code: def test_seasonal_order(reset_randomstate, method):
      seasonal = np.arange(12.0)
      time_series = np.array(list(seasonal) * 100)
      res = ETSModel(
          time_series,
          seasonal="add",
          seasonal_periods=12,
          initialization_method=method,
      ).fit()
      assert_allclose(
          res.initial_seasonal + res.initial_level,
          seasonal,
          atol=1e-4,
          rtol=1e-4,
      )
      assert res.mae < 1e-6
  
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 42 for calling a global function with example usage: test_seasonal_order(reset_randomstate, method) without return types