code: def test_default_trend(default_kwargs):
      # GH 6686
      class_kwargs, _, _ = _to_class_kwargs(default_kwargs)
      class_kwargs["seasonal"] = 17
      class_kwargs["trend"] = None
      mod = STL(**class_kwargs)
      period = class_kwargs["period"]
      seasonal = class_kwargs["seasonal"]
      expected = int(np.ceil(1.5 * period / (1 - 1.5 / seasonal)))
      expected += 1 if expected % 2 == 0 else 0
      assert mod.config["trend"] == expected
  
      class_kwargs["seasonal"] = 7
      mod = STL(**class_kwargs)
      period = class_kwargs["period"]
      seasonal = class_kwargs["seasonal"]
      expected = int(np.ceil(1.5 * period / (1 - 1.5 / seasonal)))
      expected += 1 if expected % 2 == 0 else 0
      assert mod.config["trend"] == expected
  
imports: from statsmodels.compat.pandas import MONTH_END
  import os
  import pickle
  import numpy
  from numpy.testing import assert_allclose
  import pandas
  import pytest
  from statsmodels.datasets import co2
  from statsmodels.tsa.seasonal import STL, DecomposeResult
label_desc: Use image node_id 21 for calling a global function with example usage: test_default_trend(default_kwargs) without return types