code: def test_jump_errors(default_kwargs):
      class_kwargs, _, _ = _to_class_kwargs(default_kwargs)
      endog = class_kwargs["endog"]
      period = class_kwargs["period"]
      with pytest.raises(
          ValueError, match="low_pass_jump must be a positive"
      ):
          STL(endog=endog, period=period, low_pass_jump=0)
      with pytest.raises(
          ValueError, match="low_pass_jump must be a positive"
      ):
          STL(endog=endog, period=period, low_pass_jump=1.0)
      with pytest.raises(
          ValueError, match="seasonal_jump must be a positive"
      ):
          STL(endog=endog, period=period, seasonal_jump=0)
      with pytest.raises(
          ValueError, match="seasonal_jump must be a positive"
      ):
          STL(endog=endog, period=period, seasonal_jump=1.0)
      with pytest.raises(
          ValueError, match="trend_jump must be a positive"
      ):
          STL(endog=endog, period=period, trend_jump=0)
      with pytest.raises(
          ValueError, match="trend_jump must be a positive"
      ):
          STL(endog=endog, period=period, trend_jump=1.0)
  
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 15 for calling a global function with example usage: test_jump_errors(default_kwargs) without return types