Python GP.freeze_all_parametersの例

コード例 #1

ファイル: test_modeling.py プロジェクト: dfm/george

def test_bounds():
    kernel = 10 * kernels.ExpSquaredKernel(1.0, metric_bounds=[(None, 4.0)])
    kernel += 0.5 * kernels.RationalQuadraticKernel(log_alpha=0.1, metric=5.0)
    gp = GP(kernel, white_noise=LinearWhiteNoise(1.0, 0.1))

    # Test bounds length.
    assert len(gp.get_parameter_bounds()) == len(gp.get_parameter_vector())
    gp.freeze_all_parameters()
    gp.thaw_parameter("white_noise:m")
    assert len(gp.get_parameter_bounds()) == len(gp.get_parameter_vector())

    # Test invalid bounds specification.
    with pytest.raises(ValueError):
        kernels.ExpSine2Kernel(gamma=0.1, log_period=5.0, bounds=[10.0])

コード例 #2

def test_bounds():
    kernel = 10 * kernels.ExpSquaredKernel(1.0, metric_bounds=[(None, 4.0)])
    kernel += 0.5 * kernels.RationalQuadraticKernel(log_alpha=0.1, metric=5.0)
    gp = GP(kernel, white_noise=LinearWhiteNoise(1.0, 0.1))

    # Test bounds length.
    assert len(gp.get_parameter_bounds()) == len(gp.get_parameter_vector())
    gp.freeze_all_parameters()
    gp.thaw_parameter("white_noise:m")
    assert len(gp.get_parameter_bounds()) == len(gp.get_parameter_vector())

    # Test invalid bounds specification.
    with pytest.raises(ValueError):
        kernels.ExpSine2Kernel(gamma=0.1, log_period=5.0, bounds=[10.0])

コード例 #3

ファイル: test_modeling.py プロジェクト: dfm/george

def test_parameters():
    kernel = 10 * kernels.ExpSquaredKernel(1.0)
    kernel += 0.5 * kernels.RationalQuadraticKernel(log_alpha=0.1, metric=5.0)
    gp = GP(kernel, white_noise=LinearWhiteNoise(1.0, 0.1))

    n = len(gp.get_parameter_vector())
    assert n == len(gp.get_parameter_names())
    assert n - 2 == len(kernel.get_parameter_names())

    gp.freeze_parameter(gp.get_parameter_names()[0])
    assert n - 1 == len(gp.get_parameter_names())
    assert n - 1 == len(gp.get_parameter_vector())

    gp.freeze_all_parameters()
    assert len(gp.get_parameter_names()) == 0
    assert len(gp.get_parameter_vector()) == 0

    gp.kernel.thaw_all_parameters()
    gp.white_noise.thaw_all_parameters()
    assert n == len(gp.get_parameter_vector())
    assert n == len(gp.get_parameter_names())

    assert np.allclose(kernel[0], np.log(10.))

コード例 #4

def test_parameters():
    kernel = 10 * kernels.ExpSquaredKernel(1.0)
    kernel += 0.5 * kernels.RationalQuadraticKernel(log_alpha=0.1, metric=5.0)
    gp = GP(kernel, white_noise=LinearWhiteNoise(1.0, 0.1))

    n = len(gp.get_parameter_vector())
    assert n == len(gp.get_parameter_names())
    assert n - 2 == len(kernel.get_parameter_names())

    gp.freeze_parameter(gp.get_parameter_names()[0])
    assert n - 1 == len(gp.get_parameter_names())
    assert n - 1 == len(gp.get_parameter_vector())

    gp.freeze_all_parameters()
    assert len(gp.get_parameter_names()) == 0
    assert len(gp.get_parameter_vector()) == 0

    gp.kernel.thaw_all_parameters()
    gp.white_noise.thaw_all_parameters()
    assert n == len(gp.get_parameter_vector())
    assert n == len(gp.get_parameter_names())

    assert np.allclose(kernel[0], np.log(10.))