code: def test_evaluate_with_window_splitters(
      wrapper, splitter, strategy, sample_frac
  ):
      """Test interval wrappers with different strategies and cross validators.
  
      The wrapper does some internal sliding window cross-validation to calculate the
      `residuals_matrix`, which means the initial cross-validation can cause issues.
  
      This checks refit and update strategies as well as expanding and sliding window
      splitters.
      """
      y = load_airline()[:60]
  
      if splitter == SlidingWindowSplitter:
          cv = splitter(
              fh=np.arange(1, 7),
              window_length=24,
              step_length=6,
          )
      elif splitter == ExpandingWindowSplitter:
          cv = splitter(
              fh=np.arange(1, 7),
              initial_window=24,
              step_length=6,
          )
  
      f = NaiveForecaster()
  
      if wrapper == ConformalIntervals:
          interval_forecaster = wrapper(
              f, initial_window=12, sample_frac=sample_frac
          )
      else:
          interval_forecaster = wrapper(f, initial_window=12)
  
      results = evaluate(
          forecaster=interval_forecaster,
          cv=cv,
          y=y,
          X=None,
          strategy=strategy,
          scoring=PinballLoss(alpha=[0.1, 0.5, 0.9]),
          return_data=True,
          error_score="raise",
          backend=None,
      )
  
      assert len(results) == 6
      assert not results.test_PinballLoss.isna().any()
  
file_path: sktime/sktime/forecasting/tests/test_interval_wrappers.py
imports: import numpy
  import pandas
  import pytest
  from sktime.datasets import load_airline
  from sktime.datatypes import convert_to, scitype_to_mtype
  from sktime.forecasting.conformal import ConformalIntervals
  from sktime.forecasting.model_evaluation import evaluate
  from sktime.forecasting.naive import NaiveForecaster, NaiveVariance
  from sktime.performance_metrics.forecasting.probabilistic import PinballLoss
  from sktime.split import ExpandingWindowSplitter, SlidingWindowSplitter
  from sktime.tests.test_switch import run_test_for_class
label_desc: Use image node_id 2 for calling a global function with example usage: test_evaluate_with_window_splitters(wrapper, splitter, strategy, sample_frac) without return types