def getLoglik():
if len(z[0]) < 4: return np.zeros(((0))), np.zeros(((0)))
_z, _logpxz = hmc.combine_samples(z[0], logpxz[0])
ll, ll_var = hmc.estimate_mcmc_likelihood(_z, _logpxz, len(z[0]))
z[0] = []
logpxz[0] = []
return ll, ll_var
def est_ll(w, mean=False):
for _ in range(n_burnin):
doLeap(w)
z_list = []
logpxz_list = []
for _ in range(n_leaps):
logpxz = doLeap(w)
z_list.append(z_mcmc.copy())
logpxz_list.append(logpxz.copy())
_z, _logpxz = hmc.combine_samples(z_list, logpxz_list)
ll, var = estimate_mcmc_likelihood(_z, _logpxz, len(z_list), method=method)
if mean: return ll.mean(), var.mean()
return ll, var
