Change order smaller hopkins are better and add __repr__ method to ApplyW

justclust/analysis/bolzano.py

@@ -40,7 +40,7 @@ else:
 
 print("=" * 50)
 print(f"BEST PRE-PROCESSING (10/{len(pre_scores)}):")
-print(pre_scores.sort_values("hopkins", ascending=False).loc[:10, :])
+print(pre_scores.sort_values("hopkins", ascending=True).loc[:10, :])
 print("-" * 50)
 print("Hopkins statistics of main pre-processing options")
 print(pre_scores["hopkins"].describe())

justclust/explore/preprocs.py

@@ -12,10 +12,6 @@ from justclust.hopkins import hopkins
 # from pathlib import Path
 
 
-
-
-
-
 class ApplyW:
     def __init__(self, weights):
         self.weights = weights
@@ -23,6 +19,9 @@ class ApplyW:
     def fit_transform(self, X, *args, **kwargs):
         return X * self.weights
 
+    def __repr__(self):
+        return f"ApplyW(weights={self.weights!r})"
+
 
 def get_preprocs(selected=None, apply_weight=None):
     scalers = [
@@ -196,6 +195,6 @@ def explore_preprocs(
     )
 
     scores = pd.DataFrame.from_records(res)
-    scores.sort_values("hopkins", ascending=False, inplace=True)
+    scores.sort_values("hopkins", ascending=True, inplace=True)
 
     return scores