code: def hypervolume(
      points: npt.NDArray[np.float32], box: float = 1
  ) -> float:
      """
      Computes the hypervolume assuming that all values were previously
      normalized to lie in the range (0, 1).
  
      Args:
          point: Array of shape [N, D] (N: number of points, D: dimensionality) containing the points
              of the Pareto front.
          box: The coordinate of the box's edge. By default, this is located at [1, ..., 1] with
              the appropriate dimensionality.
  
      Returns:
          The hypervolume.
      """
      dim = points.shape[1]
      ref = np.ones(dim) * box
      return pygmo.hypervolume(points).compute(ref) / (box**dim)
  
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 1 for calling a global function with example usage: hypervolume(points, box) and returns: unknown