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)