human
Solve the following python programming problem given the following code:
def test_batch_missing_data() : 
    ' batch filter should accept missing data with None in the measurements ' 
    def fx(x, dt) : 
        F = np.array ([[1, dt, 0, 0], [0, 1, 0, 0], [0, 0, 1, dt], [0, 0, 0, 1]], dtype = float) 
        return np.dot (F, x) 
def hx(x) : 
        return np.array ([x [0], x [2]]) 
dt = 0.1 
    points = MerweScaledSigmaPoints (4, 0.1, 2.0, (- 1)) 
    kf = UKF (dim_x = 4, dim_z = 2, dt = dt, fx = fx, hx = hx, points = points) 
    kf.x = np.array ([(- 1.0), 1.0, (- 1.0), 1]) 
    kf.P *= 0.0001 
    zs = [] 
    for i in range (20) : 
        z = np.array ([(Ms + (randn () * 0.1)), (i + (randn () * 0.1))]) 
        zs.append (z) 
zs [2] = None 
    Rs = ([1] * len (zs)) 
    Rs [2] = None 
    (Ms, Ps) = kf.batch_filter (zs) 

    
    

    Fix the buggy line: z = np.array ([(Ms + (randn () * 0.1)), (i + (randn () * 0.1))])
assistant
#Here is Python program to fix the buggy line: z = np.

z = np.array ([(i + (randn () * 0.1)), (i + (randn () * 0.1))])