new_contents: from milk.supervised.classifier import normaliselabels
  import numpy as np
  
  def test_normaliselabels():
      np.random.seed(22)
      labels = np.zeros(120, np.uint8)
      labels[40:] += 1
      labels[65:] += 1
      reorder = np.argsort(np.random.rand(len(labels)))
      labels = labels[reorder]
      labels2,names = normaliselabels(labels)
      for new_n,old_n in enumerate(names):
          assert np.all( (labels == old_n) == (labels2 == new_n) )
  
  
subject: Test for normaliselabels