def METHOD_NAME():
    print(__file__ + " start!!")
    ox, oy = create_dummy_observation_data()
    grid_resolution = 10.0
    ndt_map = NDTMap(ox, oy, grid_resolution)
    # plot raw observation
    plt.plot(ox, oy, ".r")
    # plot grid clustering
    [plt.plot(ox[inds], oy[inds], "x") for inds in ndt_map.grid_index_map.values()]
    # plot ndt grid map
    [plot_covariance_ellipse(ndt.mean_x, ndt.mean_y, ndt.covariance, color="-k") for ndt in ndt_map.grid_map.data if ndt.n_points > 0]
    plt.axis("equal")
    plt.show()