def short_state_trace():
fbhmm = ForwardBackwardHMM(pxk_xkm1, pyk_xk, px0, y_obs_long)
probs, alphas, betas = fbhmm.forward_backward()
probs_eln, logalphas, logbetas = fbhmm.forward_backward_eln()
state_trace = fbhmm.max_likelihood_state_estimate(probs)
eln_state_trace = fbhmm.max_likelihood_state_estimate(probs_eln)
K = [i for i in range(0, len(y_obs_long) + 1)]
plt.plot(K,
state_trace,
marker='+',
markersize='12',
linestyle='-.',
color='b',
linewidth=2,
drawstyle='steps-mid',
label='Regular FB')
plt.plot(K,
eln_state_trace,
marker='x',
markersize='12',
linestyle=':',
color='r',
linewidth=2,
drawstyle='steps-mid',
label='ELN FB')
yint = range(1, 5)
plt.yticks(yint)
plt.legend(handlelength=4, loc='upper right')
plt.title("State transition chart for Long Dataset")
plt.ylabel("State")
plt.xlabel("Xk")
plt.show()
def posterior_chart():
fbhmm = ForwardBackwardHMM(pxk_xkm1, pyk_xk, px0, y_obs_short)
probs, alphas, betas = fbhmm.forward_backward()
print(
tabulate(probs,
headers=[
"K1", "K2", "K3", "K4", "K5", "K6", "K7", "K8", "K9",
"K11", "K11", "K12", "K13", "K14", "K15"
],
tablefmt="latex"))
def posterior_chart():
fbhmm = ForwardBackwardHMM(pxk_xkm1, pyk_xk, px0, y_obs_long)
probs, alphas, betas = fbhmm.forward_backward()
probs = np.concatenate((probs.transpose()[:5], probs.transpose()[-5:]),
axis=0).transpose()
print(
tabulate(probs,
headers=[
"X1", "X2", "X3", "X4", "X5", "X42", "X43", "X44", "X45",
"X46"
],
tablefmt="latex"))
def data_likelihood():
fbhmm = ForwardBackwardHMM(pxk_xkm1, pyk_xk, px0, y_obs_long)
probs, alphas, betas = fbhmm.forward_backward()
print(eln(sum(alphas[:, len(y_obs_long)])))