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Merge branch 'develop' into backtest_live_models

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This commit is contained in:
Wagner Costa Santos
2022-10-10 14:53:45 -03:00
parent 6845a5c6ea 002a46c5a0
commit 3081e73f8a
93 changed files with 1575 additions and 616 deletions
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39
freqtrade/freqai/freqai_interface.py
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@@ -215,7 +215,8 @@ class IFreqaiModel(ABC):
new_trained_timerange, pair, strategy, dk, data_load_timerange
)
except Exception as msg:
logger.warning(f'Training {pair} raised exception {msg}, skipping.')
logger.warning(f"Training {pair} raised exception {msg.__class__.__name__}. "
f"Message: {msg}, skipping.")
self.train_timer('stop')
@@ -297,7 +298,8 @@ class IFreqaiModel(ABC):
if dk.check_if_backtest_prediction_exists():
self.dd.load_metadata(dk)
self.check_if_feature_list_matches_strategy(dataframe_train, dk)
dk.find_features(dataframe_train)
self.check_if_feature_list_matches_strategy(dk)
append_df = dk.get_backtesting_prediction()
dk.append_predictions(append_df)
else:
@@ -318,7 +320,6 @@ class IFreqaiModel(ABC):
else:
self.model = self.dd.load_data(pair, dk)
# self.check_if_feature_list_matches_strategy(dataframe_train, dk)
pred_df, do_preds = self.predict(dataframe_backtest, dk)
append_df = dk.get_predictions_to_append(pred_df, do_preds)
dk.append_predictions(append_df)
@@ -415,7 +416,7 @@ class IFreqaiModel(ABC):
# allows FreqUI to show full return values.
pred_df, do_preds = self.predict(dataframe, dk)
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)
dk.return_dataframe = self.dd.attach_return_values_to_return_dataframe(pair, dataframe)
@@ -436,13 +437,13 @@ class IFreqaiModel(ABC):
if self.freqai_info.get('fit_live_predictions_candles', 0) and self.live:
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)
return
def check_if_feature_list_matches_strategy(
self, dataframe: DataFrame, dk: FreqaiDataKitchen
self, dk: FreqaiDataKitchen
) -> None:
"""
Ensure user is passing the proper feature set if they are reusing an `identifier` pointing
@@ -451,11 +452,12 @@ class IFreqaiModel(ABC):
:param dk: FreqaiDataKitchen = non-persistent data container/analyzer for
current coin/bot loop
"""
dk.find_features(dataframe)
if "training_features_list_raw" in dk.data:
feature_list = dk.data["training_features_list_raw"]
else:
feature_list = dk.data['training_features_list']
if dk.training_features_list != feature_list:
raise OperationalException(
"Trying to access pretrained model with `identifier` "
@@ -503,13 +505,16 @@ class IFreqaiModel(ABC):
if self.freqai_info["feature_parameters"].get('noise_standard_deviation', 0):
dk.add_noise_to_training_features()
def data_cleaning_predict(self, dk: FreqaiDataKitchen, dataframe: DataFrame) -> None:
def data_cleaning_predict(self, dk: FreqaiDataKitchen) -> None:
"""
Base data cleaning method for predict.
Functions here are complementary to the functions of data_cleaning_train.
"""
ft_params = self.freqai_info["feature_parameters"]
# ensure user is feeding the correct indicators to the model
self.check_if_feature_list_matches_strategy(dk)
if ft_params.get('inlier_metric_window', 0):
dk.compute_inlier_metric(set_='predict')
@@ -527,9 +532,6 @@ class IFreqaiModel(ABC):
if ft_params.get("use_DBSCAN_to_remove_outliers", False):
dk.use_DBSCAN_to_remove_outliers(predict=True)
# ensure user is feeding the correct indicators to the model
self.check_if_feature_list_matches_strategy(dk.data_dictionary['prediction_features'], dk)
def model_exists(self, dk: FreqaiDataKitchen) -> bool:
"""
Given a pair and path, check if a model already exists
@@ -604,7 +606,7 @@ class IFreqaiModel(ABC):
self.dd.purge_old_models()
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:
"""
This function is called only if the datadrawer failed to load an
@@ -623,11 +625,11 @@ class IFreqaiModel(ABC):
If the user reuses an identifier on a subsequent instance,
this function will not be called. In that case, "real" predictions
will be appended to the loaded set of historic predictions.
:param: df: DataFrame = the dataframe containing the training feature data
:param: model: Any = A model which was `fit` using a common library such as
catboost or lightgbm
:param: dk: FreqaiDataKitchen = object containing methods for data analysis
:param: pair: str = current pair
:param df: DataFrame = the dataframe containing the training feature data
:param model: Any = A model which was `fit` using a common library such as
catboost or lightgbm
:param dk: FreqaiDataKitchen = object containing methods for data analysis
:param pair: str = current pair
"""
self.dd.historic_predictions[pair] = pred_df
@@ -647,6 +649,9 @@ class IFreqaiModel(ABC):
for return_str in dk.data['extra_returns_per_train']:
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
# # viewing is correct in frequi
if self.freqai_info.get('keras', False) or self.ft_params.get('inlier_metric_window', 0):