python复杂网络分析库NetworkX

1、python复杂网络分析库NetworkX阅读目录 无向图 有向图加权图 经典图论算法计算 强连通、弱连通子图条件过滤 pred,succNetworkX是一个用Python语言开发的图论与复杂网络建模工具，内置了常用的图与复杂网络分析算法，可以方便的进行复杂网络数据分析、仿真建模等工作。networkx支持创建简单无向图、有向图和多重图(multigraph)；内置许多标准的图论算法，节点可为任意数据；支持任意的边值维度，功能丰富，简单易用。引入模块importnetworkxasnxprintnx回到顶部无向图#!-*-coding:utf8-*-aspitimportnetworkxas

2、nximportmatplotlib.pyplotnx.draw(G)plt.savefig("wuxiangtu.png")plt.show()G=nx.Graph()G.add_node(1)G.add_edge(2,3)3)G.add_edge(3,2)边printprintprint#建立一个空的无向图G#添加一个节点1#添加一条边2-3(隐含着添加了两个节点2、#对于无向图，边3-2与边2-3被认为是一条"nodes:",G.nodesO"edges:",G.edgesO"numberofedges:",

3、#输出全部的节点：1,2,3#输出全部的边：(2,3)G.number_of_edges()#输出边的数量：1输出1nodes:1,2,32edges:(2,3)3numberofedges:1例2：骑#-*-coding:utf8-*-importnetworkxasnximportmatplotlib.pyplotaspitG=nx.DiGraph()G.add_node(l)G.add_node(2)#加点G.add_nodes_from(3,4,5,6)#加点集合G.add_cycle(l,2,3,4)#加环G.add_edge(l,3)G.add_edges_from(3,5),(3

4、,6),(6,7)#加边集合nx.draw(G)plt.savefig("youxiangtu.png")plt.show()回到顶部有向图例1:电#!*coding:utf8*importnetworkxasnximportmatplotlib.pyplotaspitG=nx.DiGraph()G.add_node(l)G.add_node(2)G.add_nodes_from(3,4,5,6)G.add_cycle(l,2,3,4)G.add_edge(l,3)G.add_edges_from(3,5),(3,6),(6,7)nx.draw(G)pit.savefig(

5、"youxiangtu.png")pit.show()侖#!*coding:utf8*importnetworkxasnximportmatplotlib.pyplotaspitG=nx.DiGraph()G.add_node(l)G.add_node(2)G.add_nodes_from(3,4,5,6)G.add_cycle(l,2,3,4)G.add_edge(l,3)G.add_edges_from(3,5),(3,6),(6,7)G=G.to_undirected()nx.draw(G)pit.savefig("wuxiangtu.png")p

6、it.show()注意区分以下2例例3-1#-*-coding:utf8-*-importnetworkxasnximportmatplotlib.pyplotaspitG=nx.DiGraph()road_nodes='a':1,'b':2,'c':3#road_nodes='a':1:1,'b':2:2,'c':3:3road_edges=('a','b'),('b','c')G.add_nodes_from(road_nodes.

7、iteritems()G.add_edges_from(road_edges)nx.draw(G)plt.savefig("youxiangtu.png")plt.show()#-*-coding:utf8-*-importnetworkxasnximportmatplotlib.pyplotaspitG=nx.DiGraph()#road_nodes='a':1,'b':2,'c':3road_nodes='a':1:1,'b':2:2,'c':3:3road_edges=(&

8、#39;a','b'),('b','c')G.add_nodes_from(road_nodes.iteritems()G.add_edges_from(road_edges)nx.draw(G)plt.savefig("youxiangtu.png")plt.show()加权图有向图和无向图都可以给边赋予权重，用到的方法是add_weighted_edges_from,它接受1个或多个三元组u,v,w作为参数，其中u是起点，v是终点，w是权重。例1:#!*coding:utf8*importnetworkxasnxi

9、mportmatplotlib.pyplotaspitG=nx.Graph()#建立一个空的无向图GG.add_edge(2,3)#添加一条边23(隐含着添加了两个节点2、3)G.add_weighted_edges_from(3,4,3.5),(3,5,7.0)#对于无向图，边3-2与边2-3被认为是一条边printG.get_edge_data(2,3)printG.get_edge_data(3,4)printG.get_edge_data(3,5)nx.draw(G)pit.savefig("wuxiangtu.png")pit.show()输出'weigh

10、t':3.5'weight':7.0经典图论算法计算计算1：求无向图的任意两点间的最短路径#*coding:cp936*importnetworkxasnximportmatplotlib.pyplotaspit#计算1：求无向图的任意两点间的最短路径G=nx.Graph()G.add_edges_from(1,2),(1,3),(1,4),(1,5),(4,5),(4,6),(5,6)path=nx.all_pairs_shortest_path(G)printpath1计算2：找图中两个点的最短路径鬲importnetworkxasnxG=nx.Graph()G.a

11、dd_nodes_from(1,2,3,4)G.add_edge(1,2)G.add_edge(3,4)try:n二nx.shortest_path_length(G,1,4)printnexceptnx.NetworkXNoPath:print'Nopath'回到顶部强连通、弱连通强连通：有向图中任意两点v1、v2间存在v1到v2的路径（path）及v2到v1的路径。弱联通：将有向图的所有的有向边替换为无向边，所得到的图称为原图的基图。如果一个有向图的基图是连通图，则有向图是弱连通图。距离例1：弱连通#*coding:utf8*importnetworkxasnximport

12、matplotlib.pyplotasplt#G=nx.path_graph(4,create_using二nx.Graph()#0123G=nx.path_graph(4,create_using二nx.DiGraph()#默认生成节点0123,生成有向变0->1,1->2,2->3G.add_path(7,&3)#生成有向边：7>8>3forcinnx.weakly_connected_components(G):printcprintlen(c)forcinsorted(nx.weakly_connected_components(G),key=le

13、n,reverse二True)nx.draw(G)plt.savefig("youxiangtu.png")plt.show()执行结果set(0,1,2,3,7,8)6例2：强连通电#-*-coding:utf8-*-importnetworkxasnximportmatplotlib.pyplotasplt#G=nx.path_graph(4,create_using二nx.Graph()#0123G=nx.path_graph(4,create_using二nx.DiGraph()G.add_path(3,&1)#forcinnx.strongly_conne

14、cted_components(G):# printc#printlen(c)forcinsorted(nx.strongly_connected_components(G),key=len,reverse二True)con=nx.strongly_connected_components(G)printconprinttype(con)printlist(con)nx.draw(G)pit.savefig("youxiangtu.png")pit.show()执行结果generatorobjectstrongly_connected_componentsat0x00000

15、00008AAlD80>type'generator'>set(8,1,2,3),set(0)回到顶部子图#-*-coding:utf8-*-importnetworkxasnximportmatplotlib.pyplotaspitG=nx.DiGraph()G.add_path(5,6,7,8)sub_graph=G.subgraph(5,6,8)#sub_graph=G.subgraph(5,6,8)#ok一样nx.draw(sub_graph)pit.savefig("youxiangtu.png")pit.show()回到顶部条件过滤#

16、原图#-*-coding:utf8-*-importnetworkxasnximportmatplotlib.pyplotaspltG=nx.DiGraph()road_nodes='a':'id':l,'b':'id':l,'c':'id':3,'d':'id':4road_edges二('a',，b'),('a',，c'),('a',，d'),(，b',，d，)G.add_nodes_

17、from(road_nodes)G.add_edges_from(road_edges)nx.draw(G)pit.savefig("youxiangtu.png")pit.show()#过滤函数#*coding:utf8*importnetworkxasnximportmatplotlib.pyplotaspitG=nx.DiGraph()defflt_func_draw():flt_func=lambdad:d'id'!=1returnflt_funcroad_nodes='a':'id':l,'b':&#

18、39;id':l,'c':'id':3,'d':'id':4road_edges二('a',，b'),('a',，c'),('a',，d'),(，b',，d，)G.add_nodes_from(road_nodes.iteritems()G.add_edges_from(road_edges)flt_func=flt_func_draw()part_G=G.subgraph(nforn,dinG.nodes_iter(data二True)iff

19、lt_func(d)nx.draw(part_G)pit.savefig("youxiangtu.png")pit.show()图Figure!刁|Icx=0,579437y=0-842171回到顶部wl»l-»l»|Q|s|iapred,succ#-*-coding:utf8-*-importnetworkxasnximportmatplotlib.pyplotaspitG=nx.DiGraph()road_nodes='a':'id':1,'b':'id':l,'c':'id':3road_edges=('a','b'),('a','c'),('c','d')G.add_nodes_from(road_nodes.iteritems()G.add_edges_from(road_edges)printG.nodes()printG.edges()print"a'spred",G.pred'a'pr