code: def test_1D_score_with_na():
      """Test score with 1D input array with missing values."""
      X = np.array(
          [
              np.nan,
              -5.72257076,
              -4.91555882,
              -8.3456977,
              -5.57087531,
              0.0,
              6.50605589,
              5.42526004,
              5.45336814,
              5.435548,
              5.10996217,
          ]
      )
  
      y_scores_expected = np.array(
          [
              np.nan,
              0.17662069,
              0.23095851,
              0.17662069,
              0.18683466,
              0.33097498,
              0.07087969,
              0.02122967,
              0.02312225,
              0.02192238,
              0.02122967,
          ]
      )
  
      scaler = MinMaxScaler()
      X = scaler.fit_transform(X.reshape(-1, 1))
      model = STRAY(k=3)
      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 3 for calling a global function with example usage: test_1D_score_with_na() without return types