def test_rica_reconstruct(): X = np.random.standard_normal((10, 2)) X, = theano_floatx(X) rica = Rica(2, 10, code_transfer='softabs', hidden_transfer='identity', loss='squared', c_ica=0.5, max_iter=10) rica.reconstruct(X)
def test_rica_iter_fit(): X = np.random.standard_normal((10, 2)) rica = Rica(2, 10, feature_transfer='softabs', hidden_transfer='identity', loss='squared', c_ica=0.5, max_iter=10) for i, info in enumerate(rica.iter_fit(X)): if i >= 10: break
def test_rica_fit(): X = np.random.standard_normal((10, 2)) rica = Rica(2, 10, feature_transfer='softabs', hidden_transfer='identity', loss='squared', c_ica=0.5, max_iter=10) rica.fit(X)