code: def setup_class(cls):
      path = os.path.join(
          current_path, "results", "results_predict_fedfunds.csv"
      )
      results = pd.read_csv(path)
  
      true = {
          "params": np.r_[
              0.7279288,
              0.2114578,
              0.6554954,
              -0.0944924,
              0.8314458,
              0.9292574,
              0.1355425,
              0.0343072,
              -0.0273928,
              0.2125275,
              0.5764495**2,
          ],
          "llf": -229.25614,
          "llf_fit": -229.25614,
          "llf_fit_em": -229.25624,
          "bse_oim": np.r_[
              0.0929915,
              0.0641179,
              0.1373889,
              0.1279231,
              0.0333236,
              0.0270852,
              0.0294113,
              0.0240138,
              0.0408057,
              0.0297351,
              np.nan,
          ],
          "predict0": results.iloc[4:]["constL1exog_syhat1"],
          "predict1": results.iloc[4:]["constL1exog_syhat2"],
          "predict_smoothed": results.iloc[4:]["constL1exog_syhat"],
      }
      super().setup_class(
          true,
          fedfunds[4:],
          k_regimes=2,
          exog=np.c_[fedfunds[3:-1], ogap[4:], inf[4:]],
      )
  
imports: import os
  import warnings
  import numpy
  from numpy.testing import assert_allclose, assert_raises
  import pandas
  import pytest
  from statsmodels.tsa.regime_switching import markov_switching, markov_regression
label_desc: Use image node_id 1 for calling the TestFedFundsConstL1Exog obj's underlying member method code with example usage: obj.setup_class(cls) without return types