code: def test_sequential_simulate():
      # Test that we can perform simulation, change the system matrices, and then
      # perform simulation again (i.e. check that everything updates correctly
      # in the simulation smoother).
      n_simulations = 100
      mod = sarimax.SARIMAX([1], order=(0, 0, 0), trend="c")
  
      actual = mod.simulate([1, 0], n_simulations)
      assert_allclose(actual, np.ones(n_simulations))
  
      actual = mod.simulate([10, 0], n_simulations)
      assert_allclose(actual, np.ones(n_simulations) * 10)
  
imports: from statsmodels.compat.pandas import MONTH_END
  import numpy
  from numpy.testing import assert_, assert_allclose, assert_equal
  import pandas
  import pytest
  from scipy.signal import lfilter
  from statsmodels.tools.sm_exceptions import EstimationWarning, SpecificationWarning
  from statsmodels.tsa.statespace import dynamic_factor, sarimax, structural, varmax
  from .test_impulse_responses import TVSS
label_desc: Use image node_id 7 for calling a global function with example usage: test_sequential_simulate() without return types