code: def test_prediction_results(austourists_model_fit):
      # simple test case starting at 0
      pred = austourists_model_fit.get_prediction(
          start=0,
          dynamic=30,
          end=40,
      )
      summary = pred.summary_frame()
      assert len(summary["mean"].values) == 41
      assert np.all(~np.isnan(summary["mean"]))
  
      # simple test case starting at not 0
      pred = austourists_model_fit.get_prediction(
          start=10, dynamic=30, end=40
      )
      summary = pred.summary_frame()
      assert len(summary["mean"].values) == 31
      assert np.all(~np.isnan(summary["mean"]))
  
      # long out of sample prediction
      pred = austourists_model_fit.get_prediction(
          start=0, dynamic=30, end=80
      )
      summary = pred.summary_frame()
      assert len(summary["mean"].values) == 81
      assert np.all(~np.isnan(summary["mean"]))
  
      # long out of sample, starting in-sample
      pred = austourists_model_fit.get_prediction(start=67, end=80)
      summary = pred.summary_frame()
      assert len(summary["mean"].values) == 14
      assert np.all(~np.isnan(summary["mean"]))
  
      # long out of sample, starting at end of sample
      pred = austourists_model_fit.get_prediction(start=68, end=80)
      summary = pred.summary_frame()
      assert len(summary["mean"].values) == 13
      assert np.all(~np.isnan(summary["mean"]))
  
      # long out of sample, starting just out of sample
      pred = austourists_model_fit.get_prediction(start=69, end=80)
      summary = pred.summary_frame()
      assert len(summary["mean"].values) == 12
      assert np.all(~np.isnan(summary["mean"]))
  
      # long out of sample, starting long out of sample
      pred = austourists_model_fit.get_prediction(start=79, end=80)
      summary = pred.summary_frame()
      assert len(summary["mean"].values) == 2
      assert np.all(~np.isnan(summary["mean"]))
  
      # long out of sample, `start`== `end`
      pred = austourists_model_fit.get_prediction(start=80, end=80)
      summary = pred.summary_frame()
      assert len(summary["mean"].values) == 1
      assert np.all(~np.isnan(summary["mean"]))
  
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 32 for calling a global function with example usage: test_prediction_results(austourists_model_fit) without return types