code: def count_error(
      true_change_points: npt.ArrayLike,
      pred_change_points: npt.ArrayLike,
  ) -> float:
      """Error counting the difference in the number of change points.
  
      Parameters
      ----------
      true_change_points: array_like
          Integer indexes (positions) of true change points
      pred_change_points: array_like
          Integer indexes (positions) of predicted change points
  
      Returns
      -------
          count_error
      """
      true_change_points = check_array(
          true_change_points, ensure_2d=False
      )
      pred_change_points = check_array(
          pred_change_points, ensure_2d=False
      )
      return abs(true_change_points.size - pred_change_points.size)
  
imports: import numpy
  import numpy.typing
  from scipy.spatial.distance import directed_hausdorff
  from sklearn.utils import check_array
label_desc: Use image node_id 1 for calling a global function with example usage: count_error(true_change_points, pred_change_points) and returns: abs