Introduction to the Modeling and Analysis of Complex Systems

15.3. CONSTRUCTING NETWORK MODELS WITH NETWORKX 307}’Jess’: {’Jill’: {}, ’Josh’: {}},’Jill’: {’Jess’: {}, ’Jeff’: {}},’Jack’: {’Jane’: {}},’Jane’: {’Jack’: {}, ’Jeff’: {}}Now its structure is much clearer. g.edge is a dictionary that describes edges in thenetwork in the adjacency list format. Each entry of g.edge is a pair of the node’s nameand a dictionary that contains its neighbors. For example, the first entry says that Jeffis connected to Jane and Jill. Note that the connections are perfectly symmetric; if Jeffis connected to Jane, then the entry for Jane (in the last line) also contains Jeff as herneighbor. Such symmetry is automatically maintained by NetworkX, because this Graphobject is for undirected graphs.Moreover, each neighbor’s name works as a key associated with another dictionaryin which we can store properties of the connection (initially they are all empty, as shownabove). So you can dynamically add or modify any edge property as follows:Code 15.7:>>> g.edge[’Jeff’][’Jane’][’trust’] = 1.0>>> g.edge[’Josh’][’Jess’][’love’] = True>>> g.edge[’Jess’][’Josh’][’love’]True>>> g.edge{’Jeff’: {’Jane’: {’trust’: 1.0}, ’Jill’: {}},’Josh’: {’Jess’: {’love’: True}},’Jess’: {’Jill’: {}, ’Josh’: {’love’: True}},’Jill’: {’Jess’: {}, ’Jeff’: {}},’Jack’: {’Jane’: {}},’Jane’: {’Jack’: {}, ’Jeff’: {’trust’: 1.0}}}Again, the output is reformatted to enhance the readability. Note that the new edge properties(’trust’ between Jeff and Jane; ’love’ between Josh and Jess) are correctlyinserted into the respective dictionaries, always maintaining symmetry between nodes.I just added True ’love’ from Josh to Jess, which has been reciprocated from Jess toJosh! What a beautiful world. This is all because we are using a Graph object.The DiGraph object behaves differently. It is designed to represent directed graphs, so