if '1' in sys.argv[8]:
L1 = True
else:
L1 = False
if 'y' in sys.argv[4]:
model = MLFKTAdaptTransitionDifficultyModel(X, P, intermediate_states, 0, L1)
else:
model = MLFKTAdaptTransitionDifficultyModel(X, P, intermediate_states, 0.1, L1)
mcmc = MCMCSampler(model, 0.15)
burn = int(sys.argv[1])
for c in range(20):
mcmc.burnin(int(math.ceil((burn+0.0) / 20)))
print("finished burn-in #: " + str((c+1)*burn/20))
num_iterations = int(sys.argv[2])
loop = 20
per_loop = int(math.ceil((num_iterations+0.0) / loop))
for c in range(loop):
a = time.time()
mcmc.MH(per_loop)
b = time.time()
print("finished iteration: " + str((c+1)*per_loop) + " in " + str(int(b-a)) + " seconds")
end = time.time()
print("Finished burnin and " + str(num_iterations) + " iterations in " + str(int(end-start)) + " seconds.")
