# initializing sampling method
if sampling_method == 'mmh':
sampler = mmh.ModifiedMetropolisHastings(sample_marg_PDF_list, f_marg_PDF_list, 'gaussian', Nb)
elif sampling_method == 'cs':
sampler = cs.CondSampling(sample_marg_PDF_list, 0.8, Nb)
# initialization
pf_list = []
theta_list = []
g_list = []
m_list = []
start_time = timer.time()
for sim in range(0, n_simulations):
pf_hat, theta_temp, g_temp, acc_rate, m_array = \
mp.mp_with_seed_selection(N, LSF, sampler, sample_marg_PDF_list, seed_selection_strategy)
# transform samples back from u to x-space
# for j in range(0, len(theta_temp)):
# theta_temp[j] = transform_U2X(theta_temp[j])
# save simulation in list
pf_list.append(pf_hat)
g_list.append(g_temp)
theta_list.append(theta_temp)
m_list.append(m_array)
uutil.print_simulation_progress(sim, n_simulations, start_time)
if sampling_method == 'mmh':
sampler = mmh.ModifiedMetropolisHastings(sample_marg_PDF_list,
f_marg_PDF_list, 'gaussian',
burnin)
elif sampling_method == 'cs':
sampler = cs.CondSampling(sample_marg_PDF_list, 0.8, burnin)
# initialization
pf_list = []
theta_list = []
g_list = []
m_list = []
start_time = timer.time()
for sim in range(0, n_simulations):
pf_hat, theta_temp, g_temp, acc_rate, m_array = mp.mp_with_seed_selection(
N, LSF, sampler, sample_marg_PDF_list, seed_selection_strategy)
# save simulation in list
pf_list.append(pf_hat)
g_list.append(g_temp)
theta_list.append(theta_temp)
m_list.append(m_array)
uutil.print_simulation_progress(sim, n_simulations, start_time)
pf_sim_array = np.asarray(pf_list)
pf_mean = np.mean(pf_sim_array)
pf_sigma = np.std(pf_sim_array)
# ---------------------------------------------------------------------------
# RESULTS
# ---------------------------------------------------------------------------
