def __process_evaluated_metric(y1_true, y0_true, y1_hat, y0_hat,
ite_dict, true_ITE_list, predicted_ITE_list, ite_csv_path, iter_id):
y1_true_np = np.array(y1_true)
y0_true_np = np.array(y0_true)
y1_hat_np = np.array(y1_hat)
y0_hat_np = np.array(y0_hat)
PEHE = Metrics.PEHE(y1_true_np, y0_true_np, y1_hat_np, y0_hat_np)
ATE = Metrics.ATE(y1_true_np, y0_true_np, y1_hat_np, y0_hat_np)
print("PEHE: {0}".format(PEHE))
print("ATE: {0}".format(ATE))
true_ATE = sum(true_ITE_list) / len(true_ITE_list)
predicted_ATE = sum(predicted_ITE_list) / len(predicted_ITE_list)
Utils.write_to_csv(ite_csv_path.format(iter_id), ite_dict)
return PEHE, ATE, true_ATE, predicted_ATE