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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def discrete_gaussian_curvature_measure(mesh, points, radius):
 """ 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. """


    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)