content: """Testing for bicluster metrics module"""
  
  import numpy as np
  
  from sklearn.utils.testing import assert_equal, assert_almost_equal
  
  from sklearn.metrics.cluster.bicluster import _jaccard
  from sklearn.metrics import consensus_score
  
  
  def test_jaccard():
      a1 = np.array([True, True, False, False])
      a2 = np.array([True, True, True, True])
      a3 = np.array([False, True, True, False])
      a4 = np.array([False, False, True, True])
  
      assert_equal(_jaccard(a1, a1, a1, a1), 1)
      assert_equal(_jaccard(a1, a1, a2, a2), 0.25)
      assert_equal(_jaccard(a1, a1, a3, a3), 1.0 / 7)
      assert_equal(_jaccard(a1, a1, a4, a4), 0)
  
  
  def test_consensus_score():
      a = [[True, True, False, False],
           [False, False, True, True]]
      b = a[::-1]
  
      assert_equal(consensus_score((a, a), (a, a)), 1)
      assert_equal(consensus_score((a, a), (b, b)), 1)
      assert_equal(consensus_score((a, b), (a, b)), 1)
      assert_equal(consensus_score((a, b), (b, a)), 1)
  
      assert_equal(consensus_score((a, a), (b, a)), 0)
      assert_equal(consensus_score((a, a), (a, b)), 0)
      assert_equal(consensus_score((b, b), (a, b)), 0)
      assert_equal(consensus_score((b, b), (b, a)), 0)
  
  
  def test_consensus_score_issue2445():
      ''' Different number of biclusters in A and B'''
      a_rows = np.array([[True, True, False, False],
                         [False, False, True, True],
                         [False, False, False, True]])
      a_cols = np.array([[True, True, False, False],
                         [False, False, True, True],
                         [False, False, False, True]])
      idx = [0, 2]
      s = consensus_score((a_rows, a_cols), (a_rows[idx], a_cols[idx]))
      # B contains 2 of the 3 biclusters in A, so score should be 2/3
      assert_almost_equal(s, 2.0/3.0)
  