def test_hopfield_network_get_updated_state(self):
node_number = 2
weight_mat = np.ones(( node_number, node_number))
threshold_vec = np.array([[1, 1]])
init_state = np.array([[1, 1]])
energy = HopfieldNetwork.get_energy_value(weight_mat, threshold_vec,init_state )
assert energy == 0
def test_hopfield_network_get_energy_value(self):
node_number = 2
weight_mat = np.ones(( node_number, node_number))
init_state = np.array([[1, 1]])
updated_state = HopfieldNetwork.get_updated_state(weight_mat, init_state)
assert updated_state.tolist()[0][0] == 1
assert updated_state.tolist()[0][1] == 1
def test_hopfield_network_predict(self):
node_number = 4
threshold = 0
hn = HopfieldNetwork(node_number, threshold)
train_data = [[1, 1, 1, -1], [-1, -1, 1, 1]]
hn.train(train_data)
# アソシアトロン
assert hn.get_updated_state(hn.weight_mat , np.array([[1, 1, 1, -1]])).tolist() == [[1, 1, 1, -1]]
assert hn.get_updated_state(hn.weight_mat , np.array([[-1, -1, 1, 1]])).tolist() == [[-1, -1, 1, 1]]
assert hn.get_updated_state(hn.weight_mat , np.array([[1, 1, -1, -1]])).tolist() == [[1, 1, 1, -1]]
# hopfield
assert hn.predict([1, 1, 1, -1]) == [[1, 1, 1, -1]]
assert hn.predict([-1, -1, 1, 1]) == [[-1, -1, 1, 1]]
assert hn.predict([1, 1, -1, -1]) == [[1, 1, 1, -1]]
def test_hopfield_network_train(self):
node_number = 2
threshold = 0
hn = HopfieldNetwork(node_number, threshold)
train_data = [[1, 1]]
hn.train(train_data)
assert hn.weight_mat.tolist() == [[0, 1], [1, 0]]
hn = HopfieldNetwork(node_number, threshold)
train_data = [[1, -1]]
hn.train(train_data)
assert hn.weight_mat.tolist() == [[0, -1], [-1, 0]]
hn = HopfieldNetwork(node_number, threshold)
train_data = [[-1, 1]]
hn.train(train_data)
assert hn.weight_mat.tolist() == [[0, -1], [-1, 0]]
hn = HopfieldNetwork(node_number, threshold)
train_data = [[-1, -1]]
hn.train(train_data)
assert hn.weight_mat.tolist() == [[0, 1], [1, 0]]
