【练习】HDU 3836 Equivalent Sets (强连通分量)

本文介绍了一个基于Tarjan算法实现的SCC(强连通分量)求解框架,通过缩点处理复杂图论问题。该框架能够高效地计算图中的强连通分量,并进一步统计各分量之间的连接特性,最终解决特定图论问题。

题意

同HDU 2767

题解

同HDU 2767

代码

#include<bits/stdc++.h>
using namespace std;
typedef double db;
typedef long long ll;
typedef unsigned long long ull;
const int nmax = 1e6+7;
const int INF = 0x3f3f3f3f;
const ll LINF = 0x3f3f3f3f3f3f3f3f;
const ull p = 67;
const ull MOD = 1610612741;
int N,M;
struct Tarjan{
    int head[nmax],low[nmax],dfn[nmax],sstack[nmax],color[nmax],top,sccnum,dfnnum,tot,n;
    int in[nmax],out[nmax];
    bool visit[nmax];
    struct edge{int to,nxt;}e[nmax<<1];
    void init(int n){
        memset(head,-1,sizeof head);
        memset(dfn,0,sizeof dfn);
        memset(color,0,sizeof color);
        memset(visit,0,sizeof visit);
        memset(in,0,sizeof in);
        memset(out,0,sizeof out);
        dfnnum = top = sccnum = tot = 0;
        this->n = n;
    }
    void add_edge(int u,int v){
        e[tot].to = v, e[tot].nxt = head[u]; head[u] = tot++;
    }
    void tarjan(int u){
        low[u] = dfn[u] = ++dfnnum;
        visit[u] = true;
        sstack[++top] = u;
        for(int i = head[u] ; i != -1; i = e[i].nxt){
            int v = e[i].to;
            if(!dfn[v]){
                tarjan(v);
                low[u] = min(low[u],low[v]);
            }else if(visit[v]) low[u] = min(low[u], dfn[v]);
        }
        if(dfn[u] == low[u]){
            visit[u] = false;
            color[u] = ++ sccnum;
            while(sstack[top] != u){
                color[sstack[top]] = sccnum;
                visit[sstack[top]] = false;
                top--;
            }
            top--;
        }
    }
    void dfs(int u){
        visit[u] = true;
        for(int i = head[u];i!=-1;i=e[i].nxt){
            int v = e[i].to;
            if(!visit[v]){
                if(color[v] != color[u]) in[color[v]]++ ,out[color[u]]++;
                dfs(v);
            }else if(visit[v]){
                if(color[v] != color[u]) in[color[v]]++ ,out[color[u]]++;
            }
        }
    }
    void start(){for(int i = 1;i<=n;++i) if(!dfn[i])
        tarjan(i);}
    int get_ans(){
        if(sccnum == 1) return 0;
        memset(visit,0,sizeof visit);
        for(int i = 1;i<=n;++i) if(!visit[i]) dfs(i);
        int notin = 0, notout = 0;
        for(int i = 1;i<=sccnum;++i){
            if(!in[i]) notin++;
            if(!out[i]) notout++;
        }
        return max(notin,notout);
    }
}solver;
int main(){
    while(scanf("%d %d",&N,&M)!=EOF){
        solver.init(N);
        int u,v;
        for(int i = 1;i<=M;++i){
            scanf("%d %d",&u,&v);
            solver.add_edge(u,v);
        }
        solver.start();
        printf("%d\n",solver.get_ans());
    }
    return 0;
}
### 使用Tarjan算法计算强连通分量数量 #### 算法原理 Tarjan算法通过深度优先搜索(DFS)遍历有向图中的节点,记录访问顺序和低链值(low-link value),从而识别出所有的强连通分量。当发现一个节点的访问序号等于其最低可达节点编号时,表明找到了一个新的强连通分量。 #### 时间复杂度分析 该方法的时间效率取决于存储结构的选择。对于采用邻接表表示的稀疏图而言,整体性能更优,能够在线性时间内完成操作,即O(n+m)[^4];而针对稠密图则可能退化至平方级别(O())。 #### Python代码实现 下面给出一段Python程序用于演示如何基于NetworkX库构建并处理带权无环图(DAG),进而求解其中存在的全部SCC及其总数: ```python import networkx as nx def tarjan_scc(graph): index_counter = [0] stack = [] lowlinks = {} index = {} result = [] def strongconnect(node): # Set the depth index for this node to be the next available incrementing counter. index[node] = index_counter[0] lowlinks[node] = index_counter[0] index_counter[0] += 1 stack.append(node) try: successors = graph.successors(node) except AttributeError: successors = graph.neighbors(node) for successor in successors: if successor not in lowlinks: strongconnect(successor) lowlinks[node] = min(lowlinks[node], lowlinks[successor]) elif successor in stack: lowlinks[node] = min(lowlinks[node], index[successor]) if lowlinks[node] == index[node]: scc = set() while True: current_node = stack.pop() scc.add(current_node) if current_node == node: break result.append(scc) for node in graph.nodes(): if node not in lowlinks: strongconnect(node) return result if __name__ == "__main__": G = nx.DiGraph() # Create a directed graph object using NetworkX library edges_list = [(1, 2),(2, 3),(3, 1)] # Define edge list according to sample input data from hdu1269 problem statement[^5] G.add_edges_from(edges_list) components = tarjan_scc(G) print(f"Number of Strongly Connected Components found: {len(components)}") ``` 此段脚本定义了一个名为`tarjan_scc()`的功能函数接收网络对象作为参数,并返回由集合组成的列表形式的结果集,每个子集中包含了构成单个SCC的所有顶点。最后部分展示了创建测试用DAG实例的过程以及调用上述功能获取最终答案的方式。
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