test_abc_smc_algorithm.py 文件源码

def test_all_in_one_model(db_path, sampler):
    models = [AllInOneModel() for _ in range(2)]
    population_size = ConstantPopulationSize(800)
    parameter_given_model_prior_distribution = [Distribution(theta=RV("beta",
                                                                      1, 1))
                                                for _ in range(2)]
    abc = ABCSMC(models, parameter_given_model_prior_distribution,
                 MinMaxDistanceFunction(measures_to_use=["result"]),
                 population_size,
                 eps=MedianEpsilon(.1),
                 sampler=sampler)
    abc.new(db_path, {"result": 2})

    minimum_epsilon = .2
    history = abc.run(minimum_epsilon, max_nr_populations=3)
    mp = history.get_model_probabilities(history.max_t)
    assert abs(mp.p[0] - .5) + abs(mp.p[1] - .5) < .08