code: def test_2D_score_with_na():
      """Test score with 2D input array with missing values."""
      X = np.array(
          [
              [-1.20706575, -0.57473996],
              [0.27742924, -0.54663186],
              [1.08444118, np.nan],
              [-2.3456977, -0.89003783],
              [0.42912469, -0.4771927],
              [0.50605589, -0.99838644],
          ]
      )
  
      y_scores_expected = np.array(
          [
              0.43612712,
              0.43612712,
              np.nan,
              0.69004259,
              0.51240831,
              0.85697804,
          ]
      )
  
      scaler = MinMaxScaler()
      X = scaler.fit_transform(X)
      model = STRAY(k=2, size_threshold=4)
      fitted_model = model.fit(X)
      y_scores_actual = fitted_model.score_
      assert np.allclose(
          y_scores_actual, y_scores_expected, equal_nan=True
      )
  
file_path: sktime/sktime/annotation/tests/test_stray.py
imports: import numpy
  from sklearn.preprocessing import MinMaxScaler, RobustScaler
  from sktime.annotation.stray import STRAY
label_desc: Use image node_id 5 for calling a global function with example usage: test_2D_score_with_na() without return types