test_algorithms.py 文件源码

def test_ica(eng):
    t = linspace(0, 10, 100)
    s1 = sin(t)
    s2 = square(sin(2*t))
    x = c_[s1, s2, s1+s2]
    random.seed(0)
    x += 0.001*random.randn(*x.shape)
    x = fromarray(x, engine=eng)

    def normalize_ICA(s, aT):
        a = aT.T
        c = a.sum(axis=0)
        return s*c, (a/c).T

    from sklearn.decomposition import FastICA
    ica = FastICA(n_components=2, fun='cube', random_state=0)
    s1 = ica.fit_transform(x.toarray())
    aT1 = ica.mixing_.T
    s1, aT1 = normalize_ICA(s1, aT1)

    s2, aT2 = ICA(k=2, svd_method='direct', max_iter=200, seed=0).fit(x)
    s2, aT2 = normalize_ICA(s2, aT2)
    tol=1e-1
    assert allclose_sign_permute(s1, s2, atol=tol)
    assert allclose_sign_permute(aT1, aT2, atol=tol)