code: def setup_class(cls):
      nobs = 30
      np.random.seed(987128)
      x = np.random.randn(nobs, 3)
      y = x.sum(1) + np.random.randn(nobs)
      index = ["obs%02d" % i for i in range(nobs)]
      # add one extra column to check that it does not matter
      cls.data = pd.DataFrame(
          np.round(np.column_stack((y, x)), 4),
          columns="y var1 var2 var3".split(),
          index=index,
      )
  
      cls.res = OLS.from_formula("y ~ var1 + var2", data=cls.data).fit()
  
file_path: statsmodels/statsmodels/base/tests/test_predict.py
imports: from statsmodels.compat.pandas import testing
  import numpy
  import pandas
  from numpy.testing import assert_allclose, assert_equal
  from statsmodels.regression.linear_model import OLS
  from statsmodels.genmod.generalized_linear_model import GLM
label_desc: Use image node_id 1 for calling the TestPredictOLS obj's underlying member method code with example usage: obj.setup_class(cls) without return types