1.工具类：队列和字典

export class DictionNary {// 字典的封装constructor() {this.items = {}}set(key, value) {// 添加键this.items[key] = value}has(key){// 判断键是否存在return this.items.hasOwnProperty(key)}get(key){// 获取键的valuereturn this.has(key) ? this.items[key] : undefined}remove (key){// 删除键if(this.has(key)){delete this.items[key]return true}return false}keys(){// 获取所有的键return Object.keys(this.items)}values(){// 获取所有的值return Object}size(){// 获取键值对的数量return this.keys().length}clear(){// 清空字典this.items = {}}toString(){// 转换为字符串if(this.size() > 0){let objString = `{${this.keys().join(',')}}`return objString}else{return '{}'}}
}export class Queue {// 队列的封装constructor() {this.items = []}// 方法enqueue(element) {// 添加元素到队列this.items.push(element)}dequeue() {// 移除队列的第一个元素return this.items.shift()}front() {// 返回队列的第一个元素return this.items[0]}isEmpty() {// 判断队列是否为空return this.items.length == 0}size() {// 返回队列的元素个数return this.items.length}toString() {return this.items.toString()}}

2. 图的封装

class Graph {constructor() {// 顶点this.vertexes = []// 边this.edges = new DictionNary()}// 方法addVertex(v){// 添加顶点this.vertexes.push(v)// 顶点对于边数组的初始化this.edges.set(v, [])}addEdge(v1, v2){// 无向图中边的设置this.edges.get(v1).push(v2)this.edges.get(v2).push(v1)}toString(){let result = ''for(let i = 0; i < this.vertexes.length; i++){result += this.vertexes[i] + ' -> 'const neighbors = this.edges.get(this.vertexes[i])for(let j = 0; j < neighbors.length; j++){result += neighbors[j] + ' '}result += '\n'}return result}initializeColor(){// 顶点遍历颜色初始化const colors = []for(let i = 0; i < this.vertexes.length; i++){colors[this.vertexes[i]] = 'white'}return colors}bfs(firstVertex, callback){// 广度优先遍历// 顶点遍历测试// 1.层序遍历：Breadth-First Search (BFS)// 2.深度遍历：Depth-First Search (DFS)// 3.为了记录顶点是否被访问过，我们使用三种颜色定义顶点的状态// 1.白色：表示该顶点还没有被访问// 2.灰色：表示该顶点被访问过，但并未被探索(被探索意思是其所有相邻顶点都被访问过)// 3.黑色：表示该顶点被访问过且被完全探索// 1.初始化顶点颜色const colors = this.initializeColor()// 2.创建队列const queue = new Queue()// 3.将第一个顶点加入队列queue.enqueue(firstVertex)// 4.循环遍历队列while(!queue.isEmpty()){// 4.1.从队列中取出一个顶点const v = queue.dequeue()// 4.2.获取和该顶点相邻的顶点const neighbors = this.edges.get(v)// 4.3.将当前顶点的颜色设置为灰色（被访问过）   colors[v] = 'gray'// 4.4.遍历该顶点的所有相邻顶点for(let i = 0; i < neighbors.length; i++){const w = neighbors[i]if(colors[w] === 'white'){colors[w] = 'gray'queue.enqueue(w) }}// 4.5.将当前顶点设置为黑色（被探索）colors[v] = 'black'// 4.6.调用callback函数callback(v)}}dfs(initVertex, callback){// 1.初始化颜色const colors = this.initializeColor()// 2.递归函数this.dfsVisit(initVertex, colors, callback)}dfsVisit(vertexes, colors, callback){// 1.访问过节点置灰色colors[vertexes] = 'gray'// 2.调用callback函数callback(vertexes)// 3.获取和该顶点相邻的顶点const neighbors = this.edges.get(vertexes)for(let i = 0; i < neighbors.length; i++){const w = neighbors[i]if(colors[w] === 'white'){this.dfsVisit(w, colors, callback)}}// 4.访问完节点置黑色colors[vertexes] = 'black'}}

图测试用例

 const graph = new Graph()// 1.添加顶点const myVertices = ['A', 'B', 'C', 'D', 'E', 'F','G', 'H','I']for(let i = 0; i < myVertices.length; i++){graph.addVertex(myVertices[i])}// 2.添加边graph.addEdge('A', 'B')graph.addEdge('A', 'C')graph.addEdge('A', 'D')graph.addEdge('C', 'D')graph.addEdge('C', 'G')graph.addEdge('D', 'G')graph.addEdge('D', 'H')graph.addEdge('B', 'E')graph.addEdge('B', 'F')graph.addEdge('E', 'I')console.log(graph.toString())// 测试广度优先遍历let result = ''graph.bfs(graph.vertexes[0], function(v){result += v + ' '})console.log(result)// 测试深度优先遍历let deepRsult = ''graph.dfs(graph.vertexes[0], function(v){deepRsult += v + ' '})console.log(deepRsult)