new_contents: #!/usr/bin/env python
  # encoding: utf-8
  
  # The MIT License (MIT)
  
  # Copyright (c) 2014 Hervé BREDIN
  
  # Permission is hereby granted, free of charge, to any person obtaining a copy
  # of this software and associated documentation files (the "Software"), to deal
  # in the Software without restriction, including without limitation the rights
  # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  # copies of the Software, and to permit persons to whom the Software is
  # furnished to do so, subject to the following conditions:
  
  # The above copyright notice and this permission notice shall be included in
  # all copies or substantial portions of the Software.
  
  # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  # SOFTWARE.
  
  
  from sklearn.metrics import homogeneity_score, completeness_score
  
  
  def homogeneity(reference, hypothesis, images):
      """
      >>> reference = Clustering.load('reference.txt')
      >>> hypothesis = Clustering.load('hypothesis.txt')
      >>> images =  # list of images to evaluate
      >>> homogeneity(reference, hypothesis, images)
      """
      return homogeneity_score(
          reference.to_list(images),
          hypothesis.to_list(images)
      )
  
  def completeness(reference, hypothesis, images):
      return completeness_score(
          reference.to_list(images),
          hypothesis.to_list(images)
      )
  
subject: add homogeneity (purity) and completeness (coverage)