code: def setup_class(cls):
      data = ds.df
      nobs = len(data)
      data["dummy"] = (np.arange(nobs) < (nobs / 2)).astype(float)
      # alias to correspond to patsy name
      data["C(dummy)[T.1.0]"] = data["dummy"]
      cls.data = data
  
      columns = ["C(dummy)[T.1.0]", "pared", "public", "gpa"]
      # standard fit
      mod = OrderedModel(
          data["apply"].values.codes,
          np.asarray(data[columns], float),
          distr="logit",
      )
      cls.res = mod.fit(method="bfgs", disp=False)
      # standard fit with pandas input
      modp = OrderedModel(data["apply"], data[columns], distr="logit")
      cls.resp = modp.fit(method="bfgs", disp=False)
  
imports: import warnings
  import numpy
  from numpy.testing import assert_allclose, assert_equal
  import pandas
  import pytest
  import scipy.stats
  from statsmodels.discrete.discrete_model import Logit
  from statsmodels.miscmodels.ordinal_model import OrderedModel
  from statsmodels.tools.sm_exceptions import HessianInversionWarning
  from statsmodels.tools.tools import add_constant
  from .results.results_ordinal_model import data_store
label_desc: Use image node_id 1 for calling the TestLogitModelFormula obj's underlying member method code with example usage: obj.setup_class(cls) without return types