def test_add(self):
        prio_set_list = event._PrioritizedSetList()
        objs = [(i,) for i in range(5)]

        prio_set_list.add(0, objs[0])
        assert prio_set_list.list == [(0, {objs[0]})]

        prio_set_list.add(0, objs[1])
        assert prio_set_list.list == [(0, {objs[0], objs[1]})]

        prio_set_list.add(10, objs[2])
        assert prio_set_list.list == [(10, {objs[2]}),
                                      (0,  {objs[0], objs[1]})]

        prio_set_list.add(-10, objs[3])
        assert prio_set_list.list == [( 10, {objs[2]}),           # noqa: E201
                                      (  0, {objs[0], objs[1]}),  # noqa: E201
                                      (-10, {objs[3]})]
        prio_set_list.add(-1, objs[4])
        assert prio_set_list.list == [( 10, {objs[2]}),           # noqa: E201
                                      (  0, {objs[0], objs[1]}),  # noqa: E201
                                      ( -1, {objs[4]}),           # noqa: E201
                                      (-10, {objs[3]})]
def __calculate_initial_covariances(self, initial_clusters):
        covariances = []
        for initial_cluster in initial_clusters:
            if len(initial_cluster) > 1:
                cluster_sample = [self.__sample[index_point] for index_point in initial_cluster]
                covariances.append(numpy.cov(cluster_sample, rowvar=False))
            else:
                dimension = len(self.__sample[0])
                covariances.append(numpy.zeros((dimension, dimension)) + random.random() / 10.0)