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https://github.com/youngyangyang04/leetcode-master.git
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Merge branch 'youngyangyang04:master' into master
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@ -313,63 +313,47 @@ func lowestCommonAncestor(root, p, q *TreeNode) *TreeNode {
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}
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```
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JavaScript版本
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> 递归
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JavaScript版本:
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1. 使用递归的方法
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```javascript
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/**
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* Definition for a binary tree node.
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* function TreeNode(val) {
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* this.val = val;
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* this.left = this.right = null;
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* }
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*/
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/**
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* @param {TreeNode} root
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* @param {TreeNode} p
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* @param {TreeNode} q
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* @return {TreeNode}
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*/
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var lowestCommonAncestor = function(root, p, q) {
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if(root.val > p.val && root.val > q.val)
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return lowestCommonAncestor(root.left, p , q);
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else if(root.val < p.val && root.val < q.val)
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return lowestCommonAncestor(root.right, p , q);
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return root;
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};
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```
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> 迭代
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```javascript
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/**
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* Definition for a binary tree node.
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* function TreeNode(val) {
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* this.val = val;
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* this.left = this.right = null;
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* }
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*/
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/**
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* @param {TreeNode} root
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* @param {TreeNode} p
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* @param {TreeNode} q
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* @return {TreeNode}
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*/
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var lowestCommonAncestor = function(root, p, q) {
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while(1) {
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if(root.val > p.val && root.val > q.val)
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root = root.left;
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else if(root.val < p.val && root.val < q.val)
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root = root.right;
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else
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break;
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// 使用递归的方法
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// 1. 使用给定的递归函数lowestCommonAncestor
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// 2. 确定递归终止条件
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if(root === null) {
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return root;
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}
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if(root.val>p.val&&root.val>q.val) {
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// 向左子树查询
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let left = lowestCommonAncestor(root.left,p,q);
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return left !== null&&left;
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}
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if(root.val<p.val&&root.val<q.val) {
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// 向右子树查询
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let right = lowestCommonAncestor(root.right,p,q);
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return right !== null&&right;
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}
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return root;
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};
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```
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2. 使用迭代的方法
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```javascript
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var lowestCommonAncestor = function(root, p, q) {
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// 使用迭代的方法
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while(root) {
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if(root.val>p.val&&root.val>q.val) {
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root = root.left;
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}else if(root.val<p.val&&root.val<q.val) {
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root = root.right;
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}else {
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return root;
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}
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}
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return null;
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};
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```
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-----------------------
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@ -311,35 +311,34 @@ func lowestCommonAncestor(root, p, q *TreeNode) *TreeNode {
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}
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```
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JavaScript版本
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JavaScript版本:
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```javascript
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/**
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* Definition for a binary tree node.
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* function TreeNode(val) {
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* this.val = val;
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* this.left = this.right = null;
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* }
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*/
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/**
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* @param {TreeNode} root
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* @param {TreeNode} p
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* @param {TreeNode} q
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* @return {TreeNode}
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*/
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var lowestCommonAncestor = function(root, p, q) {
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if(root === p || root === q || root === null)
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return root;
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let left = lowestCommonAncestor(root.left, p , q);
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let right = lowestCommonAncestor(root.right, p, q);
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if(left && right)
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return root;
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if(!left)
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return right;
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return left;
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// 使用递归的方法
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// 需要从下到上,所以使用后序遍历
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// 1. 确定递归的函数
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const travelTree = function(root,p,q) {
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// 2. 确定递归终止条件
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if(root === null || root === p||root === q) {
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return root;
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}
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// 3. 确定递归单层逻辑
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let left = travelTree(root.left,p,q);
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let right = travelTree(root.right,p,q);
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if(left !== null&&right !== null) {
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return root;
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}
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if(left ===null) {
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return right;
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}
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return left;
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}
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return travelTree(root,p,q);
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};
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```
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-----------------------
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* 作者微信:[程序员Carl](https://mp.weixin.qq.com/s/b66DFkOp8OOxdZC_xLZxfw)
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* B站视频:[代码随想录](https://space.bilibili.com/525438321)
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@ -214,8 +214,26 @@ class Solution:
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return dp[n]
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```
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Python3:
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```python
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class Solution:
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def numSquares(self, n: int) -> int:
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# 初始化
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# 组成和的完全平方数的最多个数,就是只用1构成
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# 因此,dp[i] = i
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dp = [i for i in range(n + 1)]
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# dp[0] = 0 无意义,只是为了方便记录特殊情况:
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# n本身就是完全平方数,dp[n] = min(dp[n], dp[n - n] + 1) = 1
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for i in range(1, n): # 遍历物品
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if i * i > n:
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break
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num = i * i
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for j in range(num, n + 1): # 遍历背包
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dp[j] = min(dp[j], dp[j - num] + 1)
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return dp[n]
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```
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Go:
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```go
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@ -523,52 +523,76 @@ func traversal(root *TreeNode,result *[]int,pre *TreeNode){//遍历统计
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}
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```
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JavaScript版本
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JavaScript版本:
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使用额外空间map的方法:
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```javascript
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/**
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* Definition for a binary tree node.
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* function TreeNode(val, left, right) {
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* this.val = (val===undefined ? 0 : val)
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* this.left = (left===undefined ? null : left)
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* this.right = (right===undefined ? null : right)
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* }
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*/
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/**
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* @param {TreeNode} root
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* @return {number[]}
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*/
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var findMode = function (root) {
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let maxCount = 0;
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let curCount = 0;
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let pre = null;
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let res = [];
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const inOrder = (root) => {
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if (root === null)
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return;
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inOrder(root.left);
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if (pre === null)
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curCount = 1;
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else if (pre.val === root.val)
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curCount++;
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else
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curCount = 1;
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pre = root;
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if (curCount === maxCount)
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res.push(root.val);
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if (curCount > maxCount) {
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maxCount = curCount;
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res.splice(0, res.length);
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res.push(root.val);
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var findMode = function(root) {
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// 使用递归中序遍历
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let map = new Map();
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// 1. 确定递归函数以及函数参数
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const traverTree = function(root) {
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// 2. 确定递归终止条件
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if(root === null) {
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return ;
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}
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inOrder(root.right);
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return;
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traverTree(root.left);
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// 3. 单层递归逻辑
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map.set(root.val,map.has(root.val)?map.get(root.val)+1:1);
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traverTree(root.right);
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}
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inOrder(root);
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traverTree(root);
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//上面把数据都存储到map
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//下面开始寻找map里面的
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// 定义一个最大出现次数的初始值为root.val的出现次数
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let maxCount = map.get(root.val);
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// 定义一个存放结果的数组res
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let res = [];
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for(let [key,value] of map) {
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// 如果当前值等于最大出现次数就直接在res增加该值
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if(value === maxCount) {
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res.push(key);
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}
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// 如果value的值大于原本的maxCount就清空res的所有值,因为找到了更大的
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if(value>maxCount) {
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res = [];
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maxCount = value;
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res.push(key);
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}
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}
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return res;
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};
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```
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不使用额外空间,利用二叉树性质,中序遍历(有序):
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```javascript
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var findMode = function(root) {
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// 不使用额外空间,使用中序遍历,设置出现最大次数初始值为1
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let count = 0,maxCount = 1;
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let pre = root,res = [];
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// 1.确定递归函数及函数参数
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const travelTree = function(cur) {
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// 2. 确定递归终止条件
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if(cur === null) {
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return ;
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}
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travelTree(cur.left);
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// 3. 单层递归逻辑
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if(pre.val === cur.val) {
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count++;
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}else {
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count = 1;
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}
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pre = cur;
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if(count === maxCount) {
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res.push(cur.val);
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}
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if(count > maxCount) {
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res = [];
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maxCount = count;
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res.push(cur.val);
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}
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travelTree(cur.right);
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}
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travelTree(root);
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return res;
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};
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```
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@ -118,6 +118,27 @@ class Solution {
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}
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```
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```python
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# 方法一:可以使用切片方法
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class Solution:
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def reverseLeftWords(self, s: str, n: int) -> str:
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return s[n:] + s[0:n]
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# 方法二:也可以使用上文描述的方法,有些面试中不允许使用切片,那就使用上文作者提到的方法
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# class Solution:
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# def reverseLeftWords(self, s: str, n: int) -> str:
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# s = list(s)
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# s[0:n] = list(reversed(s[0:n]))
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# s[n:] = list(reversed(s[n:]))
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# s.reverse()
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# return "".join(s)
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# 时间复杂度:O(n)
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# 空间复杂度:O(n),python的string为不可变,需要开辟同样大小的list空间来修改
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```
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Go:
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```go
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@ -82,7 +82,7 @@ leetcode上没有纯01背包的问题,都是01背包应用方面的题目,
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那么可以有两个方向推出来dp[i][j],
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* 由dp[i - 1][j]推出,即背包容量为j,里面不放物品i的最大价值,此时dp[i][j]就是dp[i - 1][j]
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* 由dp[i - 1][j]推出,即背包容量为j,里面不放物品i的最大价值,此时dp[i][j]就是dp[i - 1][j]。(其实就是当物品i的重量大于背包j的重量时,物品i无法放进背包中,所以被背包内的价值依然和前面相同。)
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* 由dp[i - 1][j - weight[i]]推出,dp[i - 1][j - weight[i]] 为背包容量为j - weight[i]的时候不放物品i的最大价值,那么dp[i - 1][j - weight[i]] + value[i] (物品i的价值),就是背包放物品i得到的最大价值
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所以递归公式: dp[i][j] = max(dp[i - 1][j], dp[i - 1][j - weight[i]] + value[i]);
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