code: def setup_class(cls):
      np.random.seed(987125643)
      nr = 1
      n_groups = 2
      labels = np.arange(n_groups)
      x = np.repeat(labels, np.array([40, 60]) * nr)
      nobs = x.shape[0]
      exog = (x[:, None] == labels).astype(np.float64)
      # reparameterize to explicit constant
      # exog[:, 1] = 1
      beta = np.array([0.1, 0.3], np.float64)
  
      linpred = exog @ beta
      mean = np.exp(linpred)
      y = np.random.poisson(mean)
  
      cls.endog = y
      cls.exog = exog
  
file_path: statsmodels/statsmodels/discrete/tests/test_diagnostic.py
imports: import numpy
  from numpy.testing import assert_allclose, assert_equal
  import pytest
  from statsmodels.discrete.discrete_model import Poisson
  import statsmodels.discrete._diagnostics_count
  from statsmodels.discrete.diagnostic import PoissonDiagnostic
label_desc: Use image node_id 1 for calling the TestPoissonDiagnosticClass obj's underlying member method code with example usage: obj.setup_class(cls) without return types