def baseline_re_batch_analysis(test_data_id, Ns, cap=10):
    '\n    Runs baseline_re_single_analysis on all networks in test_data_id of size N.\n    cap is as in baseline_re_single_analysis.\n    returns numpy.array percents, where\n      percents[i] is as in baseline_re_single_analysis for the i^{th} sample network.\n    '
    percents = []
    (network_sizes, num_samples, _) = fe.load_test_data(('%s.npz' % test_data_id))
    for (N, S) in zip(network_sizes, num_samples):
        if (N not in Ns):
            continue
        for samp in range(S):
            percents.append(baseline_re_single_analysis(test_data_id, N, samp, cap=cap))
    percents = np.array(percents)
    print(('mean %%: %f%%' % percents.mean()))
Runs baseline_re_single_analysis on all networks in test_data_id of size N.
cap is as in baseline_re_single_analysis.
returns numpy.array percents, where
  percents[i] is as in baseline_re_single_analysis for the i^{th} sample network.
def baseline_re_batch_analysis(test_data_id, Ns, cap=10):
    '\n    Runs baseline_re_single_analysis on all networks in test_data_id of size N.\n    cap is as in baseline_re_single_analysis.\n    returns numpy.array percents, where\n      percents[i] is as in baseline_re_single_analysis for the i^{th} sample network.\n    '
    percents = []
    (network_sizes, num_samples, _) = fe.load_test_data(('%s.npz' % test_data_id))
    for (N, S) in zip(network_sizes, num_samples):
        if (N not in Ns):
            continue
        for samp in range(S):
            percents.append(baseline_re_single_analysis(test_data_id, N, samp, cap=cap))
    percents = np.array(percents)
    print(('mean %%: %f%%' % percents.mean()))