old_contents: import choix
  import numpy as np
  
  from testutils import data_path, parse_pairwise
  
  
  LOGIT_TRUE_MEAN = np.array(
      [-2.24876774, -0.54278959, 0.5427896, 2.24876774])
  LOGIT_TRUE_COV = np.array(
      [[ 5.13442507, 1.78941794, 0.7363867,  0.33977029],
       [ 1.78941794, 3.87821895, 1.59597641, 0.73638669],
       [ 0.7363867,  1.59597641, 3.87821895, 1.78941794],
       [ 0.33977029, 0.73638669, 1.78941794, 5.13442508]])
  
  
  def test_ep_logit():
      with open(data_path("simpletrans-4.dat")) as f:
          num_items, data = parse_pairwise(f.read())
      mean, cov = choix.ep_pairwise(num_items, data, 8.0, model='logit')
      assert np.allclose(mean, LOGIT_TRUE_MEAN)
      assert np.allclose(cov, LOGIT_TRUE_COV)
  
new_contents: import choix
  import numpy as np
  
  from testutils import data_path, parse_pairwise
  
  
  LOGIT_TRUE_MEAN = np.array(
      [-2.24876774, -0.54278959, 0.5427896, 2.24876774])
  LOGIT_TRUE_COV = np.array(
      [[ 5.13442507, 1.78941794, 0.7363867,  0.33977029],
       [ 1.78941794, 3.87821895, 1.59597641, 0.73638669],
       [ 0.7363867,  1.59597641, 3.87821895, 1.78941794],
       [ 0.33977029, 0.73638669, 1.78941794, 5.13442508]])
  
  
  def test_ep_logit():
      with open(data_path("simpletrans-4.dat")) as f:
          num_items, data = parse_pairwise(f.read())
      mean, cov = choix.ep_pairwise(num_items, data, 8.0, model='logit')
      assert np.allclose(mean, LOGIT_TRUE_MEAN, atol=1e-3)
      assert np.allclose(cov, LOGIT_TRUE_COV, atol=1e-3)
  
subject: Increase the tolerance in EP unit test.