old_contents: """Tests for bicluster utilities."""
  
  import numpy as np
  
  from scipy.sparse import csr_matrix, issparse
  
  from sklearn.utils.testing import assert_equal
  from sklearn.utils.testing import assert_array_equal
  from sklearn.utils.testing import assert_true
  
  from sklearn.cluster.bicluster.utils import get_indicators
  from sklearn.cluster.bicluster.utils import get_shape
  from sklearn.cluster.bicluster.utils import get_submatrix
  
  
  def test_get_indicators():
      rows = [2, 4, 5]
      columns = [0, 1, 3]
      shape = (6, 4)
      row_ind, col_ind = get_indicators(rows, columns, shape)
      assert_array_equal(row_ind, [False, False, True, False, True, True])
      assert_array_equal(col_ind, [True, True, False, True])
  
  
  def test_get_shape():
      rows = [True, True, False, False]
      cols = [True, False, True, True]
      assert_equal(get_shape(rows, cols), (2, 3))
  
  
  def test_get_submatrix():
      data = np.arange(20).reshape(5, 4)
      rows = [True, True, False, False, True]
      cols = [False, False, True, True]
      for X in (data, csr_matrix(data)):
          submatrix = get_submatrix(rows, cols, X)
          if issparse(submatrix):
              submatrix = submatrix.todense()
          assert_array_equal(submatrix, [[2, 3],
                                         [6, 7],
                                         [18, 19]])
          submatrix[:] = -1
          assert_true(np.all(X != -1))
  
new_contents: """Tests for bicluster utilities."""
  
  import numpy as np
  
  from scipy.sparse import csr_matrix, issparse
  
  from sklearn.utils.testing import assert_equal
  from sklearn.utils.testing import assert_array_equal
  from sklearn.utils.testing import assert_true
  
  from sklearn.cluster.bicluster.utils import get_indicators
  from sklearn.cluster.bicluster.utils import get_shape
  from sklearn.cluster.bicluster.utils import get_submatrix
  
  
  def test_get_indicators():
      rows = [2, 4, 5]
      columns = [0, 1, 3]
      shape = (6, 4)
      row_ind, col_ind = get_indicators(rows, columns, shape)
      assert_array_equal(row_ind, [False, False, True, False, True, True])
      assert_array_equal(col_ind, [True, True, False, True])
  
  
  def test_get_shape():
      rows = [True, True, False, False]
      cols = [True, False, True, True]
      assert_equal(get_shape(rows, cols), (2, 3))
  
  
  def test_get_submatrix():
      data = np.arange(20).reshape(5, 4)
      rows = [True, True, False, False, True]
      cols = [False, False, True, True]
      for X in (data, csr_matrix(data)):
          submatrix = get_submatrix(rows, cols, X)
          if issparse(submatrix):
              submatrix = submatrix.todense()
          assert_array_equal(submatrix, [[2, 3],
                                         [6, 7],
                                         [18, 19]])
          submatrix[:] = -1
          if issparse(X):
              X = X.todense()
          assert_true(np.all(X != -1))
  
subject: fix test on scipy dev version