old_contents: 
  """
  Find out which experts exist in the DBLP dataset and how many abstracts 
  they have. 
  """
  import logging 
  import sys 
  import itertools 
  import numpy 
  from exp.influence2.ArnetMinerDataset import ArnetMinerDataset
  
  logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
  
  dataset = ArnetMinerDataset() 
  #dataset.dataFilename = dataset.dataDir + "DBLP-citation-100000.txt" 
  
  authorList, documentList, citationList = dataset.readAuthorsAndDocuments()
  
  authorSet = set(itertools.chain.from_iterable(authorList))
  
  print("Found all authors")
  expertMatchesDict = {} 
  
  for field in dataset.fields: 
      expertMatchesDict[field] = 0    
      
      for expert in dataset.expertsDict[field]: 
          if expert in authorSet: 
              expertMatchesDict[field] += 1
      
      expertMatchesDict[field] /= float(len(dataset.expertsDict[field]))
  
  print(expertMatchesDict)
  
  
new_contents: 
  """
  Find out which experts exist in the DBLP dataset and how many abstracts 
  they have. 
  """
  import logging 
  import sys 
  import itertools 
  import numpy 
  from exp.influence2.ArnetMinerDataset import ArnetMinerDataset
  
  logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
  
  dataset = ArnetMinerDataset() 
  #dataset.dataFilename = dataset.dataDir + "DBLP-citation-100000.txt" 
  
  authorList, documentList, citationList = dataset.readAuthorsAndDocuments()
  authorSet = set(itertools.chain.from_iterable(authorList))
  
  print("Found all authors")
  expertMatchesDict = {} 
  
  for field in dataset.fields: 
      expertMatchesDict[field] = 0    
      
      for expert in dataset.expertsDict[field]: 
          if expert in authorSet: 
              expertMatchesDict[field] += 1
      
      expertMatchesDict[field] /= float(len(dataset.expertsDict[field]))
  
  print(expertMatchesDict)
  print(numpy.mean(expertMatchesDict.values())) 
  
  
subject: Print mean max coverage