make logentries same length before computing linecontent-scores. Remove jaccard

logmetric.py

@@ -167,10 +167,7 @@ class LogMetric(evaluate.Metric):
         preds_split = [p.split() for p in pred_logMessages]
         refs_split = [r.split() for r in ref_logMessages]
 
-        # compute jaccard pair-wise, then take mean of all results
-        mean_jaccard_score = np.mean([self.get_jaccard_similarity(set(p_split), set(r_split)) for p_split, r_split in zip(preds_split,refs_split)])
-        
-        return sacrebleu_score, mean_jaccard_score, smape_length_score
+        return sacrebleu_score, smape_length_score
     
     # get different scores regarding the timestamp
     def getTimestampsScore(self, pred_timestamps, ref_timestamps):
@@ -249,15 +246,13 @@ class LogMetric(evaluate.Metric):
             ref_timestamps.append(ref_split_log[i])
             ref_logMessages.append(ref_split_log[i+1])
 
-        # We cut off the longer list, since we only want to compute the content-scores for actually predicted lines
-        # -> hence, the content score can be good, even if the amount of predicted lines are wrong
+        # We extend the shorter list to the length of the longer one
         min_logentries = min(len(pred_logMessages), len(ref_logMessages))
-        # print("min_logentries:", min_logentries)
-        pred_logMessages = pred_logMessages[:min_logentries]
-        ref_logMessages = ref_logMessages[:min_logentries]
+        pred_logMessages += (len(pred_logMessages) - min_logentries) * [""]
+        ref_logMessages += (len(ref_logMessages) - min_logentries) * [""]
 
 
-        linecontent_sacrebleu, linecontent_jaccard, linecontentlength_difference_SMAPE = self.getLineContentScore(pred_logMessages, ref_logMessages)
+        linecontent_sacrebleu, linecontentlength_difference_SMAPE = self.getLineContentScore(pred_logMessages, ref_logMessages)
         
         timestamps_difference_SMAPE, timestamps_formatConsistency_absolute, timestamps_monotinicity_absolute = self.getTimestampsScore(pred_timestamps, ref_timestamps)
 
@@ -269,7 +264,6 @@ class LogMetric(evaluate.Metric):
         return {"linecount_difference_SMAPE_score": linecount_difference_SMAPE,
                 "linecontentlength_difference_SMAPE_score": linecontentlength_difference_SMAPE,
                 "linecontent_sacrebleu_score": linecontent_sacrebleu,
-                "linecontent_jaccard_score": linecontent_jaccard,
                 "timestamps_SMAPE_difference_score": timestamps_difference_SMAPE,
                 "timestamps_formatConsistency_score": timestamps_formatConsistency_absolute,
                 "timestamps_monotinicity_score": timestamps_monotinicity_absolute