fix backtesting bug, undo move of label stat calc, fix example strat exit logic

freqtrade/freqai/data_kitchen.py

@@ -635,20 +635,20 @@ class FreqaiDataKitchen:
         Append backtest prediction from current backtest period to all previous periods
         """
 
-        self.append_df = DataFrame()
+        append_df = DataFrame()
         for label in self.label_list:
-            self.append_df[label] = predictions[label]
-            self.append_df[f"{label}_mean"] = self.data["labels_mean"][label]
-            self.append_df[f"{label}_std"] = self.data["labels_std"][label]
+            append_df[label] = predictions[label]
+            append_df[f"{label}_mean"] = self.data["labels_mean"][label]
+            append_df[f"{label}_std"] = self.data["labels_std"][label]
 
-        self.append_df["do_predict"] = do_predict
+        append_df["do_predict"] = do_predict
         if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0:
-            self.append_df["DI_values"] = self.DI_values
+            append_df["DI_values"] = self.DI_values
 
         if self.full_df.empty:
-            self.full_df = self.append_df
+            self.full_df = append_df
         else:
-            self.full_df = pd.concat([self.full_df, self.append_df], axis=0)
+            self.full_df = pd.concat([self.full_df, append_df], axis=0)
 
         return
 
@@ -668,7 +668,7 @@ class FreqaiDataKitchen:
         to_keep = [col for col in dataframe.columns if not col.startswith("&")]
         self.return_dataframe = pd.concat([dataframe[to_keep], self.full_df], axis=1)
 
-        self.append_df = DataFrame()
+        # self.append_df = DataFrame()
         self.full_df = DataFrame()
 
         return

freqtrade/freqai/freqai_interface.py

@@ -1,7 +1,6 @@
 # import contextlib
 import copy
 import datetime
-import gc
 import logging
 import shutil
 import threading
@@ -183,8 +182,6 @@ class IFreqaiModel(ABC):
             (_, _, _) = self.dd.get_pair_dict_info(metadata["pair"])
             train_it += 1
             total_trains = len(dk.backtesting_timeranges)
-            gc.collect()
-            dk.data = {}  # clean the pair specific data between training window sliding
             self.training_timerange = tr_train
             dataframe_train = dk.slice_dataframe(tr_train, dataframe)
             dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe)

freqtrade/freqai/prediction_models/BaseRegressionModel.py

@@ -56,6 +56,8 @@ class BaseRegressionModel(IFreqaiModel):
                     f"{end_date}--------------------")
         # split data into train/test data.
         data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
+        if not self.freqai_info.get('fit_live_predictions', 0) or not self.live:
+            dk.fit_labels()
         # normalize all data based on train_dataset only
         data_dictionary = dk.normalize_data(data_dictionary)
 
@@ -75,8 +77,6 @@ class BaseRegressionModel(IFreqaiModel):
 
         if self.freqai_info.get('fit_live_predictions_candles', 0) and self.live:
             self.fit_live_predictions(dk)
-        else:
-            dk.fit_labels()
 
         self.dd.save_historic_predictions_to_disk()
 

freqtrade/templates/FreqaiExampleStrategy.py

@@ -235,7 +235,7 @@ class FreqaiExampleStrategy(IStrategy):
 
         if (
             "prediction" + entry_tag not in pair_dict[pair]
-            or pair_dict[pair]["prediction" + entry_tag] > 0
+            or pair_dict[pair]["prediction" + entry_tag] == 0
         ):
             with self.freqai.lock:
                 pair_dict[pair]["prediction" + entry_tag] = abs(trade_candle["&-s_close"])