def test_param_sampler():
    # test basic properties of param sampler
    param_distributions = {"kernel": ["rbf", "linear"],
                           "C": uniform(0, 1)}
    sampler = ParameterSampler(param_distributions=param_distributions,
                               n_iter=10, random_state=0)
    samples = [x for x in sampler]
    assert_equal(len(samples), 10)
    for sample in samples:
        assert_true(sample["kernel"] in ["rbf", "linear"])
        assert_true(0 <= sample["C"] <= 1)

    # test that repeated calls yield identical parameters
    param_distributions = {"C": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]}
    sampler = ParameterSampler(param_distributions=param_distributions,
                               n_iter=3, random_state=0)
    assert_equal([x for x in sampler], [x for x in sampler])

    if sp_version >= (0, 16):
        param_distributions = {"C": uniform(0, 1)}
        sampler = ParameterSampler(param_distributions=param_distributions,
                                   n_iter=10, random_state=0)
        assert_equal([x for x in sampler], [x for x in sampler])
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/model_selection/tests/test_search.py/test_param_sampler/original