code: def setup_class(cls):
      nobs = 60
      np.random.seed(123456)
      cls.o = np.random.binomial(2, 0.7, size=(nobs, 1))
      cls.o2 = np.random.binomial(3, 0.7, size=(nobs, 1))
      cls.c1 = np.random.normal(size=(nobs, 1))
      cls.c2 = np.random.normal(10, 1, size=(nobs, 1))
      cls.c3 = np.random.normal(10, 2, size=(nobs, 1))
      cls.noise = np.random.normal(size=(nobs, 1))
      b0 = 0.3
      b1 = 1.2
      b2 = 3.7  # regression coefficients
      cls.y = b0 + b1 * cls.c1 + b2 * cls.c2 + cls.noise
      cls.y2 = b0 + b1 * cls.c1 + b2 * cls.c2 + cls.o + cls.noise
      # Italy data from R's np package (the first 50 obs) R>> data (Italy)
  
      cls.Italy_gdp = [
          8.556,
          12.262,
          9.587,
          8.119,
          5.537,
          6.796,
          8.638,
          6.483,
          6.212,
          5.111,
          6.001,
          7.027,
          4.616,
          3.922,
          4.688,
          3.957,
          3.159,
          3.763,
          3.829,
          5.242,
          6.275,
          8.518,
          11.542,
          9.348,
          8.02,
          5.527,
          6.865,
          8.666,
          6.672,
          6.289,
          5.286,
          6.271,
          7.94,
          4.72,
          4.357,
          4.672,
          3.883,
          3.065,
          3.489,
          3.635,
          5.443,
          6.302,
          9.054,
          12.485,
          9.896,
          8.33,
          6.161,
          7.055,
          8.717,
          6.95,
      ]
  
      cls.Italy_year = [
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1951,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1952,
          1953,
          1953,
          1953,
          1953,
          1953,
          1953,
          1953,
          1953,
      ]
  
      # OECD panel data from NP  R>> data(oecdpanel)
      cls.growth = [
          -0.0017584,
          0.00740688,
          0.03424461,
          0.03848719,
          0.02932506,
          0.03769199,
          0.0466038,
          0.00199456,
          0.03679607,
          0.01917304,
          -0.00221,
          0.00787269,
          0.03441118,
          -0.0109228,
          0.02043064,
          -0.0307962,
          0.02008947,
          0.00580313,
          0.00344502,
          0.04706358,
          0.03585851,
          0.01464953,
          0.04525762,
          0.04109222,
          -0.0087903,
          0.04087915,
          0.04551403,
          0.036916,
          0.00369293,
          0.0718669,
          0.02577732,
          -0.0130759,
          -0.01656641,
          0.00676429,
          0.08833017,
          0.05092105,
          0.02005877,
          0.00183858,
          0.03903173,
          0.05832116,
          0.0494571,
          0.02078484,
          0.09213897,
          0.0070534,
          0.08677202,
          0.06830603,
          -0.00041,
          0.0002856,
          0.03421225,
          -0.0036825,
      ]
  
      cls.oecd = [
          0,
          0,
          1,
          1,
          0,
          0,
          1,
          0,
          0,
          0,
          0,
          0,
          1,
          0,
          0,
          0,
          0,
          0,
          0,
          1,
          0,
          0,
          0,
          0,
          0,
          1,
          1,
          1,
          0,
          1,
          0,
          0,
          0,
          0,
          0,
          1,
          0,
          0,
          1,
          0,
          1,
          0,
          1,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
      ]
  
file_path: statsmodels/statsmodels/sandbox/nonparametric/tests/test_kernel_extras.py
imports: import numpy
  import numpy.testing
  from statsmodels.sandbox.nonparametric.kernel_extras import SemiLinear
label_desc: Use image node_id 1 for calling the KernelExtrasTestBase obj's underlying member method code with example usage: obj.setup_class(cls) without return types