old_contents: from pygraphc.misc.LKE import *
  from pygraphc.evaluation.ExternalEvaluation import *
  
  # set input and output path
  ip_address = '161.166.232.17'
  standard_path = '/home/hudan/Git/labeled-authlog/dataset/Hofstede2014/dataset1/' + ip_address
  standard_file = standard_path + 'auth.log.anon.labeled'
  analyzed_file = 'auth.log.anon'
  prediction_file = 'lke-result-' + ip_address + '.txt'
  OutputPath = './results'
  para = Para(path=standard_path, logname=analyzed_file, save_path=OutputPath)
  
  # run LKE method
  myparser = LKE(para)
  time = myparser.main_process()
  clusters = myparser.get_clusters()
  original_logs = myparser.logs
  
  # perform evaluation
  ExternalEvaluation.set_cluster_label_id(None, clusters, original_logs, prediction_file)
  homogeneity_completeness_vmeasure = ExternalEvaluation.get_homogeneity_completeness_vmeasure(standard_file,
                                                                                               prediction_file)
  # print evaluation result
  print homogeneity_completeness_vmeasure
  print ('The running time of LKE is', time)
  
new_contents: from pygraphc.misc.LKE import *
  from pygraphc.evaluation.ExternalEvaluation import *
  
  # set input and output path
  dataset_path = '/home/hudan/Git/labeled-authlog/dataset/Hofstede2014/dataset1_perday/'
  groundtruth_file = dataset_path + 'Dec 1.log.labeled'
  analyzed_file = 'Dec 1.log'
  OutputPath = '/home/hudan/Git/pygraphc/result/misc/'
  prediction_file = OutputPath + 'Dec 1.log.perline'
  para = Para(path=dataset_path, logname=analyzed_file, save_path=OutputPath)
  
  # run LKE method
  myparser = LKE(para)
  time = myparser.main_process()
  clusters = myparser.get_clusters()
  original_logs = myparser.logs
  
  # perform evaluation
  ExternalEvaluation.set_cluster_label_id(None, clusters, original_logs, prediction_file)
  
  # get evaluation of clustering performance
  ar = ExternalEvaluation.get_adjusted_rand(groundtruth_file, prediction_file)
  ami = ExternalEvaluation.get_adjusted_mutual_info(groundtruth_file, prediction_file)
  nmi = ExternalEvaluation.get_normalized_mutual_info(groundtruth_file, prediction_file)
  h = ExternalEvaluation.get_homogeneity(groundtruth_file, prediction_file)
  c = ExternalEvaluation.get_completeness(groundtruth_file, prediction_file)
  v = ExternalEvaluation.get_vmeasure(groundtruth_file, prediction_file)
  
  # print evaluation result
  print ar, ami, nmi, h, c, v
  print ('The running time of LKE is', time)
  
subject: Edit path and external evaluation