for i in cluster_id:
rvs_id.append(np.where(cluster_mat[:, i] == 1)[0])
rvs_id = np.concatenate(rvs_id, axis=None)
data = well_t[rvs_id, :t]
print(len(rvs_id))
domain = Domain((-4, 4), continuous=True, integral_points=linspace(-4, 4, 30))
kmf = KalmanFilter(domain, np.eye(len(rvs_id)), 1, np.eye(len(rvs_id)), 1)
result = []
for i in range(t):
# i = t - 1
g, rvs_table = kmf.grounded_graph(i + 1, data)
bp = HybridLBP(g, n=50, proposal_approximation='simple')
# bp = GaLBP(g)
print('number of vr', len(g.rvs))
num_evidence = 0
for rv in g.rvs:
if rv.value is not None:
num_evidence += 1
print('number of evidence', num_evidence)
start_time = time.time()
bp.run(6, c2f=0, log_enable=False)
print('time lapse', time.time() - start_time)
# for i in range(t):
temp = []
