updated function cluster to only have one function per cluster, remov…

…ed extra tab in output

Workflows/Representative_function/Cluster_Representative_Function.py

@@ -271,6 +271,25 @@ def min_max_scale(self,X, minX, maxX):
 
 
 
+ def get_most_significant_function(self,functions_list):
+ functions_score={}
+ for temp_string in functions_list:
+ functions_score[temp_string]=0
+ tokens_lists,putative_ids = self.unifunc.pre_process_string(temp_string)
+ if putative_ids: functions_score[temp_string]+=self.unifunc.default_word_count
+ n_tokens = sum([len(i) for i in tokens_lists])
+ if tokens_lists:
+ vector_list = self.process_string_nlp(tokens_lists)
+ for vector in vector_list:
+ if self.unifunc.wordnet_tagger.placeholder.lower() in vector: vector.remove(self.unifunc.wordnet_tagger.placeholder.lower())
+ tf_idf_dict = self.unifunc.calculate_tf_idf(vector)
+ current_score=sum(tf_idf_dict.values())
+ functions_score[temp_string]+=current_score
+ if n_tokens:
+ functions_score[temp_string]/=n_tokens
+ return [max(functions_score,key=functions_score.get)]
+
+
  def get_representative_function(self):
  annotations_scores_generator=self.compare_annotations()
  with open(self.OUTPUT_FUNC_CLUSTER,'w+') as outfile:
@@ -284,11 +303,14 @@ def get_representative_function(self):
  score=l[0]
  annotations=l[1]
  line=[cluster_id,score]
+ if len(annotations)>1:
+ annotations=self.get_most_significant_function(annotations)
  line.extend(annotations)
- line.append('\n')
- line='\t'.join(line)
+ line='\t'.join(line)+'\n'
+
  outfile.write(line)
  if not temp:
  if self.output_without_representative:
  line=f'{cluster_id}\n'
  outfile.write(line)
+