TypeScript方式实现源码
// 图的遍历算法 // 算 法 数据结构 描 述 // 深度优先搜索 栈 通过将顶点存入栈中，顶点是沿着路径被探索的，存在新的相 // 邻顶点就去访问 // 广度优先搜索 队列 通过将顶点存入队列中，最先入队列的顶点先被探索 // 当要标注已经访问过的顶点时，我们用三种颜色来反映它们的状态。 // 白色：表示该顶点还没有被访问。 // 灰色：表示该顶点被访问过，但并未被探索过。 // 黑色：表示该顶点被访问过且被完全探索过。 // 广度优先搜索算法会从指定的第一个顶点开始遍历图， 先访问其所有的相邻点， 就像一次访 // 问图的一层
1 class Graph { 2 vertices = []; 3 adjList = new Dictionary(); 4 public addVertex(v) { 5 this.vertices.push(v); 6 this.adjList.set(v, []); 7 } 8 public addEdge(v, w) { 9 this.adjList.get(v).push(w); 10 this.adjList.get(w).push(v); 11 } 12 public initializeColor() { 13 let color = [], length = this.vertices.length; 14 for (var i = 0; i < length; i++) { 15 color[this.vertices[i]] = 'white'; 16 } 17 return color; 18 } 19 /** 20 * 宽度优先搜索 21 * @param v 22 * @param callback 23 */ 24 public bfs(v, callback) { 25 let color = this.initializeColor(), 26 queue = new Queue(); 27 queue.enqueue(v); 28 while (!queue.isEmpty()) { 29 let u = queue.dequeue(), 30 neighbors = this.adjList.get(u); 31 color[u] = 'grey'; 32 for (let i = 0; i < neighbors.length; i++) { 33 let w = neighbors[i]; 34 if (color[w] === 'white') { 35 color[w] = 'grey'; 36 queue.enqueue(w); 37 } 38 } 39 color[u] = 'black'; 40 if (callback) { 41 callback(u); 42 } 43 } 44 } 45 /** 46 * 寻找最短路径 47 * @param v 48 */ 49 public BFS(v) { 50 let color = this.initializeColor(), 51 queue = new Queue(), 52 d = [], 53 pred = []; 54 queue.enqueue(v); 55 for (var i = 0; i < this.vertices.length; i++) { 56 d[this.vertices[i]] = 0; 57 pred[this.vertices[i]] = null; 58 } 59 while (!queue.isEmpty()) { 60 let u = queue.dequeue(), 61 neighbors = this.adjList.get(u); 62 color[u] = 'grey'; 63 for (let i = 0; i < neighbors.length; i++) { 64 let w = neighbors[i]; 65 if (color[w] === 'white') { 66 color[w] = 'grey'; 67 d[w] = d[u] + 1; 68 pred[w] = u; 69 queue.enqueue(w); 70 } 71 } 72 color[u] = 'black'; 73 } 74 return { 75 distances: d, 76 predecessors: pred 77 } 78 } 79 public toString() { 80 let s = ''; 81 for (let i = 0; i < this.vertices.length; i++) { 82 s += this.vertices[i] + ' -> '; 83 let neighbors = this.adjList.get(this.vertices[i]); 84 for (var j = 0; j < neighbors.length; j++) { 85 s += neighbors[j] + ' '; 86 } 87 s += ' '; 88 } 89 return s; 90 } 91 } 92 var graph = new Graph(); 93 var myVertices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']; //{7} 94 for (var i = 0; i < myVertices.length; i++) { //{8} 95 graph.addVertex(myVertices[i]); 96 } 97 graph.addEdge('A', 'B'); //{9} 98 graph.addEdge('A', 'C'); 99 graph.addEdge('A', 'D'); 100 graph.addEdge('C', 'D'); 101 graph.addEdge('C', 'G'); 102 graph.addEdge('D', 'G'); 103 graph.addEdge('D', 'H'); 104 graph.addEdge('B', 'E'); 105 graph.addEdge('B', 'F'); 106 graph.addEdge('E', 'I'); 107 108 console.log(graph.toString()); 109 110 function printNode(value) { 111 console.log('Visited vertex:' + value); 112 } 113 graph.bfs(myVertices[0], printNode); 114 115 var shortestPathA = graph.BFS(myVertices[0]); 116 console.log(shortestPathA);
JavaScript方式实现源码
1 var Graph = (function () { 2 function Graph() { 3 this.vertices = []; 4 this.adjList = new Dictionary(); 5 } 6 Graph.prototype.addVertex = function (v) { 7 this.vertices.push(v); 8 this.adjList.set(v, []); 9 }; 10 Graph.prototype.addEdge = function (v, w) { 11 this.adjList.get(v).push(w); 12 this.adjList.get(w).push(v); 13 }; 14 Graph.prototype.initializeColor = function () { 15 var color = [], length = this.vertices.length; 16 for (var i = 0; i < length; i++) { 17 color[this.vertices[i]] = 'white'; 18 } 19 return color; 20 }; 21 /** 22 * 宽度优先搜索 23 * @param v 24 * @param callback 25 */ 26 Graph.prototype.bfs = function (v, callback) { 27 var color = this.initializeColor(), queue = new Queue(); 28 queue.enqueue(v); 29 while (!queue.isEmpty()) { 30 var u = queue.dequeue(), neighbors = this.adjList.get(u); 31 color[u] = 'grey'; 32 for (var i_1 = 0; i_1 < neighbors.length; i_1++) { 33 var w = neighbors[i_1]; 34 if (color[w] === 'white') { 35 color[w] = 'grey'; 36 queue.enqueue(w); 37 } 38 } 39 color[u] = 'black'; 40 if (callback) { 41 callback(u); 42 } 43 } 44 }; 45 /** 46 * 寻找最短路径 47 * @param v 48 */ 49 Graph.prototype.BFS = function (v) { 50 var color = this.initializeColor(), queue = new Queue(), d = [], pred = []; 51 queue.enqueue(v); 52 for (var i = 0; i < this.vertices.length; i++) { 53 d[this.vertices[i]] = 0; 54 pred[this.vertices[i]] = null; 55 } 56 while (!queue.isEmpty()) { 57 var u = queue.dequeue(), neighbors = this.adjList.get(u); 58 color[u] = 'grey'; 59 for (var i_2 = 0; i_2 < neighbors.length; i_2++) { 60 var w = neighbors[i_2]; 61 if (color[w] === 'white') { 62 color[w] = 'grey'; 63 d[w] = d[u] + 1; 64 pred[w] = u; 65 queue.enqueue(w); 66 } 67 } 68 color[u] = 'black'; 69 } 70 return { 71 distances: d, 72 predecessors: pred 73 }; 74 }; 75 Graph.prototype.toString = function () { 76 var s = ''; 77 for (var i_3 = 0; i_3 < this.vertices.length; i_3++) { 78 s += this.vertices[i_3] + ' -> '; 79 var neighbors = this.adjList.get(this.vertices[i_3]); 80 for (var j = 0; j < neighbors.length; j++) { 81 s += neighbors[j] + ' '; 82 } 83 s += ' '; 84 } 85 return s; 86 }; 87 return Graph; 88 }());