code: def setup_class(cls):
      yt0 = np.array(
          [
              102.0,
              320.0,
              0.0,
              107.0,
              198.0,
              200.0,
              4.0,
              20.0,
              110.0,
              128.0,
              7.0,
              119.0,
              309.0,
          ]
      )
  
      yt1 = np.array(
          [
              0.0,
              1.0,
              228.0,
              81.0,
              87.0,
              119.0,
              79.0,
              181.0,
              43.0,
              12.0,
              90.0,
              105.0,
              108.0,
              119.0,
              0.0,
              9.0,
          ]
      )
      yt2 = np.array(
          [
              33.0,
              294.0,
              134.0,
              216.0,
              83.0,
              105.0,
              69.0,
              20.0,
              20.0,
              63.0,
              98.0,
              155.0,
              78.0,
              75.0,
          ]
      )
  
      y0 = np.array(
          [
              452.0,
              874.0,
              554.0,
              447.0,
              356.0,
              754.0,
              558.0,
              574.0,
              664.0,
              682.0,
              547.0,
              435.0,
              245.0,
          ]
      )
      y1 = np.array(
          [
              546.0,
              547.0,
              774.0,
              465.0,
              459.0,
              665.0,
              467.0,
              365.0,
              589.0,
              534.0,
              456.0,
              651.0,
              654.0,
              665.0,
              546.0,
              537.0,
          ]
      )
      y2 = np.array(
          [
              785.0,
              458.0,
              886.0,
              536.0,
              669.0,
              857.0,
              821.0,
              772.0,
              732.0,
              689.0,
              654.0,
              597.0,
              830.0,
              827.0,
          ]
      )
  
      n_groups = 3
      data = [y0, y1, y2]
      nobs = np.asarray([len(yi) for yi in data])
      nobs_mean = np.mean(nobs)
      means = np.asarray([yi.mean() for yi in data])
      stds = np.asarray([yi.std(ddof=1) for yi in data])
      cls.data = data
      cls.data_transformed = [yt0, yt1, yt2]
      cls.means = means
      cls.nobs = nobs
      cls.stds = stds
      cls.n_groups = n_groups
      cls.nobs_mean = nobs_mean
  
imports: import numpy
  from numpy.testing import assert_allclose, assert_equal
  import pytest
  from statsmodels.regression.linear_model import OLS
  import statsmodels.stats.power
  import statsmodels.stats.oneway
  from statsmodels.stats.oneway import confint_effectsize_oneway, confint_noncentrality, effectsize_oneway, anova_oneway, anova_generic, equivalence_oneway, equivalence_oneway_generic, power_equivalence_oneway, _power_equivalence_oneway_emp, f2_to_wellek, fstat_to_wellek, wellek_to_f2
  from statsmodels.stats.robust_compare import scale_transform
  from statsmodels.stats.contrast import wald_test_noncent_generic, wald_test_noncent, _offset_constraint
label_desc: Use image node_id 1 for calling the TestOnewayScale obj's underlying member method code with example usage: obj.setup_class(cls) without return types