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Merge pull request krahets#196 from RiverTwilight/patch-1
code: added Typescript and Javascript examples
2 parents 0e49f00 + 5a24254 commit 1f5f7e1

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6 files changed

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‎.prettierrc

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{
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"tabWidth": 4,
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"useTabs": false
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}

‎codes/javascript/chapter_computational_complexity/time_complexity.js

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/**
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* File: time_complexity.js
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* Created Time: 2023-01-02
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* Author: RiverTwilight ([email protected])
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*/
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/* 常数阶 */
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function constant(n) {
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let count = 0;
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const size = 100000;
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for (let i = 0; i < size; i++) count++;
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return count;
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}
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/* 线性阶 */
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function linear(n) {
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let count = 0;
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for (let i = 0; i < n; i++) count++;
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return count;
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}
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/* 线性阶（遍历数组） */
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function arrayTraversal(nums) {
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let count = 0;
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// 循环次数与数组长度成正比
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for (let i = 0; i < nums.length; i++) {
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count++;
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}
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return count;
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}
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/* 平方阶 */
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function quadratic(n) {
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let count = 0;
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// 循环次数与数组长度成平方关系
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for (let i = 0; i < n; i++) {
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for (let j = 0; j < n; j++) {
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count++;
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}
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}
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return count;
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}
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/* 平方阶（冒泡排序） */
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function bubbleSort(nums) {
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let count = 0; // 计数器
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// 外循环：待排序元素数量为 n-1, n-2, ..., 1
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for (let i = nums.length - 1; i > 0; i--) {
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// 内循环：冒泡操作
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for (let j = 0; j < i; j++) {
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if (nums[j] > nums[j + 1]) {
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// 交换 nums[j] 与 nums[j + 1]
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let tmp = nums[j];
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nums[j] = nums[j + 1];
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nums[j + 1] = tmp;
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count += 3; // 元素交换包含 3 个单元操作
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}
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}
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}
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return count;
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}
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/* 指数阶（循环实现） */
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function exponential(n) {
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let count = 0,
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base = 1;
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// cell 每轮一分为二，形成数列 1, 2, 4, 8, ..., 2^(n-1)
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for (let i = 0; i < n; i++) {
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for (let j = 0; j < base; j++) {
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count++;
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}
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base *= 2;
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}
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// count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
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return count;
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}
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/* 指数阶（递归实现） */
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function expRecur(n) {
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if (n == 1) return 1;
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return expRecur(n - 1) + expRecur(n - 1) + 1;
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}
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/* 对数阶（循环实现） */
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function logarithmic(n) {
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let count = 0;
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while (n > 1) {
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n = n / 2;
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count++;
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}
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return count;
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}
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/* 对数阶（递归实现） */
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function logRecur(n) {
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if (n <= 1) return 0;
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return logRecur(n / 2) + 1;
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}
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/* 线性对数阶 */
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function linearLogRecur(n) {
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if (n <= 1) return 1;
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let count = linearLogRecur(n / 2) + linearLogRecur(n / 2);
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for (let i = 0; i < n; i++) {
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count++;
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}
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return count;
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}
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/* 阶乘阶（递归实现） */
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function factorialRecur(n) {
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if (n == 0) return 1;
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let count = 0;
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// 从 1 个分裂出 n 个
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for (let i = 0; i < n; i++) {
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count += factorialRecur(n - 1);
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}
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return count;
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}
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/* Driver Code */
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// 可以修改 n 运行，体会一下各种复杂度的操作数量变化趋势
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const n = 8;
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console.log("输入数据大小 n = " + n);
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let count = constant(n);
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console.log("常数阶的计算操作数量 = " + count);
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count = linear(n);
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console.log("线性阶的计算操作数量 = " + count);
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count = arrayTraversal(new Array(n));
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console.log("线性阶（遍历数组）的计算操作数量 = " + count);
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count = quadratic(n);
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console.log("平方阶的计算操作数量 = " + count);
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let nums = new Array(n);
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for (let i = 0; i < n; i++) nums[i] = n - i; // [n,n-1,...,2,1]
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count = bubbleSort(nums);
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console.log("平方阶（冒泡排序）的计算操作数量 = " + count);
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count = exponential(n);
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console.log("指数阶（循环实现）的计算操作数量 = " + count);
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count = expRecur(n);
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console.log("指数阶（递归实现）的计算操作数量 = " + count);
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count = logarithmic(n);
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console.log("对数阶（循环实现）的计算操作数量 = " + count);
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count = logRecur(n);
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console.log("对数阶（递归实现）的计算操作数量 = " + count);
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count = linearLogRecur(n);
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console.log("线性对数阶（递归实现）的计算操作数量 = " + count);
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count = factorialRecur(n);
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console.log("阶乘阶（递归实现）的计算操作数量 = " + count);

‎codes/javascript/chapter_computational_complexity/worst_best_time_complexity.js

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/*
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* File: worst_best_time_complexity.js
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* Created Time: 2023-01-05
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* Author: RiverTwilight ([email protected])
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*/
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/* 生成一个数组，元素为 { 1, 2, ..., n }，顺序被打乱 */
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function randomNumbers(n) {
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let nums = Array(n);
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// 生成数组 nums = { 1, 2, 3, ..., n }
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for (let i = 0; i < n; i++) {
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nums[i] = i + 1;
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}
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// 随机打乱数组元素
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for (let i = 0; i < n; i++) {
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let r = Math.floor(Math.random() * (i + 1));
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let temp = nums[i];
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nums[i] = nums[r];
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nums[r] = temp;
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}
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return nums;
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}
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/* 查找数组 nums 中数字 1 所在索引 */
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function findOne(nums) {
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for (let i = 0; i < nums.length; i++) {
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if (nums[i] === 1) {
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return i;
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}
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}
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return -1;
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}
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/* Driver Code */
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function main() {
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for (let i = 0; i < 10; i++) {
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let n = 100;
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let nums = randomNumbers(n);
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let index = findOne(nums);
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console.log(
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"\n数组 [ 1, 2, ..., n ] 被打乱后 = [" + nums.join(", ") + "]"
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);
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console.log("数字 1 的索引为 " + index);
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}
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}

‎codes/typescript/chapter_computational_complexity/time_complexity.ts

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/**
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* File: time_complexity.ts
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* Created Time: 2023-01-02
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* Author: RiverTwilight ([email protected])
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*/
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/* 常数阶 */
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function constant(n: number): number {
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let count = 0;
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const size = 100000;
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for (let i = 0; i < size; i++) count++;
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return count;
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}
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/* 线性阶 */
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function linear(n: number): number {
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let count = 0;
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for (let i = 0; i < n; i++) count++;
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return count;
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}
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/* 线性阶（遍历数组） */
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function arrayTraversal(nums: number[]): number {
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let count = 0;
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// 循环次数与数组长度成正比
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for (let i = 0; i < nums.length; i++) {
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count++;
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}
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return count;
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}
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/* 平方阶 */
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function quadratic(n: number): number {
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let count = 0;
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// 循环次数与数组长度成平方关系
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for (let i = 0; i < n; i++) {
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for (let j = 0; j < n; j++) {
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count++;
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}
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}
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return count;
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}
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/* 平方阶（冒泡排序） */
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function bubbleSort(nums: number[]): number {
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let count = 0; // 计数器
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// 外循环：待排序元素数量为 n-1, n-2, ..., 1
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for (let i = nums.length - 1; i > 0; i--) {
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// 内循环：冒泡操作
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for (let j = 0; j < i; j++) {
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if (nums[j] > nums[j + 1]) {
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// 交换 nums[j] 与 nums[j + 1]
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let tmp = nums[j];
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nums[j] = nums[j + 1];
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nums[j + 1] = tmp;
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count += 3; // 元素交换包含 3 个单元操作
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}
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}
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}
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return count;
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}
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/* 指数阶（循环实现） */
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function exponential(n: number): number {
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let count = 0,
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base = 1;
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// cell 每轮一分为二，形成数列 1, 2, 4, 8, ..., 2^(n-1)
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for (let i = 0; i < n; i++) {
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for (let j = 0; j < base; j++) {
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count++;
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}
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base *= 2;
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}
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// count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
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return count;
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}
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/* 指数阶（递归实现） */
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function expRecur(n: number): number {
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if (n == 1) return 1;
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return expRecur(n - 1) + expRecur(n - 1) + 1;
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}
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/* 对数阶（循环实现） */
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function logarithmic(n: number): number {
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let count = 0;
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while (n > 1) {
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n = n / 2;
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count++;
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}
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return count;
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}
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/* 对数阶（递归实现） */
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function logRecur(n: number): number {
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if (n <= 1) return 0;
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return logRecur(n / 2) + 1;
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}
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/* 线性对数阶 */
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function linearLogRecur(n: number): number {
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if (n <= 1) return 1;
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let count = linearLogRecur(n / 2) + linearLogRecur(n / 2);
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for (let i = 0; i < n; i++) {
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count++;
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}
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return count;
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}
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/* 阶乘阶（递归实现） */
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function factorialRecur(n: number): number {
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if (n == 0) return 1;
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let count = 0;
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// 从 1 个分裂出 n 个
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for (let i = 0; i < n; i++) {
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count += factorialRecur(n - 1);
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}
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return count;
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}
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/* Driver Code */
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// 可以修改 n 运行，体会一下各种复杂度的操作数量变化趋势
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const n = 8;
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console.log("输入数据大小 n = " + n);
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let count = constant(n);
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console.log("常数阶的计算操作数量 = " + count);
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count = linear(n);
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console.log("线性阶的计算操作数量 = " + count);
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count = arrayTraversal(new Array(n));
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console.log("线性阶（遍历数组）的计算操作数量 = " + count);
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count = quadratic(n);
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console.log("平方阶的计算操作数量 = " + count);
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var nums = new Array(n);
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for (let i = 0; i < n; i++) nums[i] = n - i; // [n,n-1,...,2,1]
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count = bubbleSort(nums);
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console.log("平方阶（冒泡排序）的计算操作数量 = " + count);
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count = exponential(n);
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console.log("指数阶（循环实现）的计算操作数量 = " + count);
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count = expRecur(n);
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console.log("指数阶（递归实现）的计算操作数量 = " + count);
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count = logarithmic(n);
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console.log("对数阶（循环实现）的计算操作数量 = " + count);
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count = logRecur(n);
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console.log("对数阶（递归实现）的计算操作数量 = " + count);
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count = linearLogRecur(n);
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console.log("线性对数阶（递归实现）的计算操作数量 = " + count);
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count = factorialRecur(n);
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console.log("阶乘阶（递归实现）的计算操作数量 = " + count);

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