コード例 #1
0
ファイル: test_space.py プロジェクト: felker/deephyper
def test_normalize_integer():
    for dtype in [
            "int",
            "int8",
            "int16",
            "int32",
            "int64",
            "uint8",
            "uint16",
            "uint32",
            "uint64",
    ]:
        a = Integer(2, 30, transform="normalize", dtype=dtype)
        for X in range(2, 31):
            X_orig = a.inverse_transform(a.transform(X))
            assert_array_equal(X_orig, X)
    for dtype in [
            int,
            np.int8,
            np.int16,
            np.int32,
            np.int64,
            np.uint8,
            np.uint16,
            np.uint32,
            np.uint64,
    ]:
        a = Integer(2, 30, transform="normalize", dtype=dtype)
        for X in range(2, 31):
            X_orig = a.inverse_transform(a.transform(X))
            assert_array_equal(X_orig, X)
            assert isinstance(X_orig, dtype)
コード例 #2
0
ファイル: test_space.py プロジェクト: felker/deephyper
def test_normalize_integer():
    a = Integer(2, 30, transform="normalize")
    for i in range(50):
        check_limits(a.rvs(random_state=i), 2, 30)
    assert_array_equal(a.transformed_bounds, (0, 1))
    rng = np.random.RandomState(0)
    X = rng.randint(2, 31, dtype=np.int64)
    # Check transformed values are in [0, 1]
    assert np.all(a.transform(X) <= np.ones_like(X))
    assert np.all(np.zeros_like(X) <= a.transform(X))

    # Check inverse transform
    X_orig = a.inverse_transform(a.transform(X))
    assert isinstance(X_orig, np.int64)
    assert_array_equal(X_orig, X)

    a = Integer(2, 30, transform="normalize", dtype=int)
    X = rng.randint(2, 31, dtype=int)
    # Check inverse transform
    X_orig = a.inverse_transform(a.transform(X))
    assert isinstance(X_orig, int)

    a = Integer(2, 30, transform="normalize", dtype="int")
    X = rng.randint(2, 31, dtype=int)
    # Check inverse transform
    X_orig = a.inverse_transform(a.transform(X))
    assert isinstance(X_orig, int)

    a = Integer(2,
                30,
                prior="log-uniform",
                base=2,
                transform="normalize",
                dtype=int)
    for i in range(50):
        check_limits(a.rvs(random_state=i), 2, 30)
    assert_array_equal(a.transformed_bounds, (0, 1))

    X = rng.randint(2, 31, dtype=int)
    # Check transformed values are in [0, 1]
    assert np.all(a.transform(X) <= np.ones_like(X))
    assert np.all(np.zeros_like(X) <= a.transform(X))

    # Check inverse transform
    X_orig = a.inverse_transform(a.transform(X))
    assert isinstance(X_orig, int)
    assert_array_equal(X_orig, X)
コード例 #3
0
ファイル: test_space.py プロジェクト: felker/deephyper
def test_integer():
    a = Integer(1, 10)
    for i in range(50):
        r = a.rvs(random_state=i)
        assert 1 <= r
        assert 11 >= r
        assert r in a

    random_values = a.rvs(random_state=0, n_samples=10)
    assert_array_equal(random_values.shape, (10))
    assert_array_equal(a.transform(random_values), random_values)
    assert_array_equal(a.inverse_transform(random_values), random_values)