mplot3d import proj3d
>>> # set input data
>>> points = np.array([[0, 0, 1], [0, 0, -1], [1, 0, 0],
...                    [0, 1, 0], [0, -1, 0], [-1, 0, 0], ])

Calculate the spherical Voronoi diagram:

>>> radius = 1
>>> center = np.array([0, 0, 0])
>>> sv = SphericalVoronoi(points, radius, center)

Generate plot:

>>> # sort vertices (optional, helpful for plotting)
>>> sv.sort_vertices_of_regions()
>>> t_vals = np.linspace(0, 1, 2000)
>>> fig = plt.figure()
>>> ax = fig.add_subplot(111, projection='3d')
>>> # plot the unit sphere for reference (optional)
>>> u = np.linspace(0, 2 * np.pi, 100)
>>> v = np.linspace(0, np.pi, 100)
>>> x = np.outer(np.cos(u), np.sin(v))
>>> y = np.outer(np.sin(u), np.sin(v))
>>> z = np.outer(np.ones(np.size(u)), np.cos(v))
>>> ax.plot_surface(x, y, z, color='y', alpha=0.1)
>>> # plot generator points
>>> ax.scatter(points[:, 0], points[:, 1], points[:, 2], c='b')
>>> # plot Voronoi vertices
>>> ax.scatter(sv.vertices[:, 0], sv.vertices[:, 1], sv.vertices[:, 2],
...                    c='g')
>>> # indicate Voronoi regions (as Euclidean polygons)
>>> for region in sv.regions:
...    n = len(region)
...    for i in range(n):
...        start = sv.vertices[region][i]
...        end = sv.vertices[region][(i + 1) % n]
...        result = geometric_slerp(start, end, t_vals)
...        ax.plot(result[..., 0],
...                result[..., 1],
...                result[..., 2],
...                c='k')
>>> ax.azim = 10
>>> ax.elev = 40
>>> _ = ax.set_xticks([])
>>> _ = ax.set_yticks([])
>>> _ = ax.set_zticks([])
>>> fig.set_size_inches(4, 4)
>>> plt.show()

Nc