Append model predictions to historic predictions dataframe, then set the
strategy return dataframe to the tail of the historic predictions. The length of strategy return dataframe to the tail of the historic predictions. The length of
@ -266,6 +266,7 @@ class FreqaiDataDrawer:
historic predictions. historic predictions.
""" """
len_df = len(strat_df)
index = self.historic_predictions[pair].index[-1:] index = self.historic_predictions[pair].index[-1:]
columns = self.historic_predictions[pair].columns columns = self.historic_predictions[pair].columns
@ -293,6 +294,9 @@ class FreqaiDataDrawer:
for return_str in rets: for return_str in rets:
df[return_str].iloc[-1] = rets[return_str] df[return_str].iloc[-1] = rets[return_str]
df['close_price'].iloc[-1] = strat_df['close'].iloc[-1]
df['date_pred'].iloc[-1] = strat_df['date'].iloc[-1]
self.model_return_values[pair] = df.tail(len_df).reset_index(drop=True) self.model_return_values[pair] = df.tail(len_df).reset_index(drop=True)
def attach_return_values_to_return_dataframe( def attach_return_values_to_return_dataframe(

9
freqtrade/freqai/freqai_interface.py
View File

@ -393,7 +393,7 @@ class IFreqaiModel(ABC):
# allows FreqUI to show full return values. # allows FreqUI to show full return values.
pred_df, do_preds = self.predict(dataframe, dk) pred_df, do_preds = self.predict(dataframe, dk)
if pair not in self.dd.historic_predictions: if pair not in self.dd.historic_predictions:
self.set_initial_historic_predictions(pred_df, dk, pair) self.set_initial_historic_predictions(pred_df, dk, pair, dataframe)
self.dd.set_initial_return_values(pair, pred_df) self.dd.set_initial_return_values(pair, pred_df)
dk.return_dataframe = self.dd.attach_return_values_to_return_dataframe(pair, dataframe) dk.return_dataframe = self.dd.attach_return_values_to_return_dataframe(pair, dataframe)
@ -414,7 +414,7 @@ class IFreqaiModel(ABC):
if self.freqai_info.get('fit_live_predictions_candles', 0) and self.live: if self.freqai_info.get('fit_live_predictions_candles', 0) and self.live:
self.fit_live_predictions(dk, pair) self.fit_live_predictions(dk, pair)
self.dd.append_model_predictions(pair, pred_df, do_preds, dk, len(dataframe)) self.dd.append_model_predictions(pair, pred_df, do_preds, dk, dataframe)
dk.return_dataframe = self.dd.attach_return_values_to_return_dataframe(pair, dataframe) dk.return_dataframe = self.dd.attach_return_values_to_return_dataframe(pair, dataframe)
return return
@ -583,7 +583,7 @@ class IFreqaiModel(ABC):
self.dd.purge_old_models() self.dd.purge_old_models()
def set_initial_historic_predictions( def set_initial_historic_predictions(
self, pred_df: DataFrame, dk: FreqaiDataKitchen, pair: str self, pred_df: DataFrame, dk: FreqaiDataKitchen, pair: str, strat_df: DataFrame
) -> None: ) -> None:
""" """
This function is called only if the datadrawer failed to load an This function is called only if the datadrawer failed to load an
@ -626,6 +626,9 @@ class IFreqaiModel(ABC):
for return_str in dk.data['extra_returns_per_train']: for return_str in dk.data['extra_returns_per_train']:
hist_preds_df[return_str] = 0 hist_preds_df[return_str] = 0
hist_preds_df['close_price'] = strat_df['close']
hist_preds_df['date_pred'] = strat_df['date']
# # for keras type models, the conv_window needs to be prepended so # # for keras type models, the conv_window needs to be prepended so
# # viewing is correct in frequi # # viewing is correct in frequi
if self.freqai_info.get('keras', False) or self.ft_params.get('inlier_metric_window', 0): if self.freqai_info.get('keras', False) or self.ft_params.get('inlier_metric_window', 0):