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Commit b44b282

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code: 新增结构
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# No.110 平衡二叉树
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给定一个二叉树,判断它是否是高度平衡的二叉树。
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本题中,一棵高度平衡二叉树定义为:
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一个二叉树每个节点 的左右两个子树的高度差的绝对值不超过1。
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## 示例
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示例 1:
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给定二叉树 [3,9,20,null,null,15,7]
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3
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/ \
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9 20
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/ \
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15 7
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返回 true 。
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示例 2:
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给定二叉树 [1,2,2,3,3,null,null,4,4]
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1
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/ \
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2 2
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/ \
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3 3
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/ \
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4 4
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返回 false 。
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## 解题思路
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### 1、自顶向下发
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遍历每一个节点,计算节点的左右子树高度。
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```javascript
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var isBalanced = function(root) {
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if (root == null) return true;
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return (Math.abs(leftHeight(root) - rightHeight(root)) <= 1) && isBalanced(root.left) && isBalanced(root.right)
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};
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var leftHeight = function(node) {
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if (!node) return 0;
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return height(node.left) + 1;
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}
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var rightHeight = function(node) {
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if (!node) return 0;
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return height(node.right) + 1;
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}
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var height = function(node) {
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return Math.max(leftHeight(node), rightHeight(node));
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}
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```
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### 2、自底向上
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对二叉树做深度优先遍历DFS,递归过程中,当我们发现有一例 左/右子树高度差 > 1 的情况时,代表此树不是平衡树,返回-1;
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当发现不是平衡树时,后面的高度计算都没有意义了,因此一路返回-1,避免后续多余计算。
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最差情况是对树做一遍完整DFS,时间复杂度为 O(N)。
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```javascript
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var isBalanced = function(root) {
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return depth(root) != -1;
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};
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var depth = function(root) {
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if (!root) return 0;
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let left = depth(root.left);
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if (left == -1) return -1;
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let right = depth(root.right);
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if (right == -1) return -1;
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return Math.abs(left - right) < 2 ? Math.max(left, right) + 1 : -1;
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}
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```
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module.exports = {
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env: {
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browser: true,
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es6: true,
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},
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extends: [
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'airbnb-base',
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],
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globals: {
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Atomics: 'readonly',
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SharedArrayBuffer: 'readonly',
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},
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parserOptions: {
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ecmaVersion: 2018,
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sourceType: 'module',
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},
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rules: {
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},
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};
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{
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"root": true,
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"extends": "airbnb",
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"plugins": ["jest"],
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"env": {
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"jest/globals": true
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},
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"rules": {
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"no-bitwise": "off",
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"no-lonely-if": "off",
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"class-methods-use-this": "off",
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"arrow-body-style": "off",
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"no-loop-func": "off"
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}
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}

‎算法与数据结构学习/README.md‎

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- [堆栈](data-structures/stack)
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- [哈希表](data-structures/hash-table)
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- [堆](data-structures/heap)
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- [有限队列](data-structures/priority-queue)
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- [优先队列](data-structures/priority-queue)
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- [字典树](data-structures/trie)
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## 算法
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function shellSort(arr) {
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var len = arr.length,
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temp,
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gap = Math.floor(len / 2);
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while (gap > 0) {
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for (var i = gap; i < len; i++) {
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temp = arr[i];
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for (var j = i-gap; j >= 0 && arr[j] > temp; j -= gap) {
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arr[j+gap] = arr[j];
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}
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arr[j+gap] = temp;
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}
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gap = Math.floor(gap / 2);
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}
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return arr;
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}
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console.log(shellSort([5,2,4,1,3]))
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export default class InsertionSort {
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sort(originalArray) {
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const array = [...originalArray];
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for (let i = 1; i < array.length; i++) {
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let currentIdx = i;
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while ((array[currentIdx] < array[currentIdx - 1]) && currentIdx > 0) {
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const tmp = array[currentIdx - 1];
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array[currentIdx - 1] = array[currentIdx];
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array[currentIdx] = tmp;
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currentIdx--;
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}
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}
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return array;
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}
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}
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# 插入排序
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插入排序是一种构建简单的排序算法,最终排序的数组(或列表)一次一个。在大型列表上,效率要比在大型列表上低得多
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高级算法,例如快速排序,堆排序或合并排序。
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![Algorithm Visualization](https://upload.wikimedia.org/wikipedia/commons/4/42/Insertion_sort.gif)
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![Algorithm Visualization](https://upload.wikimedia.org/wikipedia/commons/0/0f/Insertion-sort-example-300px.gif)
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## 复杂度
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| 名称 | 最优 | 平均 | 最差 | Memory | Stable | Comments |
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| --------------------- | :-------------: | :-----------------: | :-----------------: | :-------: | :-------: | :-------- |
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| **Insertion sort** | n | n<sup>2</sup> | n<sup>2</sup> | 1 | Yes | |
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## References
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[Wikipedia](https://en.wikipedia.org/wiki/Insertion_sort)
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import InsertionSort from '../InsertionSort';
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import {
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equalArr,
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notSortedArr,
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reverseArr,
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sortedArr,
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SortTester,
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} from '../../SortTester';
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describe('HeapSort', () => {
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it('should sort array', () => {
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SortTester.testSort(InsertionSort);
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});
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it('should sort negative numbers', () => {
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SortTester.testNegativeNumbersSort(InsertionSort);
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});
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});
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export default class QuickSortInPlace extends Sort {
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sort(
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originalArray,
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inputLowIndex = 0,
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inputHighIndex = originalArray.length - 1,
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recursiveCall = false,
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) {
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// 复制一份数组,然后对array进行原地排序
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const array = recursiveCall ? originalArray : [...originalArray];
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const partitionArray = (lowIndex, highIndex) => {
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const swap = (leftIndex, rightIndex) => {
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const temp = array[leftIndex];
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array[leftIndex] = array[rightIndex];
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array[rightIndex] = temp;
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}
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const pivot = array[highIndex];
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}
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}
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}
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function quickSort(arr, low, high) {
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// 调整数组
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let i = adjustArr(arr, low, high);
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// 分治
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quickSort(arr, low, i-1);
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quickSort(arr, i+1, high);
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}
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function adjustArr(arr, low, high) {
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let pivot = arr[low];
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while (low < high) {
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while (arr[high] > pivot)
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high--;
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arr[low++] = arr[high];
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while (arr[low] < pivot)
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low++;
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arr[high--] = arr[low];
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}
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arr[low] = pivot;
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return low;
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}
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let arr = [72,6,57,88,60,42,83,73,48,85];
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quickSort(arr, 0, arr.length-1);
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console.log(arr);
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function quickSort(arr, low, high) {
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if (low < high) {
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// 调整数组
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let i = adjustArr(arr, low, high);
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// 分治
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quickSort(arr, low, i-1);
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quickSort(arr, i+1, high);
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}
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}
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function adjustArr(arr, low, high) {
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let pivot = arr[low];
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while (low < high) {
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while (low < high && arr[high] > pivot)
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high--;
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arr[low] = arr[high];
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while (low < high && arr[low] < pivot)
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low++;
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arr[high] = arr[low];
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}
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arr[low] = pivot;
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return low;
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}
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let arr = [72,6,57,88,60,42,83,73,48,85];
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quickSort(arr, 0, arr.length-1);
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console.log(arr);

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