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)