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 = []
