Java实现图的深度和广度优先遍历算法
Posted ljbguanli
tags:
篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了Java实现图的深度和广度优先遍历算法相关的知识,希望对你有一定的参考价值。
概述:
近期要学习写网络爬虫。所以把图的深度和广度搜索都再温习一下。
图结构展示:
实现过程:
首先,我们来看看图结构在代码中的实现。有三块逻辑:1.图中的节点:
public class GraphNode { public List<GraphEdge> edgeList = null; private String label = ""; public GraphNode(String label) { this.label = label; if (edgeList == null) { edgeList = new ArrayList<GraphEdge>(); } } /** * 给当前节点加入一条边 * GraphNode * @param edge * 加入的边 */ public void addEdgeList(GraphEdge edge) { edgeList.add(edge); } public String getLabel() { return label; } }
2.图中的边:
public class GraphEdge { private GraphNode nodeLeft; private GraphNode nodeRight; /** * @param nodeLeft * 边的左端 * @param nodeRight * 边的右端 */ public GraphEdge(GraphNode nodeLeft, GraphNode nodeRight) { this.nodeLeft = nodeLeft; this.nodeRight = nodeRight; } public GraphNode getNodeLeft() { return nodeLeft; } public GraphNode getNodeRight() { return nodeRight; } }
3.把节点和边组合成一个图结构:
public class MyGraph { private List<GraphNode> nodes = null; public void initGraph(int n) { if (nodes == null) { nodes = new ArrayList<GraphNode>(); } GraphNode node = null; for (int i = 0; i < n; i++) { node = new GraphNode(String.valueOf(i)); nodes.add(node); } } public void initGraph(int n, boolean b) { initGraph(n); GraphEdge edge01 = new GraphEdge(nodes.get(0), nodes.get(1)); GraphEdge edge02 = new GraphEdge(nodes.get(0), nodes.get(2)); GraphEdge edge13 = new GraphEdge(nodes.get(1), nodes.get(3)); GraphEdge edge14 = new GraphEdge(nodes.get(1), nodes.get(4)); GraphEdge edge25 = new GraphEdge(nodes.get(2), nodes.get(5)); GraphEdge edge26 = new GraphEdge(nodes.get(2), nodes.get(6)); GraphEdge edge37 = new GraphEdge(nodes.get(3), nodes.get(7)); GraphEdge edge47 = new GraphEdge(nodes.get(4), nodes.get(7)); GraphEdge edge56 = new GraphEdge(nodes.get(5), nodes.get(6)); nodes.get(0).addEdgeList(edge01); nodes.get(0).addEdgeList(edge02); nodes.get(1).addEdgeList(edge13); nodes.get(1).addEdgeList(edge14); nodes.get(2).addEdgeList(edge25); nodes.get(2).addEdgeList(edge26); nodes.get(3).addEdgeList(edge37); nodes.get(4).addEdgeList(edge47); nodes.get(5).addEdgeList(edge56); } public void initGraph() { initGraph(8, false); } public List<GraphNode> getGraphNodes() { return nodes; } }
有了图的结构,我们就能够进行一些实际的操作了。
深度优先搜索:
public class DFSearch { /** * 深度遍历 * DFSearch * @param node * 当前节点 * @param visited * 被訪问过的节点列表 */ public void searchTraversing(GraphNode node, List<GraphNode> visited) { // 推断是否遍历过 if (visited.contains(node)) { return; } visited.add(node); System.out.println("节点:" + node.getLabel()); for (int i = 0; i < node.edgeList.size(); i++) { searchTraversing(node.edgeList.get(i).getNodeRight(), visited); } } }
广度优先搜索:
public class BFSearch { /** * 广度优先搜索 * BFSearch * @param node * 搜索的入口节点 */ public void searchTraversing(GraphNode node) { List<GraphNode> visited = new ArrayList<GraphNode>(); // 已经被訪问过的元素 Queue<GraphNode> q = new LinkedList<GraphNode>(); // 用队列存放依次要遍历的元素 q.offer(node); while (!q.isEmpty()) { GraphNode currNode = q.poll(); if (!visited.contains(currNode)) { visited.add(currNode); System.out.println("节点:" + currNode.getLabel()); for (int i = 0; i < currNode.edgeList.size(); i++) { q.offer(currNode.edgeList.get(i).getNodeRight()); } } } } }
执行结果:
源代码下载:
以上是关于Java实现图的深度和广度优先遍历算法的主要内容,如果未能解决你的问题,请参考以下文章