Algorithms For Dummies

 Exploring the World of Graphs

Graph_A = nx.DiGraph()

Graph_B = nx.DiGraph()

Graph_C = nx.DiGraph()

Nodes = range(1,6)

Edges_OK = [(1,2),(1,3),(2,3),(3,1),(3,2),(3,4),(4,5),

            (4,6),(5,4),(5,6),(6,5),(6,1)]

Edges_dead_end = [(1,2),(1,3),(3,1),(3,2),(3,4),(4,5),

                  (4,6),(5,4),(5,6),(6,5),(6,1)]

Edges_trap = [(1,2),(1,3),(2,3),(3,1),(3,2),(3,4),(4,5),

              (4,6),(5,4),(5,6),(6,5)]

Graph_A.add_nodes_from(Nodes)

Graph_A.add_edges_from(Edges_OK)

Graph_B.add_nodes_from(Nodes)

Graph_B.add_edges_from(Edges_dead_end)

Graph_C.add_nodes_from(Nodes)

Graph_C.add_edges_from(Edges_trap)

This code displays the first network, the good one, as shown in Figure 11-1.

np.random.seed(2)

pos=nx.shell_layout(Graph_A)

nx.draw(Graph_A, pos, arrows=True, with_labels=True)

plt.show()

All nodes connect with each other. This is an example of a strongly connected 

graph, which contains no isolated nodes or single nodes and enclaves that act as 

dead ends. A random surfer can freely run through it and never stop, and any node 

can reach any other node. In the NetworkX representation of a directed graph, 

FIGURE 11-1: 

A strongly 

connected 

network.

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CHAPTER 11