class_docstr: library(DescTools)
  data = array(c(20, 14, 10, 24,
                 15, 12, 3, 15,
                 3, 2, 3, 2,
                 12, 3, 7, 5,
                 1, 0, 3, 2),
                 dim=c(2, 2, 5))
  rslt = mantelhaen.test(data)
  bd1 = BreslowDayTest(data, correct=FALSE)
  bd2 = BreslowDayTest(data, correct=TRUE)
code: def setup_class(cls):
      tables = [None] * 5
      tables[0] = np.array([[20, 14], [10, 24]])
      tables[1] = np.array([[15, 12], [3, 15]])
      tables[2] = np.array([[3, 2], [3, 2]])
      tables[3] = np.array([[12, 3], [7, 5]])
      tables[4] = np.array([[1, 0], [3, 2]])
  
      # check array of int
      cls.initialize(tables, use_arr=True)
  
      cls.oddsratio_pooled = 3.5912
      cls.logodds_pooled = np.log(3.5912)
  
      cls.mh_stat = 11.8852
      cls.mh_pvalue = 0.0005658
  
      cls.or_lcb = 1.781135
      cls.or_ucb = 7.240633
  
      # Breslow Day test without Tarone adjustment
      cls.or_homog = 1.8438
      cls.or_homog_p = 0.7645
  
      # Breslow Day test with Tarone adjustment
      cls.or_homog_adj = 1.8436
      cls.or_homog_adj_p = 0.7645
  
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 1 for calling the TestStratified2 obj's underlying member method code with example usage: obj.setup_class(cls) without return types