使用 STL 按会员订购集装箱

发布于 2024-09-12 01:39:22 字数 708 浏览 2 评论 0 原文

假设我有一些数据存储在 unique_ptr 的容器中：

struct MyData {
    int id;  // a unique id for this particular instance
    data some_data; // arbitrary additional data
};

// ...

std::vector<std::unique_ptr<MyData>> my_data_vec;

my_data_vec 的顺序很重要。假设现在我有另一个 MyDatas ID 向量：

std::vector<int> my_data_ids;

我现在想要重新排列 my_data_vec ，使元素按照 my_data_ids 指定的顺序排列。（不要忘记移动 unique_ptr 需要使用 std::move() 进行移动语义。）

实现此目的最有效的算法方法是什么，并执行以下任一操作： STL 算法很适合实现这一目标？我看不出 std::sort 有任何帮助。

编辑：我可以使用 O(n) 内存空间（不太担心内存），但 ID 是任意的（在我的具体情况下，它们实际上是随机生成的）。

原文

Suppose I have some data stored in a container of unique_ptrs:

struct MyData {
    int id;  // a unique id for this particular instance
    data some_data; // arbitrary additional data
};

// ...

std::vector<std::unique_ptr<MyData>> my_data_vec;

The ordering of my_data_vec is important. Suppose now I have another vector of IDs of MyDatas:

std::vector<int> my_data_ids;

I now want to rearrange my_data_vec such that the elements are in the sequence specified by my_data_ids. (Don't forget moving a unique_ptr requires move-semantics with std::move().)

What's the most algorithmically efficient way to achieve this, and do any of the STL algorithms lend themselves well to achieving this? I can't see that std::sort would be any help.

Edit: I can use O(n) memory space (not too worried about memory), but the IDs are arbitrary (in my specific case they are actually randomly generated).

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喜爱纠缠 2024-09-19 01:39:22

创建一个映射，将 id 映射到 my_data_ids 中的索引。
创建一个函数对象，根据其 ID 在该映射中的索引来比较 std::unique_ptr。
使用 std::sort 使用该函数对象对 my_data_vec 进行排序。

这是一个示意图：

// Beware, brain-compiled code ahead!
typedef std::vector<int> my_data_ids_type;
typedef std::map<int,my_data_ids_type::size_type> my_data_ids_map_type;

class my_id_comparator : public std::binary_function< bool
                                                    , std::unique_ptr<MyData>
                                                    , std::unique_ptr<MyData> > {
public:
  my_id_comparator(const my_data_ids_map_type& my_data_ids_map)
    : my_data_ids_map_(my_data_ids_map) {}

  bool operator()( const std::unique_ptr<MyData>& lhs
                 , const std::unique_ptr<MyData>& rhs ) const
  {
     my_data_ids_map_type::const_iterator it_lhs = my_data_ids_map_.find(lhs.id);
     my_data_ids_map_type::const_iterator it_rhs = my_data_ids_map_.find(rhs.id);
     if( it_lhs == my_data_ids_map_.end() || it_rhs == my_data_ids_map_.end() )
       throw "dammit!"; // whatever
     return it_lhs->second < it_rhs->second;
  }
private
  my_data_ids_map_type& my_data_ids_map_;
};

//...

my_data_ids_map_type my_data_ids_map;
// ...
// populate my_data_ids_map with the IDs and their indexes from my_data_ids
// ...
std::sort( my_data_vec.begin(), my_data_vec.end(), my_id_comparator(my_data_ids_map) );

如果内存不足，但时间并不重要，您可以放弃映射并在每次比较时在 my_data_ids 向量中搜索 ID。但是，您必须非常需要内存才能做到这一点，因为每次比较两个线性复杂的操作将非常昂贵。

Create a map that maps ids to their index in my_data_ids.
Create a function object that compares std::unique_ptr<MyData> based on their ID's index in that map.
Use std::sort to sort the my_data_vec using that function object.

Here's a sketch of this:

// Beware, brain-compiled code ahead!
typedef std::vector<int> my_data_ids_type;
typedef std::map<int,my_data_ids_type::size_type> my_data_ids_map_type;

class my_id_comparator : public std::binary_function< bool
                                                    , std::unique_ptr<MyData>
                                                    , std::unique_ptr<MyData> > {
public:
  my_id_comparator(const my_data_ids_map_type& my_data_ids_map)
    : my_data_ids_map_(my_data_ids_map) {}

  bool operator()( const std::unique_ptr<MyData>& lhs
                 , const std::unique_ptr<MyData>& rhs ) const
  {
     my_data_ids_map_type::const_iterator it_lhs = my_data_ids_map_.find(lhs.id);
     my_data_ids_map_type::const_iterator it_rhs = my_data_ids_map_.find(rhs.id);
     if( it_lhs == my_data_ids_map_.end() || it_rhs == my_data_ids_map_.end() )
       throw "dammit!"; // whatever
     return it_lhs->second < it_rhs->second;
  }
private
  my_data_ids_map_type& my_data_ids_map_;
};

//...

my_data_ids_map_type my_data_ids_map;
// ...
// populate my_data_ids_map with the IDs and their indexes from my_data_ids
// ...
std::sort( my_data_vec.begin(), my_data_vec.end(), my_id_comparator(my_data_ids_map) );

If memory is scarce, but time doesn't matter, you could do away with the map and search the IDs in the my_data_ids vector for each comparison. However, you would have to be really desperate for memory to do that, since two linearly complex operations per comparison are going to be quite expensive.