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依据二叉树的遍历方式,查找二叉树中的指定的节点,也有三种方式:
按照前序遍历的顺序查找:
正确代码:
- public Node preOrderSearch(int num) {
- System.out.println("当前的节点数值为:" + this.num);
- Node res = null;
- if (this.num == num) {
- return this;
- }
- if (this.left != null) {
- res = this.left.preOrderSearch(num);
- }
- if (res != null) {
- return res;
- }
- if (this.right != null) {
- res = this.right.preOrderSearch(num);
- }
- return res;
- }
在刚开始的时候,我认为没必要设置一个res的变量记录this.left.preOrderSearch(num)或者this.right.preOrderSearch(num)的值,思路和前序遍历的一样,只要判断该节点的值是不是要找的那个值即可,但是在运行代码以后,发现了问题。代码中构建的二叉树如下图所示。
(个人觉得:弄清楚递归程序最好的方式就是debug)
假设,要找到值为5的节点
递归程序的运行是这样的:【如果看不下去,可以直接设断点调试】
节点1,判断1和5的值相不相等,结果是不相等,判断左节点不为空,则进入左节点,左节点2与5不相等,则判断节点2有无左节点,节点2没有左节点,这时res=null,判断节点2有没有右节点,节点2没有右节点,所以回退到节点1判断左节点的时候,res的值为null,接着判断节点1的右节点是否为空,右节点不为空,进入右节点3,3不等于5,则继续判断节点3的左节点,节点3的左节点是5,这时,节点5就是我们要找的节点,则会把该节点返回,注意,返回到的节点是节点3的左节点判断语句,这时res被赋值为节点5,跳出if,进入判断res是否为空if语句,这时返回res,返回的值是到了节点1的右节点判断语句,res被赋值为节点5,这时节点1的左节点和右节点都判断完毕了,返回res,就可以输出了。
中序遍历和后序遍历也都是一样的理解方式。
单从要查找节点5这个具体的例子来说,后续遍历能够最快找到。
按照中序遍历的顺序查找
- public Node infixOrderSearch(int num) {
-
- Node res = null;
- if (this.left != null) {
- res = this.left.infixOrderSearch(num);
- }
- if (res != null) {
- return res;
- }
- System.out.println("当前的节点数值为:" + this.num);
- if (this.num == num) {
- return this;
- }
- if (this.right != null) {
- res = this.right.infixOrderSearch(num);
- }
- return res;
- }
按照后序遍历的顺序查找
- public Node postOrderSearch(int num) {
- Node res = null;
- if (this.left != null) {
- res = this.left.postOrderSearch(num);
- }
- if (res != null) {
- return res;
- }
- if (this.right != null) {
- res = this.right.postOrderSearch(num);
- }
- if (res != null) {
- return res;
- }
- System.out.println("当前的节点数值为:" + this.num);
- if (this.num == num) {
- return this;
- }
- return res;
- }
完整的代码(可直接运行):
- package tree;
-
- public class BinaryTreeDemo {
-
- public static void main(String[] args) {
- //创建一棵二叉树
- BinaryTree binaryTree = new BinaryTree();
- //创建需要的节点
- Node root = new Node(1);
- Node n2 = new Node(2);
- Node n3 = new Node(3);
- Node n4 = new Node(4);
-
- //新增加的节点
- Node n5 = new Node(5);
-
- //暂时手动创建二叉树
- root.setLeft(n2);
- root.setRight(n3);
- n3.setRight(n4);
- n3.setLeft(n5);
-
- //测试
- //前序遍历 :1 2 3 4
- //添加节点之后 : 1 2 3 5 4
- System.out.println("前序遍历");
- binaryTree.setRoot(root);
- binaryTree.preOrder();
-
- //中序遍历 :2 1 3 4
- //添加节点之后 :2 1 5 3 4
- System.out.println("中序遍历");
- binaryTree.infixOrder();
-
- //后序遍历 2 4 3 1
- //添加节点之后 :2 5 4 3 1
- System.out.println("后序遍历");
- binaryTree.postOrder();
-
- //前序遍历查找
- System.out.println("前序遍历查找:");
- System.out.println(binaryTree.preOrderSearch(5));
- // System.out.println("中序遍历查找:");
- // System.out.println(binaryTree.infixOrderSearch(5));
- // System.out.println("后序遍历查找:");
- // System.out.println(binaryTree.postOrderSearch(5));
-
- }
-
- }
-
- class BinaryTree {
- private Node root;
-
- public void setRoot(Node root) {
- this.root = root;
- }
-
- //前序遍历
- public void preOrder() {
- if (this.root != null) {
- this.root.preOrder();
- } else {
- System.out.println("当前二叉树为空,无法遍历!");
- }
- }
-
- //中序遍历
- public void infixOrder() {
- if (this.root != null) {
- this.root.infixOrder();
- } else {
- System.out.println("当前二叉树为空,无法遍历!");
- }
- }
-
- //后序遍历
- public void postOrder() {
- if (this.root != null) {
- this.root.postOrder();
- } else {
- System.out.println("当前二叉树为空,无法遍历!");
- }
- }
-
- public Node preOrderSearch(int num) {
- if (root != null) {
- return root.preOrderSearch(num);
- }
- return null;
- }
-
- public Node infixOrderSearch(int num) {
- if (root != null) {
- return root.infixOrderSearch(num);
- }
- return null;
- }
-
- public Node postOrderSearch(int num) {
- if (root != null) {
- return root.postOrderSearch(num);
- }
- return null;
- }
- }
-
- class Node {
- private int num;
- private Node left;
- private Node right;
-
- public Node(int num) {
- this.num = num;
- }
-
- public int getNum() {
- return num;
- }
-
- public void setNum(int num) {
- this.num = num;
- }
-
- public Node getLeft() {
- return left;
- }
-
- public void setLeft(Node left) {
- this.left = left;
- }
-
- public Node getRight() {
- return right;
- }
-
- public void setRight(Node right) {
- this.right = right;
- }
-
- @Override
- public String toString() {
- return "Node{" +
- "num=" + num +
- '}';
- }
-
- //前序遍历
- public void preOrder() {
- System.out.println(this);
- if (this.left != null) {
- this.left.preOrder();
- }
- if (this.right != null) {
- this.right.preOrder();
- }
- }
-
- //中序遍历
- public void infixOrder() {
- if (this.left != null) {
- this.left.infixOrder();
- }
- System.out.println(this);
- if (this.right != null) {
- this.right.infixOrder();
- }
- }
-
- //后序遍历
- public void postOrder() {
- if (this.left != null) {
- this.left.postOrder();
- }
- if (this.right != null) {
- this.right.postOrder();
- }
- System.out.println(this);
- }
-
- // 前序遍历查找指定的节点
- public Node preOrderSearch(int num) {
- System.out.println("当前的节点数值为:" + this.num);
- Node res = null;
- if (this.num == num) {
- return this;
- }
- if (this.left != null) {
- res = this.left.preOrderSearch(num);
- }
- if (res != null) {
- return res;
- }
- if (this.right != null) {
- res = this.right.preOrderSearch(num);
- }
- return res;
- }
- //中序遍历查找指定的节点
- public Node infixOrderSearch(int num) {
-
- Node res = null;
- if (this.left != null) {
- res = this.left.infixOrderSearch(num);
- }
- if (res != null) {
- return res;
- }
- System.out.println("当前的节点数值为:" + this.num);
- if (this.num == num) {
- return this;
- }
- if (this.right != null) {
- res = this.right.infixOrderSearch(num);
- }
- return res;
- }
-
- //后序遍历查找指定的节点
- public Node postOrderSearch(int num) {
- Node res = null;
- if (this.left != null) {
- res = this.left.postOrderSearch(num);
- }
- if (res != null) {
- return res;
- }
- if (this.right != null) {
- res = this.right.postOrderSearch(num);
- }
- if (res != null) {
- return res;
- }
- System.out.println("当前的节点数值为:" + this.num);
- if (this.num == num) {
- return this;
- }
- return res;
- }
- }
运行部分结果:
- 前序遍历查找:
- 当前的节点数值为:1
- 当前的节点数值为:2
- 当前的节点数值为:3
- 当前的节点数值为:5
- Node{num=5}
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