问题描述
我怎样才能有效地选择一个随机元素的std ::设为？
How can I efficiently select a random element from a std::set?
A 的std ::设置：迭代是双向迭代器。所以我不能直接指数随机选取的元素像我所能为的std :: deque的或的std ::矢量
A std::set::iterator is a bidirectional iterator. So I can't directly index a randomly chosen element like I could for a std::deque or std::vector
我的可以的采取从迭代器返回的std ::设置::开始（）并加一 0 到的std ::设置::大小（） - 1 次，但似乎做了很多不必要的工作。对于指数接近设定的大小，我最终会遍历树的整个上半场，即使它已经知道的元素不会被发现在那里。
I could take the iterator returned from std::set::begin() and increment it 0 to std::set::size()-1 times, but that seems to be doing a lot of unnecessary work. For an "index" close to the set's size, I would end up traversing the entire first half of the tree, even though it's already known the element won't be found there.
有没有更好的方法？
在效率的名义，我愿意来定义随机为的随机的的比什么方法，我可能会用选择随机指标的载体。称之为合理的随机。
In the name of efficiency, I am willing to define "random" as less random than whatever approach I might have used to choose a random index in a vector. Call it "reasonably random".
修改...
下面许多有见地的答案。
Many insightful answers below.
短的版本是，即使你能找到的的具体的中的的log（n）的时候，你无法找到的任意在这段时间通过的std ::设为界面元素。
The short version is that even though you can find a specific element in log(n) time, you can't find an arbitrary element in that time through the std::set interface.
推荐答案
使用的来代替：
Use boost::container::flat_set instead:
boost::container::flat_set<int> set;
// ...
auto it = set.begin() + rand() % set.size();
插入和缺失成为O（N）不过，我不知道这是一个问题。你还有为O（log N）的查找，而事实上，该容器是连续的给出了一个全面改善，往往胜过邻损失（日志N）的插入和删除。
Insertions and deletions become O(N) though, I don't know if that's a problem. You still have O(log N) lookups, and the fact that the container is contiguous gives an overall improvement that often outweighs the loss of O(log N) insertions and deletions.
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