code: def setup_class(cls):
      data = np.zeros((8, 2))
      data[:, 0] = [0, 0, 1, 1, 0, 0, 1, 1]
      data[:, 1] = [0, 1, 0, 1, 0, 1, 0, 1]
      cls.data = np.asarray(data)
      cls.table = np.asarray([[2, 2], [2, 2]])
  
      cls.oddsratio = 1.0
      cls.log_oddsratio = 0.0
      cls.log_oddsratio_se = np.sqrt(2)
      cls.oddsratio_confint = [0.062548836166112329, 15.987507702689751]
      cls.oddsratio_pvalue = 1.0
      cls.riskratio = 1.0
      cls.log_riskratio = 0.0
      cls.log_riskratio_se = 1 / np.sqrt(2)
      cls.riskratio_pvalue = 1.0
      cls.riskratio_confint = [0.25009765325990629, 3.9984381579173824]
      cls.log_riskratio_confint = [
          -1.3859038243496782,
          1.3859038243496782,
      ]
      ss = [
          "               Estimate   SE   LCB    UCB   p-value",
          "---------------------------------------------------",
          "Odds ratio        1.000        0.063 15.988   1.000",
          "Log odds ratio    0.000 1.414 -2.772  2.772   1.000",
          "Risk ratio        1.000        0.250  3.998   1.000",
          "Log risk ratio    0.000 0.707 -1.386  1.386   1.000",
          "---------------------------------------------------",
      ]
      cls.summary_string = "\n".join(ss)
      cls.initialize()
  
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 Test2x2_1 obj's underlying member method code with example usage: obj.setup_class(cls) without return types