human
Solve the following python programming problem given the following code:
def test_circle() : 
    from filterpy.kalman import KalmanFilter 
    from math import radians 
    def hx(x) : 
        radius = x [0] 
        angle = x [1] 
        x = (cos (radians (angle)) * radius) 
        y = (sin (radians (angle)) * radius) 
        return np.array ([x, y]) 
def fx(x, dt) : 
        return np.array ([x [0], (x [1] + x [2]), x [2]]) 
std_noise = 0.1 
    sp = JulierSigmaPoints (n = 3, kappa = 0.0) 
    f = UKF (dim_x = 3, dim_z = 2, dt = 0.01, hx = hx, fx = fx, points = kf) 
    f.x = np.array ([50.0, 90.0, 0]) 
    f.P *= 100 
    f.R = (np.eye (2) * (std_noise ** 2)) 
    f.Q = (np.eye (3) * 0.001) 
    f.Q [(0, 0)] = 0 
    f.Q [(2, 2)] = 0 
    kf = KalmanFilter (dim_x = 6, dim_z = 2) 
    kf.x = np.array ([50.0, 0.0, 0, 0, 0.0, 0.0]) 
    F = np.array ([[1.0, 1.0, 0.5, 0.0, 0.0, 0.0], [0.0, 1.0, 1.0, 0.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 1.0, 1.0, 0.5], [0.0, 0.0, 0.0, 0.0, 1.0, 1.0], [0.0, 0.0, 0.0, 0.0, 0.0, 1.0]]) 
    kf.F = F 
    kf.P *= 100 
    kf.H = np.array ([[1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0]]) 
    kf.R = f.R 
    kf.Q [0 : 3, 0 : 3] = Q_discrete_white_noise (3, 1.0, 1e-05) 
    kf.Q [3 : 6, 3 : 6] = Q_discrete_white_noise (3, 1.0, 1e-05) 
    measurements = [] 
    results = [] 
    zs = [] 
    kfxs = [] 
    for t in range (0, 12000) : 
        a = ((t / 30) + 90) 
        x = ((cos (radians (a)) * 50.0) + (randn () * std_noise)) 
        y = ((sin (radians (a)) * 50.0) + (randn () * std_noise)) 
        z = np.array ([x, y]) 
        zs.append (z) 
        f.predict () 
        f.update (z) 
        kf.predict () 
        kf.update (z) 
        results.append (hx (f.x)) 
        kfxs.append (kf.x) 
results = np.asarray (results) 
    zs = np.asarray (zs) 
    kfxs = np.asarray (kfxs) 
    print (results) 
    if DO_PLOT : 
        plt.plot (zs [:, 0], zs [:, 1], c = 'r', label = 'z') 
        plt.plot (results [:, 0], results [:, 1], c = 'k', label = 'UKF') 
        plt.plot (kfxs [:, 0], kfxs [:, 3], c = 'g', label = 'KF') 
     ...

    
    

    Fix the buggy line: f = UKF (dim_x = 3, dim_z = 2, dt = 0.01, hx = hx, fx = fx, points = kf)
assistant
#Here is Python code to fix the buggy line: f = UKF (dim_x = 3, dim_z = 2, dt = 0.

f = UKF (dim_x = 3, dim_z = 2, dt = 0.01, hx = hx, fx = fx, points = sp)