def test_sigmoid(self):
layer = Layer(3, 2, threshold=0.0, activation='sigmoid')
M_in = np.array([
[-1, 0, 0], [-1, 0, 1], [-1, 1, 0], [-1, 1, 1]
#[-1, 1, 1, 1, 1, 1, 1, 0], # 0
#[-1, 0, 1, 1, 0, 0, 0, 0], # 1
#[-1, 1, 1, 0, 1, 1, 0, 1], # 2
#[-1, 1, 0, 0, 1, 1, 1, 1], # 3
#[-1, 0, 1, 1, 0, 0, 1, 1], # 4
#[-1, 1, 0, 1, 1, 0, 1, 1], # 5
#[-1, 0, 0, 1, 1, 1, 1, 1], # 6
#[-1, 1, 1, 1, 0, 0, 0, 0], # 7
#[-1, 1, 1, 1, 1, 1, 1, 1], # 8
#[-1, 1, 1, 0, 0, 1, 1, 1] # 9
#[-1, 1, 1, 1, 1, 1, 1, 1, 0], # 0
#[-1, 1, 0, 1, 1, 0, 0, 0, 0], # 1
#[-1, 1, 1, 1, 0, 1, 1, 0, 1], # 2
#[-1, 2, 1, 0, 0, 1, 1, 1, 1], # 3
#[-1, 2, 0, 1, 1, 0, 0, 1, 1], # 4
#[-1, 2, 1, 0, 1, 1, 0, 1, 1], # 5
#[-1, 4, 0, 0, 1, 1, 1, 1, 1], # 6
#[-1, 4, 1, 1, 1, 0, 0, 0, 0], # 7
#[-1, 4, 1, 1, 1, 1, 1, 1, 1], # 8
#[-1, 6, 1, 1, 0, 0, 1, 1, 1] # 9
])
v_target = np.array([
[0.1],
[0.3],
[0.6],
[0.9],
#[4],
#[5],
#[6],
#[7],
#[8],
#[9]
])
#m_weights = np.random.rand(layer.num_nodes, layer.num_in)
m_weights = np.full((layer.num_nodes, layer.num_in), 0.0)
layer.init_weights(m_weights)
layer.show("before training", M_in, v_target) # before training
# training
layer.learn_wo_thr(
M_in, # input matrix/vectors
v_target, # output target vector of "or" function
5, # learning rate
)
layer.show("after training", M_in, v_target) # after training
# Test an input vector unknown to the net
arr = np.array([-1, 0.9, 0.1])
print('Testing network with input ', arr, ' : ', layer.run_wo_thr(arr))
return
def test_threshold(self):
Functions.theta = 0.0
layer = Layer(2, 1, threshold=Functions.theta, activation='threshold')
x = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
y = np.array([[1], [0], [1], [0]])
m_weights = np.full((layer.num_nodes, layer.num_in), 0)
layer.init_weights(m_weights)
layer.show("before training", x, y) # before training
# training
layer.learn_w_thr(
x, # input matrix/vectors
y, # output target vector of "or" function
0.1, # learning rate
)
layer.show("after training", x, y) # after training
# Now test an input vector unknown to the net
arr = np.array([-1, 0.2, 0.9])
print('Testing network with input ', arr, ' : ', layer.run_wo_thr(arr))
return
