logging bug fix

selfrank/algos/iterative.py

@@ -89,8 +89,8 @@ class SelfRank:
 
             # termination if reputation score converges
             delta = np.sum(np.abs(r - r_k))
-            logging.info(f"Iteration {iter}:{delta}")
-            logging.info(f"Reputation score: {r}")
+            logger.debug(f"Iteration {iter}:{delta}")
+            logger.debug(f"Reputation score: {r}")
             if delta<= tol:
                 break
             else:
@@ -101,10 +101,10 @@ class SelfRank:
         idx = np.argsort(r_k)[::-1]
         self.ranking = np.array(self.MODELS)[idx].tolist()
 
-        logger.info(f"Estimated ranks (best to worst): {self.ranking}")
+        logger.debug(f"Estimated ranks (best to worst): {self.ranking}")
         if self.true_ranking is not None:
-            logger.info(f"True ranking: {self.true_ranking}")
-            logger.info(f"RBO measure: {self.measure()}")
+            logger.debug(f"True ranking: {self.true_ranking}")
+            logger.debug(f"RBO measure: {self.measure()}")
         return self.ranking # Best to worst
 
     def measure(self, metric='rbo', k=5, p=0.95) -> float:

selfrank/algos/triplet.py

@@ -172,13 +172,13 @@ def rouge(a: str, b: str, c:str, df: pd.DataFrame) -> float:
     b_wins = sum(outcomes==0)
 
     if a_wins == b_wins:
-        logger.info(f"Judge: {c}, {bcolors.PURPLE}{bcolors.BOLD}Model {a}: {a_wins}, Model {b}: {b_wins} {bcolors.ENDC} (of {len(df)}).")
+        logger.debug(f"Judge: {c}, {bcolors.PURPLE}{bcolors.BOLD}Model {a}: {a_wins}, Model {b}: {b_wins} {bcolors.ENDC} (of {len(df)}).")
         return 0.5 # tied overall
     elif a_wins > b_wins:
-        logger.info(f"Judge: {c}, {bcolors.RED}{bcolors.BOLD}Model {a}: {a_wins}{bcolors.ENDC}, Model {b}: {b_wins} (of {len(df)}).")
+        logger.debug(f"Judge: {c}, {bcolors.RED}{bcolors.BOLD}Model {a}: {a_wins}{bcolors.ENDC}, Model {b}: {b_wins} (of {len(df)}).")
         return 1 # a wins overall
     else:
-        logger.info(f"Judge: {c}, Model {a}: {a_wins}, {bcolors.RED}{bcolors.BOLD}Model {b}: {b_wins}{bcolors.ENDC} (of {len(df)}).")
+        logger.debug(f"Judge: {c}, Model {a}: {a_wins}, {bcolors.RED}{bcolors.BOLD}Model {b}: {b_wins}{bcolors.ENDC} (of {len(df)}).")
         return 0 # b wins