Codeforces 609E Minimum spanning tree for each edge

E. Minimum spanning tree for each edge
time limit per test
2 seconds
memory limit per test
256 megabytes
input
standard input
output
standard output

Connected undirected weighted graph without self-loops and multiple edges is given. Graph contains n vertices and m edges.

For each edge (u, v) find the minimal possible weight of the spanning tree that contains the edge (u, v).

The weight of the spanning tree is the sum of weights of all edges included in spanning tree.

Input

First line contains two integers n and m (1 ≤ n ≤ 2·105, n - 1 ≤ m ≤ 2·105) — the number of vertices and edges in graph.

Each of the next m lines contains three integers ui, vi, wi (1 ≤ ui, vi ≤ n, ui ≠ vi, 1 ≤ wi ≤ 109) — the endpoints of the i-th edge and its weight.

Output

Print m lines. i-th line should contain the minimal possible weight of the spanning tree that contains i-th edge.

The edges are numbered from 1 to m in order of their appearing in input.

Examples
input
5 7
1 2 3
1 3 1
1 4 5
2 3 2
2 5 3
3 4 2
4 5 4
output
9
8
11
8
8
8
9

题目大意:给你一个图,对于每条边,求出包含这条边的最小生成树的权值和。

思路:我们可以看出,对于每个最小生成树来说,它的主体其实还是整个图的最小生成树。对于每条边(u,v),我们分情况讨论:若u,v直接连通,证明u->v这条边已经在最小生成树中了,直接输出答案;若u,v不直接连通,我们就选取u->v的路径上的最大边,去掉,再把u,v连通,输出答案。不难证明,去掉u->v路径上的一条边,再连通u,v后,图仍然是一棵树。故我们需要求两点之间边权的最大值,采用倍增LCA维护。

#include<cstdio>
#include<cstring>
#include<string>
#include<algorithm>
#include<iostream>
#include<cmath>
#include<cstdlib>
#include<ctime>

using namespace std;
const int MAXN=200010;
const int MAXLOG=20;
int n,m;
struct Edge
{
	int u,v,w,id;
};
Edge map[MAXN];
int cmp(const Edge a,const Edge b)
{
	return a.w<b.w;
}
int cmp1(const Edge a,const Edge b)
{
	return a.id<b.id;
}
struct edge
{
	int next,to,val;
};
edge e[MAXN*2];
int head[MAXN],cnt;
void addedge(int u,int v,int w)
{
	e[++cnt].next=head[u];
	e[cnt].to=v;
	e[cnt].val=w;
	head[u]=cnt;
}
int fa[MAXN];
int find(int x)
{
	if (fa[x]!=x)
	{
		fa[x]=find(fa[x]);
	}
	return fa[x];
}
long long ans;
bool use[MAXN];
void Kruskal()
{
	sort(map+1,map+1+m,cmp);
	for (int i=1;i<=n;i++)
	{
		fa[i]=i;
	}
	for (int i=1;i<=m;i++)
	{
		int f1=find(map[i].u),f2=find(map[i].v);
		if (f1==f2)
		{
			continue;
		}
		fa[f1]=f2;
		use[map[i].id]=true;
		ans+=map[i].w;
		addedge(map[i].u,map[i].v,map[i].w);
		addedge(map[i].v,map[i].u,map[i].w);
	}
}
int f[MAXN][MAXLOG],g[MAXN][MAXLOG];
int deep[MAXN]; 
bool visit[MAXN];
void dfs(int x)
{
	visit[x]=1;
	for (int i=head[x];i;i=e[i].next)
	{
		int v=e[i].to;
		if (visit[v])
		{
			continue;
		}
		f[v][0]=x;
		deep[v]=deep[x]+1;
		g[v][0]=e[i].val;
		dfs(v);
	}
}
void build()
{
	for (int j=1;j<MAXLOG;j++)
	{
		for (int i=1;i<=n;i++)
		{
			f[i][j]=f[f[i][j-1]][j-1];
			g[i][j]=max(g[i][j-1],g[f[i][j-1]][j-1]);
		}
	}
}
int maxx;
void go_up(int &x,int d)
{
	for (int i=0;i<MAXLOG;i++)
	{
		if (d&(1<<i))
		{
			maxx=max(g[x][i],maxx);
			x=f[x][i];
		}
	}
}
void LCA(int x,int y)
{
	if (deep[x]>deep[y])
	{
		go_up(x,deep[x]-deep[y]);
	}
	else
	{
		go_up(y,deep[y]-deep[x]);
	}
	if (x==y)
	{
		return ;
	}
	for (int i=MAXLOG-1;i>=0;i--)
	{
		if (f[x][i]!=f[y][i])
		{
			maxx=max(maxx,max(g[x][i],g[y][i]));
			x=f[x][i];
			y=f[y][i];	
		}	
	} 
	maxx=max(maxx,max(g[x][0],g[y][0]));
	return ;
}
int main()
{
	scanf("%d%d",&n,&m);
	for (int i=1;i<=m;i++)
	{
		scanf("%d%d%d",&map[i].u,&map[i].v,&map[i].w);
		map[i].id=i;
	}
	Kruskal();
	deep[1]=1;
	dfs(1);
	build();
	sort(map+1,map+1+m,cmp1);
	for (int i=1;i<=m;i++)
	{
		if (use[i])
		{
			printf("%I64d\n",ans);
		}
		else
		{
			maxx=0;
			LCA(map[i].u,map[i].v);
			printf("%I64d\n",(long long)ans-maxx+map[i].w);
		}
	}
    return 0;
}


### Codeforces 887E Problem Solution and Discussion The problem **887E - The Great Game** on Codeforces involves a strategic game between two players who take turns to perform operations under specific rules. To tackle this challenge effectively, understanding both dynamic programming (DP) techniques and bitwise manipulation is crucial. #### Dynamic Programming Approach One effective method to approach this problem utilizes DP with memoization. By defining `dp[i][j]` as the optimal result when starting from state `(i,j)` where `i` represents current position and `j` indicates some status flag related to previous moves: ```cpp #include <bits/stdc++.h> using namespace std; const int MAXN = ...; // Define based on constraints int dp[MAXN][2]; // Function to calculate minimum steps using top-down DP int minSteps(int pos, bool prevMoveType) { if (pos >= N) return 0; if (dp[pos][prevMoveType] != -1) return dp[pos][prevMoveType]; int res = INT_MAX; // Try all possible next positions and update 'res' for (...) { /* Logic here */ } dp[pos][prevMoveType] = res; return res; } ``` This code snippet outlines how one might structure a solution involving recursive calls combined with caching results through an array named `dp`. #### Bitwise Operations Insight Another critical aspect lies within efficiently handling large integers via bitwise operators instead of arithmetic ones whenever applicable. This optimization can significantly reduce computation time especially given tight limits often found in competitive coding challenges like those hosted by platforms such as Codeforces[^1]. For detailed discussions about similar problems or more insights into solving strategies specifically tailored towards contest preparation, visiting forums dedicated to algorithmic contests would be beneficial. Websites associated directly with Codeforces offer rich resources including editorials written after each round which provide comprehensive explanations alongside alternative approaches taken by successful contestants during live events. --related questions-- 1. What are common pitfalls encountered while implementing dynamic programming solutions? 2. How does bit manipulation improve performance in algorithms dealing with integer values? 3. Can you recommend any online communities focused on discussing competitive programming tactics? 4. Are there particular patterns that frequently appear across different levels of difficulty within Codeforces contests?
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