add tests for outlier detection and removal functions

freqtrade/freqai/data_drawer.py

@@ -566,7 +566,7 @@ class FreqaiDataDrawer:
         for training according to user defined train_period_days
         metadata: dict = strategy furnished pair metadata
         """
-
+        import pytest 
         with self.history_lock:
             corr_dataframes: Dict[Any, Any] = {}
             base_dataframes: Dict[Any, Any] = {}
@@ -576,6 +576,7 @@ class FreqaiDataDrawer:
             )
 
             for tf in self.freqai_info["feature_parameters"].get("include_timeframes"):
+                # pytest.set_trace()
                 base_dataframes[tf] = dk.slice_dataframe(timerange, historic_data[pair][tf])
                 if pairs:
                     for p in pairs:

freqtrade/freqai/data_kitchen.py

@@ -657,7 +657,7 @@ class FreqaiDataKitchen:
                 return (x, y)
 
             MinPts = int(len(self.data_dictionary['train_features'].index) * 0.25)
-            # measure pairwise distances to train_features.shape[1]*2 nearest neighbours
+            # measure pairwise distances to nearest neighbours
             neighbors = NearestNeighbors(
                 n_neighbors=MinPts, n_jobs=self.thread_count)
             neighbors_fit = neighbors.fit(self.data_dictionary['train_features'])