code: def test_cumulative_odds():
      table = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
      table = np.asarray(table)
      tbl_obj = ctab.Table(table)
  
      cum_odds = tbl_obj.cumulative_oddsratios
      assert_allclose(cum_odds[0, 0], 28 / float(5 * 11))
      assert_allclose(
          cum_odds[0, 1], (3 * 15) / float(3 * 24), atol=1e-5, rtol=1e-5
      )
      assert_allclose(
          np.log(cum_odds),
          tbl_obj.cumulative_log_oddsratios,
          atol=1e-5,
          rtol=1e-5,
      )
  
imports: import os
  import warnings
  import numpy
  import statsmodels.stats.contingency_tables
  import pandas
  from numpy.testing import assert_allclose, assert_equal
  import statsmodels.api
label_desc: Use image node_id 4 for calling a global function with example usage: test_cumulative_odds() without return types