【Python学习系列二十六】networkx库图最短路径求解

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场景：基于python库networkx来求解图最短路径，相关算法基础参考

http://blog.csdn.net/fjssharpsword/article/details/52931373

http://blog.csdn.net/fjssharpsword/article/details/52953640

可看networkx源码了解其内部算法用的原理。

代码：

# -*- coding: utf-8 -*-import networkx as nximport matplotlib.pyplot as plt#读取文件，获取节点和边f = open("D:\\tmp\\gy_contest_link_top.txt", "r")  nodelist=[]edgelist=[]while True:      line = f.readline()      if line:          pass    # do something here         line=line.strip()        node=line.split(';')[0]#获取图节点        nodelist.append(node)        in_nodes=line.split(';')[1].split('#')#获取图边，该节点是终点        for ins in range( len(in_nodes) ) :            if in_nodes[ins].strip() !='':                 in_edge=(in_nodes[ins],node)                if in_edge not in edgelist:                    edgelist.append(in_edge)        out_nodes=line.split(';')[2].split('#')#获取图边，该节点是起点          for ins in range( len(out_nodes) ) :            if out_nodes[ins].strip() !='':                 out_edge=(node,out_nodes[ins])                if out_edge not in edgelist:                    edgelist.append(out_edge)    else:          breakf.close()del nodelist[0] #删除表头生成的节点del edgelist[0]del edgelist[0] #删除表头生成的边#print len(nodelist) #图节点#print len(edgelist) #边数#有向图构建G=nx.DiGraph()G.add_nodes_from(nodelist)G.add_edges_from(edgelist)#任意两点间最短路径'''try:    n=nx.shortest_path_length(G,1,4)    print nexcept nx.NetworkXNoPath:    print 'No path''''path=nx.all_pairs_shortest_path(G)#for item in path.items():#    print itemprint path.popitem()#强联通和弱联通for c in nx.weakly_connected_components(G):#弱联通    print c    con = nx.strongly_connected_components(G)#强联通print conprint type(con)print list(con)#有向图绘制nx.draw_networkx(G, pos=None, arrows=True, with_labels=False)#with_labels=False不带节点名#plt.savefig('D:\\tmp\\it.png')plt.show()

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