关于弗洛伊德算法求最短路径详解

public class Test1 {
    public static void main(String[] args) {
        System.out.println("请输入有几个顶点：");
        Scanner scanner = new Scanner(System.in);
        int n = scanner.nextInt();
        char[] vertex = new char[n];
        System.out.println("请输入各个顶点的符号，每个字符用空格分隔：");
        for (int i = 0; i < n; i++) {
            vertex[i] = scanner.next().charAt(0);
        }
        int[][] arr = new int[n][n];
        System.out.println("请输入各个顶点在二维表之间的距离，不能直达的用100表示：");
        for (int i = 0; i < n; i++) {
            for (int j = 0; j < n; j++) {
                arr[i][j] = scanner.nextInt();
            }
        }
        Graph gp = new Graph(vertex, arr, n);
        gp.floyd();
        gp.show(vertex);
    }
}
//创建图
class Graph {
    private char[] vertex;
    private int[][] dis; // 从顶点出发到其他节点的距离
    private int[][] pre; // 目标节点的前驱节点
    // 顶点数组 邻接矩阵 长度大小
    public Graph(char[] vertex, int[][] dis, int len) {
        this.vertex = vertex;
        this.dis = dis;
        this.pre = new int[len][len];
        // 对pre数组进行初始化
        for (int i = 0; i < len; i++) {
            Arrays.fill(pre[i], i);
        }
    }
    public void show(char[] vertex) {
        for (int i = 0; i < dis.length; i++) {
            for (int j = 0; j < dis.length; j++) {
                System.out.print(vertex[pre[i][j]] + "  ");
            }
            System.out.println();
            for (int j = 0; j < dis.length; j++) {
                System.out.print("( " + vertex[i] + " -> " + vertex[j] + " 的最短路径 " + dis[i][j] + " )    ");
            }
            System.out.println();
        }
    }
    // 弗洛伊德算法
    public void floyd() {
        int len = 0;
        // 从中间节点进行遍历
        for (int k = 0; k < dis.length; k++) {
            // 对出发节点进行遍历
            for (int i = 0; i < dis.length; i++) {
                // 遍历终点节点
                for (int j = 0; j < dis.length; j++) {
                    len = dis[i][k] + dis[k][j];
                    if (len < dis[i][j]) {
                        dis[i][j] = len;
                        pre[i][j] = pre[k][j];
                    }
                }
            }
        }
    }
}