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ensure raw features match when PCA is employed

This commit is contained in:
robcaulk 2022-10-01 13:14:59 +02:00
parent cdc01a0781
commit f2b875483f
2 changed files with 5 additions and 12 deletions
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4
freqtrade/freqai/data_kitchen.py
View File

@ -1,6 +1,5 @@
import copy
import logging
import re
import shutil
from datetime import datetime, timezone
from math import cos, sin
@ -882,9 +881,6 @@ class FreqaiDataKitchen:
"""
column_names = dataframe.columns
features = [c for c in column_names if "%" in c]
pca_features = [c for c in column_names if re.search(r"^PC\d+$", c)]
if not features and pca_features:
features = pca_features
if not features:
raise OperationalException("Could not find any features!")

13
freqtrade/freqai/freqai_interface.py
View File

@ -275,7 +275,8 @@ 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:
@ -296,7 +297,6 @@ 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)
@ -420,7 +420,7 @@ class IFreqaiModel(ABC):
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
@ -429,15 +429,12 @@ 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 self.ft_params.get('principal_component_analysis', False):
feature_list = dk.data['training_features_list']
if dk.training_features_list != feature_list:
raise OperationalException(
"Trying to access pretrained model with `identifier` "
@ -510,7 +507,7 @@ class IFreqaiModel(ABC):
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)
self.check_if_feature_list_matches_strategy(dk)
def model_exists(self, dk: FreqaiDataKitchen) -> bool:
"""