test_ndlib.py 文件源码

def test_optional_parameters(self):
        g = nx.erdos_renyi_graph(1000, 0.1)
        model = th.ThresholdModel(g)
        config = mc.Configuration()
        config.add_model_parameter('percentage_infected', 0.1)
        model.set_initial_status(config)
        iterations = model.iteration_bunch(10)
        config.add_node_set_configuration("test", {n: 1 for n in g.nodes()})
        config.add_edge_set_configuration("etest", {e: 1 for e in g.edges()})

        self.assertEqual(len(iterations), 10)

        model = ks.KerteszThresholdModel(g)
        config = mc.Configuration()
        config.add_model_parameter('adopter_rate', 0.4)
        predefined_blocked = [0, 1, 2, 3, 4, 5]
        config.add_model_initial_configuration("Blocked", predefined_blocked)
        config.add_model_parameter('percentage_infected', 0.1)
        model.set_initial_status(config)
        iteration = model.iteration()
        blocked = [x for x, v in future.utils.iteritems(iteration["status"]) if v == -1]
        self.assertEqual(blocked, predefined_blocked)

        model = ids.IndependentCascadesModel(g)
        config = mc.Configuration()
        config.add_model_parameter('percentage_infected', 0.1)
        model.set_initial_status(config)
        iterations = model.iteration_bunch(10)
        self.assertEqual(len(iterations), 10)

        model = pr.ProfileModel(g)
        config = mc.Configuration()
        config.add_model_parameter('percentage_infected', 0.1)
        model.set_initial_status(config)
        iterations = model.iteration_bunch(10)
        self.assertEqual(len(iterations), 10)

        model = pt.ProfileThresholdModel(g)
        config = mc.Configuration()
        config.add_model_parameter('percentage_infected', 0.1)
        model.set_initial_status(config)
        iterations = model.iteration_bunch(10)
        self.assertEqual(len(iterations), 10)

        model = th.ThresholdModel(g)
        config = mc.Configuration()
        config.add_model_parameter('percentage_infected', 0.1)
        model.set_initial_status(config)
        iterations = model.iteration_bunch(10)
        self.assertEqual(len(iterations), 10)

        model = ks.KerteszThresholdModel(g)
        config = mc.Configuration()
        config.add_model_parameter('adopter_rate', 0.4)
        config.add_model_parameter('percentage_blocked', 0.1)
        config.add_model_parameter('percentage_infected', 0.1)
        model.set_initial_status(config)
        iterations = model.iteration_bunch(10)
        self.assertEqual(len(iterations), 10)