Python数据结构与算法之图的广度优先与深度优先搜索算法示例

""" 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

""""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)