def METHOD_NAME(k):
    k = k[np.argsort(k.prod(1))]  # sort small to large
    x, best = metric(k, wh0)
    bpr, aat = (best > thr).float().mean(), (x > thr).float().mean() * n  # best possible recall, anch > thr
    print(f'{prefix}thr={thr:.2f}: {bpr:.4f} best possible recall, {aat:.2f} anchors past thr')
    print(f'{prefix}n={n}, img_size={img_size}, metric_all={x.mean():.3f}/{best.mean():.3f}-mean/best, '
          f'past_thr={x[x > thr].mean():.3f}-mean: ', end='')
    for i, x in enumerate(k):
        print('%i,%i' % (round(x[0]), round(x[1])), end=',  ' if i < len(k) - 1 else '\n')  # use in *.cfg
    return k