Update app.py

app.py

@@ -73,15 +73,16 @@ def aggregate(list_of_hits):
         preferences.append([doc["rank"] - 1 for doc in result])
 
     preferences = np.array(preferences)
-    # y_optimal = KemenyOptimalAggregator().aggregate(preferences)
-    y_optimal = BordaRankAggregator().aggregate(preferences)
+    y_optimal = KemenyOptimalAggregator().aggregate(preferences)
+    # y_optimal = BordaRankAggregator().aggregate(preferences)
 
     rank2doc = {}
     for doc in list_of_hits[0]:
         rank2doc[doc["rank"] - 1] = doc
 
-    print("preferences: ", preferences.shape, preferences[0])
-    print("rank2doc:", rank2doc.keys())
+    print("preference:")
+    print(preferences)
+    print("preferences shape: ", preferences.shape)
     print("y_optimal: ", y_optimal)
     return [rank2doc[rank] for rank in y_optimal]