test_graph_lasso.py 文件源码

def test_graph_lasso_iris():
    # Hard-coded solution from R glasso package for alpha=1.0
    # The iris datasets in R and sklearn do not match in a few places, these
    # values are for the sklearn version
    cov_R = np.array([
        [0.68112222, 0.0, 0.2651911, 0.02467558],
        [0.00, 0.1867507, 0.0, 0.00],
        [0.26519111, 0.0, 3.0924249, 0.28774489],
        [0.02467558, 0.0, 0.2877449, 0.57853156]
        ])
    icov_R = np.array([
        [1.5188780, 0.0, -0.1302515, 0.0],
        [0.0, 5.354733, 0.0, 0.0],
        [-0.1302515, 0.0, 0.3502322, -0.1686399],
        [0.0, 0.0, -0.1686399, 1.8123908]
        ])
    X = datasets.load_iris().data
    emp_cov = empirical_covariance(X)
    for method in ('cd', 'lars'):
        cov, icov = graph_lasso(emp_cov, alpha=1.0, return_costs=False,
                                mode=method)
        assert_array_almost_equal(cov, cov_R)
        assert_array_almost_equal(icov, icov_R)