precision and recall is inverted

matching_series.py

@@ -190,8 +190,8 @@ class matching_series(evaluate.Metric):
         f1_mse = 2 / (1 / precision_mse + 1 / recall_mse)
 
         # matching precision, recall and f1
-        matching_precision = np.unique(best_match).size / len(best_match_inv)
-        matching_recall = np.unique(best_match_inv).size / len(best_match)
+        matching_recall = np.unique(best_match).size / len(best_match_inv)
+        matching_precision = np.unique(best_match_inv).size / len(best_match)
         matching_f1 = 2 / (1 / matching_precision + 1 / matching_recall)
 
         # take matching for each feature and compute metrics for them