package arithmetic.graphTraveral;
import java.util.LinkedList;
import java.util.Queue;

/**
* 这个例子是图的遍历的两种方式
* 通过它，使我来理解图的遍历
* Created on 2013-11-18
* @version 0.1
*/
public class GraphTraveral{
// 邻接矩阵存储图
// --A B C D E F G H I
// A 0 1 0 0 0 1 1 0 0
// B 1 0 1 0 0 0 1 0 1
// C 0 1 0 1 0 0 0 0 1
// D 0 0 1 0 1 0 1 1 1
// E 0 0 0 1 0 1 0 1 0
// F 1 0 0 0 1 0 1 0 0
// G 0 1 0 1 0 1 0 1 0
// H 0 0 0 1 1 0 1 0 0
// I 0 1 1 1 0 0 0 0 0

// 顶点数
private int number = 9;
// 记录顶点是否被访问
private boolean[] flag;
// 顶点
private String[] vertexs = { "A", "B", "C", "D", "E", "F", "G", "H", "I" };
// 边
private int[][] edges = {
{ 0, 1, 0, 0, 0, 1, 1, 0, 0 }, { 1, 0, 1, 0, 0, 0, 1, 0, 1 }, { 0, 1, 0, 1, 0, 0, 0, 0, 1 },
{ 0, 0, 1, 0, 1, 0, 1, 1, 1 }, { 0, 0, 0, 1, 0, 1, 0, 1, 0 }, { 1, 0, 0, 0, 1, 0, 1, 0, 0 },
{ 0, 1, 0, 1, 0, 1, 0, 1, 0 }, { 0, 0, 0, 1, 1, 0, 1, 0, 0 }, { 0, 1, 1, 1, 0, 0, 0, 0, 0 }
};

// 图的深度遍历操作(递归)
void DFSTraverse() {
flag = new boolean[number];
for (int i = 0; i < number; i++) {
if (flag[i] == false) {// 当前顶点没有被访问
DFS(i);
}
}
}

// 图的深度优先递归算法
void DFS(int i) {
flag[i] = true;// 第i个顶点被访问
System.out.print(vertexs[i] + " ");
for (int j = 0; j < number; j++) {
if (flag[j] == false && edges[i][j] == 1) {
DFS(j);
}
}
}

// 图的广度遍历操作
void BFSTraverse() {
flag = new boolean[number];
Queue<Integer> queue = new LinkedList<Integer>();
for (int i = 0; i < number; i++) {
if (flag[i] == false) {
flag[i] = true;
System.out.print(vertexs[i] + " ");
queue.add(i);
while (!queue.isEmpty()) {
int j = queue.poll();
for (int k = 0; k < number; k++) {
if (edges[j][k] == 1 && flag[k] == false) {
flag[k] = true;
System.out.print(vertexs[k] + " ");
queue.add(k);
}
}
}
}
}
}

// 测试
public static void main(String[] args) {
GraphTraveral graph = new GraphTraveral();
System.out.println("图的深度遍历操作(递归):");
graph.DFSTraverse();
System.out.println("\n-------------");
System.out.println("图的广度遍历操作:");
graph.BFSTraverse();
}
}

java实现图的遍历（深度优先遍历和广度优先遍历）