def test_initialize_reservoir(self):
w1 = EchoStateNetwork.initialize_reservoir(10, 0.1, self.rs1, 1.0, 1.0)
self.assertAlmostEqual(1.0, max(abs(eigs(w1)[0])))
w2 = EchoStateNetwork.initialize_reservoir(10, 0.1, self.rs1, 1.0, 5.0)
self.assertAlmostEqual(5.0, max(abs(eigs(w2)[0])))
w3 = EchoStateNetwork.initialize_reservoir(10, 0.1, self.rs1, 1.0, 0.1)
self.assertAlmostEqual(0.1, max(abs(eigs(w3)[0])))
def __init__(self, input_size, output_size,
reservoir_size = 300,
spectral_radius = 1.25,
leaking_rate = 0.3,
linear_model = None,
average_nb_connexions = None,
use_feedback = False,
use_raw_input = True,
feedback_scaling = 1.,
input_scaling = 1.,
output_activation_function = None,
output_activation_inverse_function = None,
reservoir_noise_scaling = 0.,
input_sparsity = 1.,
ridge_coef = 1e-6):
EchoStateNetwork.__init__(self, input_size, output_size,
reservoir_size = reservoir_size,
spectral_radius = spectral_radius,
leaking_rate = leaking_rate,
linear_model = linear_model,
average_nb_connexions = average_nb_connexions,
use_feedback = use_feedback,
use_raw_input = use_raw_input,
feedback_scaling = feedback_scaling,
input_scaling = input_scaling,
output_activation_function = output_activation_function,
output_activation_inverse_function = output_activation_inverse_function,
reservoir_noise_scaling = reservoir_noise_scaling,
input_sparsity = input_sparsity)
self.ridge_coef = ridge_coef
self.reset_correlation_matrix()
def test_initialize_weights(self):
w1 = EchoStateNetwork.initialize_weights(10, 10, 0.1, self.rs1, 1.0)
w2 = EchoStateNetwork.initialize_weights(10, 10, 0.1, self.rs2, 1.0)
assert_allclose(w1.toarray(), w2.toarray())
self.assertLessEqual(np.amax(w1.data), 1.0)
self.assertGreaterEqual(np.amin(w1.data), -1.0)
w3 = EchoStateNetwork.initialize_weights(10, 10, 0.1, self.rs1, 5.0)
self.assertLessEqual(np.amax(w3.data), 5.0)
self.assertGreaterEqual(np.amin(w3.data), -5.0)
self.assertLess(np.amin(w3.data), -1.0)
self.assertGreater(np.amax(w3.data), 1.0)
