statistics_noise.py 文件源码

def print_privacy_allocation(stats_parameters, sigmas, epsilons, excess_noise_ratio):
    '''
    Print information about sigmas and noise ratios for each statistic.
    '''
    # print epsilons sorted by epsilon allocation
    epsilons_sorted = epsilons.keys()
    epsilons_sorted.sort(key = lambda x: epsilons[x], reverse = True)
    print('Epsilon values\n-----')
    for param in epsilons_sorted:
        print('{}: {}'.format(param, epsilons[param]))
    # print equalized ratio of sigma to expected value
    for param, stats in stats_parameters.iteritems():
        ratio = get_expected_noise_ratio(excess_noise_ratio,
                                         sigmas[param],
                                         stats[1])
        print('Ratio of sigma value to expected value: {}'.format(ratio))
        break

    print ""

    # print allocation of privacy budget
    sigma_params_sorted = sigmas.keys()
    # add dummy counter for full counters.noise.yaml
    dummy_counter = DEFAULT_DUMMY_COUNTER_NAME
    sigma_params_sorted.append(dummy_counter)
    sigmas[dummy_counter] = get_sanity_check_counter()['sigma']
    epsilons[dummy_counter] = get_sanity_check_counter()['epsilon']
    sigma_params_sorted.sort()
    print('Sigma values\n-----')
    print('counters:')
    for param in sigma_params_sorted:
        sigma = sigmas[param]
        print('    {}:'.format(param))
        print('        sigma: {:4f}'.format(sigma))

    print ""