One potent tool in the analysis of graphs is the adjacency matrix, which has entries aij = 1 if there is an edge from node i to node j,and 0 otherwise. For most networks, the adjacency matrix will be sparse (most of the entries are 0). For networks that are not directed, the matrix will also be symmetric (aij =aji). There are numerous other matrices that can be associated with a network. We will briefly discuss these in the There's more... section of this recipe.
In this recipe, we will generate the adjacency matrix for a network and learn how to get some basic properties of the network from this matrix.
Getting ready
For this recipe, we will need the NetworkX package imported under the name nx, and the NumPy module imported under the name np.
How to do it...
The following steps outline how to generate the adjacency matrix for a network and derive some simple properties of the network...
