code: def test_cutoff_window_splitter(y, cutoffs, fh, window_length):
      """Test CutoffSplitter."""
      if _inputs_are_supported([cutoffs, fh, window_length]):
          cv = CutoffSplitter(
              cutoffs, fh=fh, window_length=window_length
          )
          train_windows, test_windows, cutoffs, n_splits = _check_cv(
              cv, y
          )
          np.testing.assert_array_equal(cutoffs, cv.get_cutoffs(y))
      else:
          match = "Unsupported combination of types"
          with pytest.raises(TypeError, match=match):
              CutoffSplitter(
                  cutoffs, fh=fh, window_length=window_length
              )
  
file_path: sktime/sktime/split/tests/test_cutoff.py
imports: import numpy
  import pandas
  import pytest
  from sktime.forecasting.tests._config import TEST_CUTOFFS, TEST_FHS, TEST_FHS_TIMEDELTA, TEST_WINDOW_LENGTHS, TEST_YS
  from sktime.split import CutoffFhSplitter, CutoffSplitter
  from sktime.split.base._common import _inputs_are_supported
  from sktime.split.tests.test_split import _check_cv
label_desc: Use image node_id 1 for calling a global function with example usage: test_cutoff_window_splitter(y, cutoffs, fh, window_length) without return types