print('completed %d: mean %d and se %d' % (d, mean, se))
                pickle.dump(
                    instance_list,
                    open(os.path.join(data_dir, "static_" + str(d) + ".p"),
                         "wb"))
            except:
                print('error')

        pool.close()
        pool.join()

    # ORACLE
    if 'oracle' in arguments:
        np.random.seed(43)
        instance_list = [
            XY_ORACLE(X, theta_star, delta, Z) for i in range(count)
        ]
        seed_list = list(np.random.randint(0, 100000, count))
        parallel_sim = functools.partial(sim_wrapper, instance_list, seed_list)
        pool = multiprocess.Pool(5)
        num_list = list(range(count))

        instance_list = []
        for instance in pool.imap_unordered(parallel_sim, num_list):
            try:
                instance_list.append(instance)
                print('Finished ORACLE Instance')
                sample_complexity = np.array(
                    [instance.N for instance in instance_list])
                mean = np.mean(sample_complexity)
                se = np.std(sample_complexity) / np.sqrt(count)
                print('completed %d: mean %d and se %d' % (d, mean, se))
                pickle.dump(
                    instance_list,
                    open(os.path.join(data_dir, "static_" + str(n) + ".p"),
                         "wb"))
            except:
                print('error')

        pool.close()
        pool.join()

    # ORACLE
    if 'oracle' in arguments:
        np.random.seed(43)
        instance_list = [
            XY_ORACLE(X, theta_star, delta)
            for X, theta_star in zip(X_set, theta_star_set)
        ]
        seed_list = list(np.random.randint(0, 100000, count))
        parallel_sim = functools.partial(sim_wrapper, instance_list, seed_list)
        pool = multiprocess.Pool(pool_num)
        num_list = list(range(count))
        instance_list = []
        for instance in pool.imap_unordered(parallel_sim, num_list):
            try:
                instance_list.append(instance)

                print('Finished Oracle Instance')
                sample_complexity = np.array(
                    [instance.N for instance in instance_list])
                mean = np.mean(sample_complexity)
Exemplo n.º 3
0
    #             print('completed %d: mean %d and se %d' % (d, mean, se))
    #
    #             f = open(
    #                 os.path.join(data_dir, "static_" + str(d) + ".p"), "wb")
    #             pickle.dump(instance_list, f)
    #             f.close()
    #         except:
    #             print('error')
    #
    #     pool.close()
    #     pool.join()
    #
    # ORACLE
    if 'oracle' in arguments:
        np.random.seed(43)
        instance_list = [XY_ORACLE(X, theta_star, delta) for i in range(count)]
        seed_list = list(np.random.randint(0, 100000, count))
        parallel_sim = functools.partial(sim_wrapper, instance_list, seed_list)
        pool = multiprocess.Pool(pool_num)
        num_list = list(range(count))
        instance_list = []
        for instance in pool.imap_unordered(parallel_sim, num_list):
            try:
                instance_list.append(instance)

                print('Finished Oracle Instance')
                sample_complexity = np.array(
                    [instance.N for instance in instance_list])
                mean = np.mean(sample_complexity)
                se = np.std(sample_complexity) / np.sqrt(count)
Exemplo n.º 4
0
             mean = np.mean(sample_complexity)
             se = np.std(sample_complexity)/np.sqrt(count)
             pickle.dump((mean, se), open(os.path.join(data_dir, "static_" + str(n) + "_data.p"), "wb"))
             print('completed %d: mean %d and se %d' % (n, mean, se))
             pickle.dump(instance_list, open(os.path.join(data_dir, "static_" + str(n) + ".p"), "wb"))
         except:
             print('error')
     
     pool.close()
     pool.join()  
     
     
 # ORACLE
 if 'oracle' in arguments:
     np.random.seed(43)
     instance_list = [XY_ORACLE(X, theta_star, delta) for X, theta_star in zip(X_set, theta_star_set)]
     seed_list = list(np.random.randint(0, 100000, count))
     parallel_sim = functools.partial(sim_wrapper, instance_list, seed_list)
     pool = multiprocess.Pool(pool_num)
     num_list = list(range(count))
     
     instance_list = []
     for instance in pool.imap_unordered(parallel_sim, num_list):
         try:
             instance_list.append(instance)
             print('Finished ORACLE Instance')
             sample_complexity = np.array([instance.N for instance in instance_list])
             mean = np.mean(sample_complexity)
             se = np.std(sample_complexity)/np.sqrt(count)
             pickle.dump((mean, se), open(os.path.join(data_dir, "oracle_" + str(n) + "_data.p"), "wb"))
             print('completed %d: mean %d and se %d' % (n, mean, se))