tools.py 文件源码

def approx_stabilities(instance, num, reps, random_instance=RandomState()):
    """
    This function approximates the stability of the given `instance` for
    `num` challenges evaluating it `reps` times per challenge. The stability
    is the probability that the instance gives the correct response when
    evaluated.
    :param instance: pypuf.simulation.base.Simulation
                     The instance for the stability approximation
    :param num: int
                Amount of challenges to be evaluated
    :param reps: int
                 Amount of repetitions per challenge
    :return: array of float
             Array of the stabilities for each challenge
    """

    challenges = sample_inputs(instance.n, num, random_instance)
    responses = zeros((reps, num))
    for i in range(reps):
        challenges, unpacked_challenges = itertools.tee(challenges)
        responses[i, :] = instance.eval(array(list(unpacked_challenges)))
    return 0.5 + 0.5 * np_abs(np_sum(responses, axis=0)) / reps