human
Solve the following python programming problem given the following code:
def test_rts() : 
    def fx(x, dt) : 
        A = (np.eye (3) + (dt * np.array ([[0, 1, 0], [0, 0, 0], [0, 0, 0]]))) 
        f = np.dot (A, x) 
        return f 
def hx(x) : 
        return np.sqrt (((x [0] ** 2) + (x [2] ** 2))) 
dt = 0.05 
    sp = JulierSigmaPoints (n = 3, kappa = 1.0) 
    kf = UKF (3, 1, dt, fx = fx, hx = hx, points = sp) 
    kf.Q *= 0.01 
    kf.R = 10 
    kf.x = np.array ([0.0, 90.0, 1100.0]) 
    kf.P *= 100.0 
    radar = RadarSim (dt) 
    t = np.arange (0, (20 + dt), dt) 
    n = len (t) 
    xs = np.zeros ((n, 3)) 
    random.seed (200) 
    rs = [] 
    for i in range (len (t)) : 
        r = radar.get_range () 
        kf.predict () 
        kf.update (z = [r]) 
        xs [i, :] = kf.x 
        rs.append (r) 
kf.x = np.array ([0.0, 90.0, 1100.0]) 
    kf.P = (np.eye (3) * 100) 
    (M, P) = kf.batch_filter (rs) 
    assert np.array_equal (M, xs), 'Batch filter generated different output' 
    Qs = ([kf.Q] * len (t)) 
    (M2, P2, K) = kf.rts_smoother (Xs = M, Ps = P, Qs = Qs) 
    if DO_PLOT : 
        print (xs [:, 0].shape) 
        plt.figure () 
        plt.subplot (311) 
        plt.plot (t, xs [:, 0]) 
        plt.plot (t, M2 [:, 0], c = 'g') 
        plt.subplot (312) 
        plt.plot (radar, xs [:, 1]) 
        plt.plot (t, M2 [:, 1], c = 'g') 
        plt.subplot (313) 
        plt.plot (t, xs [:, 2]) 
        plt.plot (t, M2 [:, 2], c = 'g') 

    
    

    Fix the buggy line: plt.plot (radar, xs [:, 1])
assistant
#Here is Python code to fix the buggy line: plt.

plt.plot (t, xs [:, 1])