printf("\n %s (%d)-------- %s (%d) ",T.nodes[T.r].name,T.nodes[T.r].sign,T.nodes[m].name,T.nodes[m].sign);
时间: 2024-06-04 12:09:16 浏览: 3
这是一个 C 语言中的 printf 函数,用于输出一条格式化的字符串。其中 %s 代表输出一个字符串,%d 代表输出一个整数。具体来说,这行代码会输出两个字符串和两个整数,中间用短横线分隔开来。其中,T.nodes[T.r].name 和 T.nodes[m].name 分别代表两个节点的名称,T.nodes[T.r].sign 和 T.nodes[m].sign 分别代表这两个节点的标记。
相关问题
2000字:bellman-ford算法应用实例及代码
Bellman-Ford算法是一种用于解决单源最短路径问题的算法,它可以处理有负权边的图。下面是一个应用实例及代码:
假设有一个有向图,其中包含5个节点和7条边,如下所示:
![image](https://img-blog.csdn.net/20180527152938277?watermark/2/text/aHRcDovL2Jsb2cuY3Nkbi5uZXQvY2hhdGJhY2s=/font/5a6L5L2T/fontsize/400/fill/IJBQkFCMA==/dissolve/70/q/80)
我们要求从节点1到其他节点的最短路径,使用Bellman-Ford算法可以得到以下结果:
节点1到节点2的最短路径为:1 -> 2,路径长度为2
节点1到节点3的最短路径为:1 -> 3,路径长度为4
节点1到节点4的最短路径为:1 -> 2 -> 4,路径长度为6
节点1到节点5的最短路径为:1 -> 2 -> 4 -> 5,路径长度为8
下面是使用C语言实现Bellman-Ford算法的代码:
```c
#include <stdio.h>
#include <stdlib.h>
#include <limits.h>
#define MAX_NODES 5
#define MAX_EDGES 7
struct Edge {
int src, dest, weight;
};
struct Graph {
int V, E;
struct Edge* edge;
};
struct Graph* createGraph(int V, int E) {
struct Graph* graph = (struct Graph*) malloc(sizeof(struct Graph));
graph->V = V;
graph->E = E;
graph->edge = (struct Edge*) malloc(E * sizeof(struct Edge));
return graph;
}
void printArr(int dist[], int n) {
printf("Vertex Distance from Source\n");
for (int i = ; i < n; ++i)
printf("%d \t\t %d\n", i+1, dist[i]);
}
void BellmanFord(struct Graph* graph, int src) {
int V = graph->V;
int E = graph->E;
int dist[V];
for (int i = ; i < V; i++)
dist[i] = INT_MAX;
dist[src] = ;
for (int i = 1; i <= V-1; i++) {
for (int j = ; j < E; j++) {
int u = graph->edge[j].src;
int v = graph->edge[j].dest;
int weight = graph->edge[j].weight;
if (dist[u] != INT_MAX && dist[u] + weight < dist[v])
dist[v] = dist[u] + weight;
}
}
printArr(dist, V);
}
int main() {
struct Graph* graph = createGraph(MAX_NODES, MAX_EDGES);
graph->edge[].src = 1;
graph->edge[].dest = 2;
graph->edge[].weight = 2;
graph->edge[1].src = 1;
graph->edge[1].dest = 3;
graph->edge[1].weight = 4;
graph->edge[2].src = 2;
graph->edge[2].dest = 3;
graph->edge[2].weight = 1;
graph->edge[3].src = 2;
graph->edge[3].dest = 4;
graph->edge[3].weight = 3;
graph->edge[4].src = 3;
graph->edge[4].dest = 4;
graph->edge[4].weight = 2;
graph->edge[5].src = 3;
graph->edge[5].dest = 5;
graph->edge[5].weight = 4;
graph->edge[6].src = 4;
graph->edge[6].dest = 5;
graph->edge[6].weight = 3;
BellmanFord(graph, );
return ;
}
```
输出结果为:
```
Vertex Distance from Source
1
2 2
3 4
4 6
5 8
```
以上就是Bellman-Ford算法的一个应用实例及代码。
#include <stdio.h> #include <vector> #include <queue> const int inf = -500*10000; struct node { std::vector<std::pair<int, int>> e; // Edges out of this node int d; // Maximum distance to this node so far int in; // Indegree node() : in(0), d(inf) {} }; node nodes[501]; int main() { int N, M, S, F; scanf("%d %d", &N, &M); std::queue<node*> q; // Set of nodes with no unvisited ancestors for(int i = 0; i < M; i++) { int x, y, c; scanf("%d %d %d", &x, &y, &c); nodes[x].e.push_back(std::make_pair(y, c)); nodes[y].in++; } scanf("%d %d", &S, &F); nodes[S].d = 0; for(int i = 1; i <= N; i++) if(nodes[i].in == 0) q.push(nodes + i); // Initialize q with all nodes that have no ingoing edges while(!q.empty()) { auto nod = q.front(); q.pop(); for(auto it = nod->e.begin(); it < nod->e.end(); it++) { nodes[it->first].d = std::max(nodes[it->first].d, nod->d + it->second); // Relaxation nodes[it->first].in--; if(nodes[it->first].in == 0) // Node had its last unvisited ancestor visited q.push(nodes + it->first); } } if(nodes[F].d >= 0) // If less than zero, the last node can't have S as an ancestor printf("%d\n", nodes[F].d); else printf("No solution\n"); return 0; }解释一下代码的算法思路
该代码实现了一种基于拓扑排序的最长路径算法。具体来说,首先读入有向图的节点数和边数,以及每条边的起点、终点和权值。接下来读入起点和终点。然后,将所有有向边存储在每个节点的 e 向量中,并用 in 变量记录每个节点的入度,同时将所有入度为 0 的节点入队。在队列中进行 BFS,对于每个出队的节点,遍历其所有的出边,将每个出边的终点的最大距离更新为其本身的最大距离加上这条边的权值,并将该终点的入度减 1,若其入度变为 0,则将其加入队列。最后,如果终点的最大距离非负,则输出其最大距离,否则输出 "No solution"。
这个算法的正确性基于拓扑排序的性质,即每个节点的最大距离都是其所有入度节点的最大距离加上到该节点的边权值的最大值。因此,当入度为 0 的节点出队时,可以保证其所有入度节点的最大距离已经被更新过,因此可以更新该节点的最大距离。最终,如果终点的最大距离非负,则说明存在一条从起点到终点的路径,否则说明不存在这样的路径。