code: def test_ntjump_1_class(default_kwargs):
      default_kwargs["ntjump"] = 1
      class_kwargs, outer, inner = _to_class_kwargs(default_kwargs)
      mod = STL(**class_kwargs)
      res = mod.fit(outer_iter=outer, inner_iter=inner)
  
      expected = results.loc["ntjump-1"].sort_index()
      assert_allclose(res.seasonal, expected.season)
      assert_allclose(res.trend, expected.trend)
      assert_allclose(res.weights, expected.rw)
  
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 9 for calling a global function with example usage: test_ntjump_1_class(default_kwargs) without return types