本文实例讲述了Python数据结构与算法之图的广度优先与深度优先搜索算法。分享给大家供大家参考，具体如下：
根据维基百科的伪代码实现：
广度优先BFS：
使用队列，集合
标记初始结点已被发现，放入队列
每次循环从队列弹出一个结点
将该节点的所有相连结点放入队列，并标记已被发现
通过队列，将迷宫路口所有的门打开，从一个门进去继续打开里面的门，然后返回前一个门处
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""" procedure BFS(G,v) is let Q be a queue Q.enqueue(v) label v as discovered while Q is not empty v ← Q.dequeue() procedure(v) for all edges from v to w in G.adjacentEdges(v) do if w is not labeled as discovered Q.enqueue(w) label w as discovered"""def procedure(v): passdef BFS(G,v0): """ 广度优先搜索 """ q, s = [], set() q.extend(v0) s.add(v0) while q: # 当队列q非空 v = q.pop(0) procedure(v) for w in G[v]: # 对图G中顶点v的所有邻近点w if w not in s: # 如果顶点 w 没被发现 q.extend(w) s.add(w) # 记录w已被发现 |
深度优先DFS
使用 栈，集合
初始结点入栈
每轮循环从栈中弹出一个结点，并标记已被发现
对每个弹出的结点，将其连接的所有结点放到队列中
通过栈的结构，一步步深入挖掘
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""""Pseudocode[edit]Input: A graph G and a vertex v of GOutput: All vertices reachable from v labeled as discoveredA recursive implementation of DFS:[5]1 procedure DFS(G,v):2 label v as discovered3 for all edges from v to w in G.adjacentEdges(v) do4 if vertex w is not labeled as discovered then5 recursively call DFS(G,w)A non-recursive implementation of DFS:[6]1 procedure DFS-iterative(G,v):2 let S be a stack3 S.push(v)4 while S is not empty5 v = S.pop()6 if v is not labeled as discovered:7 label v as discovered8 for all edges from v to w in G.adjacentEdges(v) do9 S.push(w)"""def DFS(G,v0): S = [] S.append(v0) label = set() while S: v = S.pop() if v not in label: label.add(v) procedure(v) for w in G[v]: S.append(w) |
希望本文所述对大家Python程序设计有所帮助。
原文链接：http://www.cnblogs.com/hanahimi/p/4692601.html
