code: def discrete_gaussian_curvature_measure(mesh, points, radius):
      
  
      points = np.asanyarray(points, dtype=np.float64)
      if not util.is_shape(points, (-1, 3)):
          raise ValueError('points must be (n,3)!')
  
      nearest = mesh.kdtree.query_ball_point(points, radius)
      gauss_curv = [mesh.vertex_defects[vertices].sum() for vertices in nearest]
  
      return np.asarray(gauss_curv)
docs: Return the discrete gaussian curvature measure of a sphere centered
      at a point as detailed in 'Restricted Delaunay triangulations and normal
      cycle', Cohen-Steiner and Morvan.
  
      Parameters
      ----------
      points : (n,3) float, list of points in space
      radius : float, the sphere radius
  
      Returns
      --------
      gaussian_curvature: (n,) float, discrete gaussian curvature measure.