code: def test_linex_function():
      """Doctest from mean_linex_error."""
      from sktime.performance_metrics.forecasting import (
          mean_linex_error,
      )
  
      y_true = np.array([3, -0.5, 2, 7, 2])
      y_pred = np.array([2.5, 0.0, 2, 8, 1.25])
      assert np.allclose(
          mean_linex_error(y_true, y_pred), 0.19802627763937575
      )
      assert np.allclose(
          mean_linex_error(y_true, y_pred, b=2), 0.3960525552787515
      )
      assert np.allclose(
          mean_linex_error(y_true, y_pred, a=-1), 0.2391800623225643
      )
      y_true = np.array([[0.5, 1], [-1, 1], [7, -6]])
      y_pred = np.array([[0, 2], [-1, 2], [8, -5]])
      assert np.allclose(
          mean_linex_error(y_true, y_pred), 0.2700398392309829
      )
      assert np.allclose(
          mean_linex_error(y_true, y_pred, a=-1), 0.49660966225813563
      )
      assert np.allclose(
          mean_linex_error(y_true, y_pred, multioutput="raw_values"),
          np.array([0.17220024, 0.36787944]),
      )
      assert np.allclose(
          mean_linex_error(y_true, y_pred, multioutput=[0.3, 0.7]),
          0.30917568000716666,
      )
  
imports: import numpy
  import pandas
label_desc: Use image node_id 4 for calling a global function with example usage: test_linex_function() without return types