code: def test_sharex(data):
      stlf = STLForecast(data, ARIMA, model_kwargs={"order": (2, 0, 0)})
      res = stlf.fit(fit_kwargs={})
      plt = res.result.plot()
      grouper_view = plt.axes[0].get_shared_x_axes()
      sibs = grouper_view.get_siblings(plt.axes[1])
      assert len(sibs) == 4
  
imports: from statsmodels.compat.pandas import MONTH_END
  import numpy
  from numpy.testing import assert_allclose
  import pandas
  import pytest
  import statsmodels.datasets
  from statsmodels.tsa.ar_model import AutoReg
  from statsmodels.tsa.arima.model import ARIMA
  from statsmodels.tsa.base.prediction import PredictionResults
  from statsmodels.tsa.deterministic import Fourier
  from statsmodels.tsa.exponential_smoothing.ets import ETSModel
  from statsmodels.tsa.forecasting.stl import STLForecast
  from statsmodels.tsa.seasonal import STL, DecomposeResult
  from statsmodels.tsa.statespace.exponential_smoothing import ExponentialSmoothing
label_desc: Use image node_id 3 for calling a global function with example usage: test_sharex(data) without return types