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archive config to the model folder, filter out features before returning dataframe to strategy (to alleviate frequi issues)`

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This commit is contained in:
robcaulk 2022-06-26 23:03:48 +02:00
parent 051b99791d
commit 68bafa9517
1 changed files with 14 additions and 1 deletions
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15
freqtrade/freqai/freqai_interface.py
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@ -2,7 +2,7 @@
import datetime
import gc
import logging
# import sys
import shutil
import threading
from abc import ABC, abstractmethod
from pathlib import Path
@ -109,6 +109,7 @@ class IFreqaiModel(ABC):
logger.info(f'Training {len(self.dh.training_timeranges)} timeranges')
dh = self.start_backtesting(dataframe, metadata, self.dh)
dataframe = self.remove_features_from_df(dataframe)
return self.return_values(dataframe, dh)
@threaded
@ -413,6 +414,18 @@ class IFreqaiModel(ABC):
self.full_path = Path(self.config['user_data_dir'] /
"models" /
str(self.freqai_info.get('identifier')))
self.full_path.mkdir(parents=True, exist_ok=True)
shutil.copy(self.config['config_files'][0], Path(self.full_path,
self.config['config_files'][0]))
def remove_features_from_df(self, dataframe: DataFrame) -> DataFrame:
"""
Remove the features from the dataframe before returning it to strategy. This keeps it
compact for Frequi purposes.
"""
to_keep = [col for col in dataframe.columns
if not col.startswith('%') or col.startswith('%%')]
return dataframe[to_keep]
@threaded
def retrain_model_on_separate_thread(self, new_trained_timerange: TimeRange, pair: str,