code: def test_tukeylambda_stats_mpmath():
      """Compare results with some values that were computed using mpmath."""
      a10 = dict(atol=1e-10, rtol=0)
      a12 = dict(atol=1e-12, rtol=0)
      data = [
          # lambda        variance              kurtosis
          [-0.1, 4.78050217874253547, 3.78559520346454510],
          [-0.0649, 4.16428023599895777, 2.52019675947435718],
          [-0.05, 3.93672267890775277, 2.13129793057777277],
          [-0.001, 3.30128380390964882, 1.21452460083542988],
          [0.001, 3.27850775649572176, 1.18560634779287585],
          [0.03125, 2.95927803254615800, 0.804487555161819980],
          [0.05, 2.78281053405464501, 0.611604043886644327],
          [0.0649, 2.65282386754100551, 0.476834119532774540],
          [1.2, 0.242153920578588346, -1.23428047169049726],
          [10.0, 0.00095237579757703597, 2.37810697355144933],
          [20.0, 0.00012195121951131043, 7.37654321002709531],
      ]
  
      for lam, var_expected, kurt_expected in data:
          var = tukeylambda_variance(lam)
          assert_allclose(var, var_expected, **a12)
          kurt = tukeylambda_kurtosis(lam)
          assert_allclose(kurt, kurt_expected, **a10)
  
      # Test with vector arguments (most of the other tests are for single
      # values).
      lam, var_expected, kurt_expected = zip(*data)
      var = tukeylambda_variance(lam)
      assert_allclose(var, var_expected, **a12)
      kurt = tukeylambda_kurtosis(lam)
      assert_allclose(kurt, kurt_expected, **a10)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from numpy.testing import assert_allclose, assert_equal
  from scipy.stats._tukeylambda_stats import tukeylambda_variance, tukeylambda_kurtosis
label_desc: Use image node_id 2 for calling a global function with example usage: test_tukeylambda_stats_mpmath() without return types