code: def setup_class(cls):
      df = data_bin
      mod = GLM(
          df["constrict"],
          df[["const", "log_rate", "log_volumne"]],
          family=families.Binomial(link=families.links.Probit()),
      )
      res = mod.fit(method="newton", tol=1e-10)
      from statsmodels.discrete.discrete_model import Probit
  
      mod2 = Probit(
          df["constrict"], df[["const", "log_rate", "log_volumne"]]
      )
      res2 = mod2.fit(method="newton", tol=1e-10)
  
      cls.infl1 = MLEInfluence(res)  # res.get_influence()
      cls.infl0 = res2.get_influence()
  
imports: from statsmodels.compat.pandas import testing
  import os.path
  import numpy
  from numpy.testing import assert_allclose
  import pandas
  import pytest
  from statsmodels.regression.linear_model import OLS
  from statsmodels.genmod.generalized_linear_model import GLM
  from statsmodels.genmod import families
  from statsmodels.stats.outliers_influence import MLEInfluence
label_desc: Use image node_id 1 for calling the TestInfluenceProbitCompare obj's underlying member method code with example usage: obj.setup_class(cls) without return types