# 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 # ---------------------------------------------------------------------------