• The Stanford library (i.e. SNAP) may solve your problem in large scale if you're gonna get involved with graphs omnidirectionally.
• Part of code in which contains your desire paste as follows,

Env = TEnv(argc, argv, TNotify::StdNotify);

Env.PrepArgs(TStr::Fmt("Graph generators. build: %s, %s. Time: %s", __TIME__, __DATE__, TExeTm::GetCurTm()));

TExeTm ExeTm;

Try

const TStr OutFNm = Env.GetIfArgPrefixStr("-o:", "output.txt", "Output graph filename");

const TStr Plot = Env.GetIfArgPrefixStr("-g:", "e", "Which generator to use:"

"\n\tf: Complete graph. Required parameters: n (number of nodes)"

"\n\ts: Star graph. Required parameters: n (number of nodes)"

"\n\t2: 2D Grid. Required parameters: n (number of rows), m (number of columns)"

"\n\te: Erdos-Renyi (G_nm). Required parameters: n (number of nodes), m (number of edges)"

"\n\tk: Random k-regular graph. Required parameters: n (number of nodes), k (degree of every node)"

"\n\tb: Albert-Barabasi Preferential Attachment. Required parameters: n (number of nodes), k (edges created by each new node)"

"\n\tp: Random Power-Law graph. Required parameters: n (number of nodes), p (power-law degree exponent)"

"\n\tc: Copying model by Kleinberg et al. Required parameters: n (number of nodes), p (copying probability Beta)"

"\n\tw: Small-world model. Required parameters: n (number of nodes), k (each node is connected to k nearest neighbors in ring topology), p (rewiring probability)\n"

);

• Also, it's necessary to install SNAP; it can be reached via this link: https://snap.stanford.edu/snap/download.html
• To analyse this generated graph you have a lot of classes in this library that you can find relevant instruction through separated packages on it.

Thank you Kamran Hayati

To get the adjacency matrix u can use one of these functions :

W = get.adjacency(g,sparse=FALSE) or

W = as_adjacency_matrix(net, attr="weight") 'weight' is the name of the weight attribute in your edges file