<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def ckf_transform(Xs, Q):
 """ Compute mean and covariance of array of cubature points. Parameters Xs : ndarray Cubature points Q : ndarray Noise covariance Returns ------- mean : ndarray mean of the cubature points variance: ndarray covariance matrix of the cubature points """


    m, n = Xs.shape

    x = sum(Xs, 0)[:, None] / m
    P = np.zeros((n, n))
    xf = x.flatten()
    for k in range(m):
        P += np.outer(Xs[k], Xs[k]) - np.outer(xf, xf)

    P *= 1 / m
    P += Q

    return x, P