lstm_stacked_mses = [] bar = ProgressBar() for s in bar(range(num_sims)): #x_0 = np.random.normal(0, x_var, 1) x_0 = np.array([0]) sim = UNGM(x_0, R, Q, x_var) ukf = UKF(sim.f, sim.F, sim.h, sim.H, sim.Q, sim.R, 5., first_x_0, 1) ekf = EKF(sim.f, sim.F, sim.h, sim.H, sim.Q, sim.R, first_x_0, 1) for t in range(T): x, y = sim.process_next() ukf.predict() ukf.update(y) ekf.predict() ekf.update(y) ukf_mses.append(MSE(ukf.get_all_predictions(), sim.get_all_x())) ekf_mses.append(MSE(ekf.get_all_predictions(), sim.get_all_x())) all_x.append(np.array(sim.get_all_x())) all_y.append(np.array(sim.get_all_y())) X = np.array(all_y)[:, :-1, :] y = np.array(all_x)[:, 1:, :] lstm10_pred = lstm10.predict(X) lstm100_pred = lstm100.predict(X) rnn10_pred = rnn10.predict(X) rnn100_pred = rnn100.predict(X) lstm10_mses = [] lstm100_mses = [] rnn10_mses = []