code: def test_recreate_model():
      nobs = 100
      endog = np.ones(nobs) * 2.0
      exog = np.ones(nobs)
  
      levels = [
          "irregular",
          "ntrend",
          "fixed intercept",
          "deterministic constant",
          "dconstant",
          "local level",
          "llevel",
          "random walk",
          "rwalk",
          "fixed slope",
          "deterministic trend",
          "dtrend",
          "local linear deterministic trend",
          "lldtrend",
          "random walk with drift",
          "rwdrift",
          "local linear trend",
          "lltrend",
          "smooth trend",
          "strend",
          "random trend",
          "rtrend",
      ]
  
      for level in levels:
          # Note: have to add in some stochastic component, otherwise we have
          # problems with entirely deterministic models
  
          # level + stochastic seasonal
          mod = UnobservedComponents(
              endog,
              level=level,
              seasonal=2,
              stochastic_seasonal=True,
              exog=exog,
          )
          mod2 = UnobservedComponents(
              endog, exog=exog, **mod._get_init_kwds()
          )
          check_equivalent_models(mod, mod2)
  
          # level + autoregressive
          mod = UnobservedComponents(
              endog, level=level, exog=exog, autoregressive=1
          )
          mod2 = UnobservedComponents(
              endog, exog=exog, **mod._get_init_kwds()
          )
          check_equivalent_models(mod, mod2)
  
          # level + stochastic cycle
          mod = UnobservedComponents(
              endog,
              level=level,
              exog=exog,
              cycle=True,
              stochastic_cycle=True,
              damped_cycle=True,
          )
          mod2 = UnobservedComponents(
              endog, exog=exog, **mod._get_init_kwds()
          )
          check_equivalent_models(mod, mod2)
  
imports: import warnings
  import numpy
  from numpy.testing import assert_equal, assert_allclose, assert_raises
  import pandas
  import pytest
  from statsmodels.datasets import macrodata
  from statsmodels.tools.sm_exceptions import SpecificationWarning
  from statsmodels.tsa.statespace import structural
  from statsmodels.tsa.statespace.structural import UnobservedComponents
  from statsmodels.tsa.statespace.tests.results import results_structural
label_desc: Use image node_id 31 for calling a global function with example usage: test_recreate_model() without return types