t_max = 100 #total epochs
trainX, trainY, testX, testY = read_file("xi(1).csv", "tau(1).csv", P, Q)
model = Model(input_size=len(trainX[0]))
model.add_layer(states=2, activation='tanh', fixed_weights=False)
model.add_layer(states=1, activation=None, fixed_weights=1)
# model.display()
# print(trainX.shape)
initial_weights, final_weights = model.train(trainX,
trainY,
testX,
testY,
ephochs=t_max,
learning_rate=learning_rate,
return_weights=True,
verbose=False)
# print(initial_weights)
# print("\n==========================================\n")
# print(final_weights)
for w in range(0, initial_weights.shape[0]):
fig, axs = plt.subplots(2)
axs[0].bar(np.arange(initial_weights[w].size), initial_weights[w])
axs[0].set_title('Initial w_' + str(w) + 'weight vector')
axs[0].set_ylabel('value')
Es = []
E_tests = []
for i in range(0, R):
print("Run " + str(i + 1) + " of " + str(R))
model = Model(input_size=len(trainX[0]))
model.add_layer(states=2, activation='tanh', fixed_weights=False)
model.add_layer(states=1, activation=None, fixed_weights=1)
# model.display()
# print(trainX.shape)
E, E_test = model.train(trainX,
trainY,
testX,
testY,
ephochs=t_max,
learning_rate=learning_rate)
Es.append(E)
E_tests.append(E_test)
average_E = np.average(Es, axis=0)
average_Etest = np.average(E_tests, axis=0)
plt.plot(average_E, label="Empirical Error(E)")
plt.title("Error-Time Graph")
plt.plot(average_Etest, label="Validation Error(E_test)")
plt.xlabel('Time')
plt.ylabel('Averaged Error')
trainX, trainY, testX, testY = read_file("real world dataset/xzscore.csv",
"real world dataset/tshift.csv",
P,
Q,
shuffle=True)
# print(trainX.size)
model = Model(input_size=len(trainX[0]))
model.add_layer(states=2, activation='tanh', fixed_weights=False)
model.add_layer(states=1, activation=None, fixed_weights=1 / 4)
E, E_test = model.train(trainX,
trainY,
testX,
testY,
ephochs=t_max,
learning_rate=learning_rate,
verbose=False)
# model.display()
plt.plot(E, label="Empirical Error(E)")
plt.title("Error-Time Graph")
plt.plot(E_test, label="Validation Error(E_test)")
plt.xlabel('Time')
plt.ylabel('Error')
plt.legend()