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create more flexible whitelist, avoid duplicating whitelist features into corr_pairlist, update docs

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This commit is contained in:
robcaulk
2022-05-09 17:01:49 +02:00
parent 22bd5556ed
commit 9b3e5faebe
6 changed files with 119 additions and 39 deletions
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7
freqtrade/templates/ExamplePredictionModel.py
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@@ -53,7 +53,7 @@ class ExamplePredictionModel(IFreqaiModel):
logger.info("--------------------Starting training--------------------")
# create the full feature list based on user config info
self.dh.training_features_list = self.dh.build_feature_list(self.config)
self.dh.training_features_list = self.dh.build_feature_list(self.config, metadata)
unfiltered_labels = self.make_labels(unfiltered_dataframe)
# filter the features requested by user in the configuration file and elegantly handle NaNs
@@ -114,7 +114,8 @@ class ExamplePredictionModel(IFreqaiModel):
return model
def predict(self, unfiltered_dataframe: DataFrame) -> Tuple[DataFrame, DataFrame]:
def predict(self, unfiltered_dataframe: DataFrame, metadata: dict) -> Tuple[DataFrame,
DataFrame]:
"""
Filter the prediction features data and predict with it.
:param: unfiltered_dataframe: Full dataframe for the current backtest period.
@@ -126,7 +127,7 @@ class ExamplePredictionModel(IFreqaiModel):
# logger.info("--------------------Starting prediction--------------------")
original_feature_list = self.dh.build_feature_list(self.config)
original_feature_list = self.dh.build_feature_list(self.config, metadata)
filtered_dataframe, _ = self.dh.filter_features(
unfiltered_dataframe, original_feature_list, training_filter=False
)

5
freqtrade/templates/FreqaiExampleStrategy.py
View File

@@ -142,8 +142,11 @@ class FreqaiExampleStrategy(IStrategy):
# the following loops are necessary for building the features
# indicated by the user in the configuration file.
for tf in self.freqai_info["timeframes"]:
# dataframe = self.populate_any_indicators(metadata["pair"], dataframe.copy(), tf)
dataframe = self.populate_any_indicators(self.pair, dataframe.copy(), tf,
coin=self.pair.split("/")[0] + "-")
for pair in self.freqai_info["corr_pairlist"]:
if metadata['pair'] in pair:
continue # do not include whitelisted pair twice if it is in corr_pairlist
dataframe = self.populate_any_indicators(
pair, dataframe.copy(), tf, coin=pair.split("/")[0] + "-"
)