output = 'results/' + exp_name + '.csv' l_scores = [] for args['set_id'] in range(1, 11): for args['n'] in [1000, 5000]: for args['citcio'] in [False, True]: for args['n_epochs'] in [10, 402]: for args['p'] in [5, 100]: for args['prop_miss'] in [0, 0.1, 0.3]: for args['model'] in ["dlvm", "lrmf"]: t0 = time.time() score = [ihdp_cevae(**args)] args['time'] = int(time.time() - t0) l_scores.append( np.concatenate((list(args.values()), score))) print('ihdp with ', args) print('........... DONE') print('in ', int(args["time"]), ' s \n\n') score_data = pd.DataFrame(l_scores, columns=list(args.keys()) + l_tau) score_data.to_csv(output + '_temp') print('saving ' + exp_name + 'at: ' + output) score_data.to_csv(output) print('*' * 20) print('IHDP with: ' + exp_name + ' succesfully ended.') print('*' * 20)
#range_sig_prior = [0.1, 1, 10] #range_n_epochs = [10, 200, 600] exp_name = 'ihdp_mi' # args['m'] = 10 print('starting exp: ' + exp_name) l_tau = ['tau_dr', 'tau_ols', 'tau_ols_ps'] output = 'results/2019-10-25_' + exp_name + '.csv' l_scores = [] for args['set_id'] in range(1, 11): for args['prop_miss'] in range_prop_miss: t0 = time.time() score = ihdp_mi(**args) args['time'] = int(time.time() - t0) l_scores.append(np.concatenate((list(args.values()), score))) print('ihdp_mi with ', args) print('........... DONE') print('in ', int(args["time"]), ' s \n\n') score_data = pd.DataFrame(l_scores, columns=list(args.keys()) + l_tau) score_data.to_csv(output + '_temp') print('saving ' + exp_name + 'at: ' + output) score_data.to_csv(output) print('*' * 20) print('IHDP with: ' + exp_name + ' succesfully ended.') print('*' * 20)