validate.py 文件源码

def kf_sim(sim):
    """
    Process each simulation trial generated with
    :func:`setup_random_test` with a Kalman filter and return the
    posterior state estimates and error covariances.
    """
    post = defaultdict(dict)
    for l in range(sim['L']):
        x_hat_l, P_l = kalman_filter(sim[l]['y'],
                                     sim['H'],
                                     sim['R'],
                                     sim['F'],
                                     sim['Q'],
                                     sim['mu'],
                                     sim['PI'])
        post[l]['x_hat'] = x_hat_l
        if l == 0:
            post['P'] = P_l
        post[l]['error'] = []
        for x_i, x_hat_i in izip(sim[l]['x'], post[l]['x_hat']):
            post[l]['error'].append(x_hat_i - x_i)
    return post