最大搜索子树
【摘要】 给定一个二叉树的头结点,返回最大搜索子树的大小。
我们先定义结点:
public static class Node { public int value; public Node left; public Node right; public Node(int data) { this.value = data; } }
分析:
直...
给定一个二叉树的头结点,返回最大搜索子树的大小。
我们先定义结点:
public static class Node {
public int value;
public Node left;
public Node right;
public Node(int data) {
this.value = data;
}
}
分析:
直接判断每个节点左边小右边大是不对滴
可以暴力判断所有的子树,就不说了。
最大搜索子树可能性:
第一种可能性,以node为头的结点的最大二叉搜索子树可能来自它左子树;
第二种可能性,以node为头的结点的最大二叉搜索子树可能来自它右子树;
第三种可能性,左树整体是搜索二叉树,右树整体也是搜索二叉树,而且左树的头是node.left,右树的头是node.right,且左树的最大值< node.value,右树的最小值 > node.value, 那么以我为头的整棵树都是搜索二叉树;
第三种可能性的判断,需要的信息有:左子树的最大值、右子树的最小值、左子树是不是搜索二叉树、右子树是不是搜索二叉树
还有左右搜索二叉树的最大深度。
我们判断了自己,并不知道自己是哪边的子树,我们要返回自己的最大值和最小值。
这样,定义一个返回类型:
public static class ReturnType{
public int size;//最大搜索子树深度
public Node head;//最大搜索子树的根
public int min;//子树最小
public int max;//子树最大
public ReturnType(int a, Node b,int c,int d) {
this.size =a;
this.head = b;
this.min = c;
this.max = d;
}
}
然后开始写代码:
注意:
1)NULL返回深度0,头为NULL,最大值最小值返回系统最大和最小,这样才不会影响别的判断。
public static ReturnType process(Node head) {
if(head == null) {
return new ReturnType(0,null,Integer.MAX_VALUE, Integer.MIN_VALUE);
}
Node left = head.left;//取信息
ReturnType leftSubTressInfo = process(left);
Node right = head.right;
ReturnType rightSubTressInfo = process(right);
int includeItSelf = 0;
if(leftSubTressInfo.head == left // 左子树为搜索树
&&rightSubTressInfo.head == right// 右子树为搜索树
&& head.value > leftSubTressInfo.max// 左子树最大值小于当前节点
&& head.value < rightSubTressInfo.min//右子树最小值大于当前节点
) {
includeItSelf = leftSubTressInfo.size + 1 + rightSubTressInfo.size;//当前节点为根的二叉树为搜索树
}
int p1 = leftSubTressInfo.size;
int p2 = rightSubTressInfo.size;
int maxSize = Math.max(Math.max(p1, p2), includeItSelf);//最大搜索树深度
Node maxHead = p1 > p2 ? leftSubTressInfo.head : rightSubTressInfo.head;
if(maxSize == includeItSelf) {
maxHead = head;
}//最大搜索树的根:来自左子树、来自右子树、本身
return new ReturnType(
maxSize, //深度
maxHead, //根
Math.min(Math.min(leftSubTressInfo.min,rightSubTressInfo.min),head.value), //最小
Math.max(Math.max(leftSubTressInfo.max,rightSubTressInfo.max),head.value)); //最大
}
可以进一步改进:
空间浪费比较严重
其实返回值为三个int,一个node,我们可以把三个int合起来,用全局数组记录,函数只返回node(搜索树的根)即可。
给出完整代码:
public class BiggestSubBSTInTree {
public static class Node {
public int value;
public Node left;
public Node right;
public Node(int data) {
this.value = data;
}
}
public static Node biggestSubBST(Node head) {
int[] record = new int[3]; // 0->size, 1->min, 2->max
return posOrder(head, record);
}
public static class ReturnType{
public int size;//最大搜索子树深度
public Node head;//最大搜索子树的根
public int min;//子树最小
public int max;//子树最大
public ReturnType(int a, Node b,int c,int d) {
this.size =a;
this.head = b;
this.min = c;
this.max = d;
}
}
public static ReturnType process(Node head) {
if(head == null) {
return new ReturnType(0,null,Integer.MAX_VALUE, Integer.MIN_VALUE);
}
Node left = head.left;//取信息
ReturnType leftSubTressInfo = process(left);
Node right = head.right;
ReturnType rightSubTressInfo = process(right);
int includeItSelf = 0;
if(leftSubTressInfo.head == left // 左子树为搜索树
&&rightSubTressInfo.head == right// 右子树为搜索树
&& head.value > leftSubTressInfo.max// 左子树最大值小于当前节点
&& head.value < rightSubTressInfo.min//右子树最小值大于当前节点
) {
includeItSelf = leftSubTressInfo.size + 1 + rightSubTressInfo.size;//当前节点为根的二叉树为搜索树
}
int p1 = leftSubTressInfo.size;
int p2 = rightSubTressInfo.size;
int maxSize = Math.max(Math.max(p1, p2), includeItSelf);//最大搜索树深度
Node maxHead = p1 > p2 ? leftSubTressInfo.head : rightSubTressInfo.head;
if(maxSize == includeItSelf) {
maxHead = head;
}//最大搜索树的根:来自左子树、来自右子树、本身
return new ReturnType(
maxSize, //深度
maxHead, //根
Math.min(Math.min(leftSubTressInfo.min,rightSubTressInfo.min),head.value), //最小
Math.max(Math.max(leftSubTressInfo.max,rightSubTressInfo.max),head.value)); //最大
}
public static Node posOrder(Node head, int[] record) {
if (head == null) {
record[0] = 0;
record[1] = Integer.MAX_VALUE;
record[2] = Integer.MIN_VALUE;
return null;
}
int value = head.value;
Node left = head.left;
Node right = head.right;
Node lBST = posOrder(left, record);
int lSize = record[0];
int lMin = record[1];
int lMax = record[2];
Node rBST = posOrder(right, record);
int rSize = record[0];
int rMin = record[1];
int rMax = record[2];
record[1] = Math.min(rMin, Math.min(lMin, value)); // lmin, value, rmin -> min
record[2] = Math.max(lMax, Math.max(rMax, value)); // lmax, value, rmax -> max
if (left == lBST && right == rBST && lMax < value && value < rMin) {
record[0] = lSize + rSize + 1;//修改深度
return head; //返回根
}//满足当前构成搜索树的条件
record[0] = Math.max(lSize, rSize);//较大深度
return lSize > rSize ? lBST : rBST;//返回较大搜索树的根
}
// for test -- print tree
public static void printTree(Node head) {
System.out.println("Binary Tree:");
printInOrder(head, 0, "H", 17);
System.out.println();
}
public static void printInOrder(Node head, int height, String to, int len) {
if (head == null) {
return;
}
printInOrder(head.right, height + 1, "v", len);
String val = to + head.value + to;
int lenM = val.length();
int lenL = (len - lenM) / 2;
int lenR = len - lenM - lenL;
val = getSpace(lenL) + val + getSpace(lenR);
System.out.println(getSpace(height * len) + val);
printInOrder(head.left, height + 1, "^", len);
}
public static String getSpace(int num) {
String space = " ";
StringBuffer buf = new StringBuffer("");
for (int i = 0; i < num; i++) {
buf.append(space);
}
return buf.toString();
}
public static void main(String[] args) {
Node head = new Node(6);
head.left = new Node(1);
head.left.left = new Node(0);
head.left.right = new Node(3);
head.right = new Node(12);
head.right.left = new Node(10);
head.right.left.left = new Node(4);
head.right.left.left.left = new Node(2);
head.right.left.left.right = new Node(5);
head.right.left.right = new Node(14);
head.right.left.right.left = new Node(11);
head.right.left.right.right = new Node(15);
head.right.right = new Node(13);
head.right.right.left = new Node(20);
head.right.right.right = new Node(16);
printTree(head);
Node bst = biggestSubBST(head);
printTree(bst);
}
}
文章来源: fantianzuo.blog.csdn.net,作者:兔老大RabbitMQ,版权归原作者所有,如需转载,请联系作者。
原文链接:fantianzuo.blog.csdn.net/article/details/84251431
【版权声明】本文为华为云社区用户转载文章,如果您发现本社区中有涉嫌抄袭的内容,欢迎发送邮件进行举报,并提供相关证据,一经查实,本社区将立刻删除涉嫌侵权内容,举报邮箱:
cloudbbs@huaweicloud.com
- 点赞
- 收藏
- 关注作者
评论(0)