DSU模板(树的启发式合并)

摘自Codeforces博客

With dsu on tree we can answer queries of this type:

How many vertices in subtree of vertex v has some property in O(n lg n) time (for all of the queries).

For example:

Given a tree, every vertex has color. Query is how many vertices in subtree of vertex v are colored with color c?

要点：记录每棵子树的大小，启发式合并。

模板整理如下：

1. easy to code but 

 1 //O(nlognlogn)
 2 map<int, int> *cnt[maxn];
 3 void dfs(int v, int p){
 4     int mx = -1, bigChild = -1;
 5     for(auto u : g[v])
 6        if(u != p){
 7            dfs(u, v);
 8            if(sz[u] > mx)
 9                mx = sz[u], bigChild = u;
10        }
11     if(bigChild != -1)
12         cnt[v] = cnt[bigChild];
13     else
14         cnt[v] = new map<int, int> ();
15     (*cnt[v])[ col[v] ] ++;
16     for(auto u : g[v])
17        if(u != p && u != bigChild){
18            for(auto x : *cnt[u])
19                (*cnt[v])[x.first] += x.second;
20        }
21     //now (*cnt)[c] is the number of vertices in subtree of vertex v that has color c. You can answer the queries easily.
22 
23 }
View Code

2. easy to code and 

 1 vector<int> *vec[maxn];
 2 int cnt[maxn];
 3 void dfs(int v, int p, bool keep){
 4     int mx = -1, bigChild = -1;
 5     for(auto u : g[v])
 6        if(u != p && sz[u] > mx)
 7            mx = sz[u], bigChild = u;
 8     for(auto u : g[v])
 9        if(u != p && u != bigChild)
10            dfs(u, v, 0);
11     if(bigChild != -1)
12         dfs(bigChild, v, 1), vec[v] = vec[bigChild];
13     else
14         vec[v] = new vector<int> ();
15     vec[v]->push_back(v);
16     cnt[ col[v] ]++;
17     for(auto u : g[v])
18        if(u != p && u != bigChild)
19            for(auto x : *vec[u]){
20                cnt[ col[x] ]++;
21                vec[v] -> push_back(x);
22            }
23     //now (*cnt)[c] is the number of vertices in subtree of vertex v that has color c. You can answer the queries easily.
24     // note that in this step *vec[v] contains all of the subtree of vertex v.
25     if(keep == 0)
26         for(auto u : *vec[v])
27             cnt[ col[u] ]--;
28 }
View Code

3. heavy-light decomposition style 

 1 int cnt[maxn];
 2 bool big[maxn];
 3 void add(int v, int p, int x){
 4     cnt[ col[v] ] += x;
 5     for(auto u: g[v])
 6         if(u != p && !big[u])
 7             add(u, v, x)
 8 }
 9 void dfs(int v, int p, bool keep){
10     int mx = -1, bigChild = -1;
11     for(auto u : g[v])
12        if(u != p && sz[u] > mx)
13           mx = sz[u], bigChild = u;
14     for(auto u : g[v])
15         if(u != p && u != bigChild)
16             dfs(u, v, 0);  // run a dfs on small childs and clear them from cnt
17     if(bigChild != -1)
18         dfs(bigChild, v, 1), big[bigChild] = 1;  // bigChild marked as big and not cleared from cnt
19     add(v, p, 1);
20     //now cnt[c] is the number of vertices in subtree of vertex v that has color c. You can answer the queries easily.
21     if(bigChild != -1)
22         big[bigChild] = 0;
23     if(keep == 0)
24         add(v, p, -1);
25 }
View Code

4. My invented style 

 1 This implementation for "Dsu on tree" technique is new and invented by me. This implementation is easier to code than others. Let st[v] dfs starting time of vertex v, ft[v] be it's finishing time and ver[time] is the vertex which it's starting time is equal to time.
 2 
 3 int cnt[maxn];
 4 void dfs(int v, int p, bool keep){
 5     int mx = -1, bigChild = -1;
 6     for(auto u : g[v])
 7        if(u != p && sz[u] > mx)
 8           mx = sz[u], bigChild = u;
 9     for(auto u : g[v])
10         if(u != p && u != bigChild)
11             dfs(u, v, 0);  // run a dfs on small childs and clear them from cnt
12     if(bigChild != -1)
13         dfs(bigChild, v, 1);  // bigChild marked as big and not cleared from cnt
14     for(auto u : g[v])
15     if(u != p && u != bigChild)
16         for(int p = st[u]; p < ft[u]; p++)
17         cnt[ col[ ver[p] ] ]++;
18     cnt[ col[v] ]++;
19     //now cnt[c] is the number of vertices in subtree of vertex v that has color c. You can answer the queries easily.
20     if(keep == 0)
21         for(int p = st[v]; p < ft[v]; p++)
22         cnt[ col[ ver[p] ] ]--;
23 }
View Code

 

时间复杂度分析

4. My invented style

考虑每个节点最多会被清零几次？

显然被清零的次数即为该节点到根节点的链上轻儿子的个数

联系树链剖分，任意一个节点到根节点的链最多被划分为O(logn)段重链，最多被清零O(logn)次.

故时间复杂度为O(nlogn).

2, 3, 4时间复杂度分析类似.

 

启发式合并算法复杂度总结

线段树合并 => O(nlogU), U为线段树权值域，从势能分析，合并的复杂度为O(总节点数减小的个数)

平衡树合并+树链剖分+单次插入删除O(logn) => O(nlognlogn)

平衡树合并+树链剖分+单次插入删除O(1) => O(nlogn)

set合并 => O(nlognlogn), 显然set合并复杂度不会高于multiset(平衡树)合并复杂度

posted @ 2017-03-27 21:08  我在地狱  阅读(548)  评论(0)  编辑  收藏  举报