code: def test_rank_compare_ord():
      # compare ordinal count version with full version
      # Example from Munzel and Hauschke 2003
      # data is given by counts, expand to observations
      levels = [-2, -1, 0, 1, 2]
      new = [24, 37, 21, 19, 6]
      active = [11, 51, 22, 21, 7]
      x1 = np.repeat(levels, new)
      x2 = np.repeat(levels, active)
  
      for use_t in [False, True]:
          res2 = rank_compare_2indep(x1, x2, use_t=use_t)
          res1 = rank_compare_2ordinal(new, active, use_t=use_t)
          assert_allclose(res2.prob1, res1.prob1, rtol=1e-13)
          assert_allclose(res2.var_prob, res1.var_prob, rtol=1e-13)
          s1 = str(res1.summary())
          s2 = str(res2.summary())
          assert s1 == s2
  
imports: from statsmodels.compat.python import lzip
  import numpy
  from numpy.testing import assert_allclose, assert_almost_equal, assert_approx_equal, assert_
  from scipy import stats
  import pytest
  from statsmodels.stats.contingency_tables import mcnemar, cochrans_q, SquareTable
  from statsmodels.sandbox.stats.runs import Runs, runstest_1samp, runstest_2samp
  from statsmodels.sandbox.stats.runs import mcnemar
  from statsmodels.stats.nonparametric import rank_compare_2indep, rank_compare_2ordinal, prob_larger_continuous, cohensd2problarger
  from statsmodels.tools.testing import Holder
label_desc: Use image node_id 14 for calling a global function with example usage: test_rank_compare_ord() without return types