code: def test_one_step_ahead(setup_model):
      model, params, results_R = setup_model
      model2 = ETSModel(
          pd.Series(model.endog),
          seasonal_periods=model.seasonal_periods,
          error=model.error,
          trend=model.trend,
          seasonal=model.seasonal,
          damped_trend=model.damped_trend,
      )
      res = model2.smooth(params)
  
      fcast1 = res.forecast(steps=1)
      fcast2 = res.forecast(steps=2)
      assert_allclose(fcast1.iloc[0], fcast2.iloc[0])
  
      pred1 = res.get_prediction(
          start=model2.nobs, end=model2.nobs, simulate_repetitions=2
      )
      pred2 = res.get_prediction(
          start=model2.nobs, end=model2.nobs + 1, simulate_repetitions=2
      )
      df1 = pred1.summary_frame(alpha=0.05)
      df2 = pred1.summary_frame(alpha=0.05)
      assert_allclose(df1.iloc[0, 0], df2.iloc[0, 0])
  
imports: from statsmodels.compat.pandas import QUARTER_END
  from statsmodels.compat.platform import PLATFORM_LINUX32, PLATFORM_WIN
  from itertools import product
  import json
  import pathlib
  import numpy
  from numpy.testing import assert_allclose, assert_almost_equal
  import pandas
  import pytest
  import scipy.stats
  from statsmodels.tsa.exponential_smoothing.ets import ETSModel
  import statsmodels.tsa.holtwinters
  import statsmodels.tsa.statespace.exponential_smoothing
label_desc: Use image node_id 40 for calling a global function with example usage: test_one_step_ahead(setup_model) without return types