Introduction to the Modeling and Analysis of Complex Systems

310 CHAPTER 15. BASICS OF NETWORKSExercise 15.8 Construct a graph by generating a complete graph made of 10nodes, and then connect a new additional node to each of the 10 nodes, using oneedge each.Exercise 15.9 Create Zachary’s Karate Club graph using NetworkX’s built-infunction, and inspect its nodes and edges to see if they have any non-topologicalproperties.15.4 Visualizing Networks with NetworkXNetworkX also provides functions for visualizing networks. They are not as powerful asother more specialized software 1 , but still quite handy and useful, especially for small- tomid-sized network visualization. Those visualization functions depend on the functionsdefined in matplotlib (pylab), so we need to import it before visualizing networks.The simplest way is to use NetworkX’s draw function:Code 15.11: karate-club-visualization.pyfrom pylab import *import networkx as nxg = nx.karate_club_graph()nx.draw(g)show()The result is shown in Fig. 15.3. Red circles represent the nodes, and the black linesconnecting them represent the edges. By default, the layout of the nodes and edgesis automatically determined by the Fruchterman-Reingold force-directed algorithm [62](called “spring layout” in NetworkX), which conducts a pseudo-physics simulation of themovements of the nodes, assuming that each edge is a spring with a fixed equilibriumdistance. This heuristic algorithm tends to bring groups of well-connected nodes closerto each other, making the result of visualization more meaningful and aesthetically morepleasing.1 For example, Gephi (http://gephi.github.io/) can handle much larger networks, and it has manymore node-embedding algorithms than NetworkX.