code: def maximum_spread(solution: npt.NDArray[np.float32]) -> float:
      """
      Computes the maximum spread of the solution's Pareto front.
  
      Args:
          solution: Array of shape [N, D] (N: number of points, D: dimensionality) containing the
              points of the solution set.
  
      Returns:
          The modified maximum spread of the solution.
      """
      solution_min = np.min(solution, axis=0)
      solution_max = np.max(solution, axis=0)
      return np.linalg.norm(solution_max - solution_min)
  
file_path: gluonts/src/gluonts/nursery/tsbench/src/tsbench/analysis/utils/mo_metrics.py
imports: from typing import Tuple
  import numpy
  import numpy.typing
  import pygmo
  import scipy.spatial
label_desc: Use image node_id 2 for calling a global function with example usage: maximum_spread(solution) and returns: np