| import networkx as nx |
| import numpy as np |
|
|
|
|
| def print_graph_stats(G): |
| n = G.number_of_nodes() |
| m = G.number_of_edges() |
|
|
| print(f"Number of nodes: {n}") |
| print(f"Number of edges: {m}") |
|
|
| if n == 0: |
| print("Average degree: 0.0") |
| print("Connectivity (weak or strong): False") |
| print("Is connected as undirected graph: False") |
| print("Number of weakly connected components: 0") |
| print("Number of strongly connected components: 0") |
| print("Number of isolated nodes: 0") |
| return |
|
|
| |
| avg_deg = m / n |
| print(f"Average degree: {avg_deg}") |
|
|
| |
| is_weak = nx.is_weakly_connected(G) |
| is_strong = nx.is_strongly_connected(G) |
| print(f"Connectivity (weak or strong): {is_weak or is_strong}") |
|
|
| |
| try: |
| und_connected = nx.is_connected(G.to_undirected(as_view=True)) |
| except Exception: |
| und_connected = False |
| print(f"Is connected as undirected graph: {und_connected}") |
|
|
| print(f"Number of weakly connected components: {nx.number_weakly_connected_components(G)}") |
| print(f"Number of strongly connected components: {nx.number_strongly_connected_components(G)}") |
| print(f"Number of isolated nodes: {len(list(nx.isolates(G)))}") |
|
|
|
|
| def audit_adj(adj: np.ndarray): |
| has_self = np.all(np.diag(adj) > 0) |
| sym = np.allclose(adj, adj.T, atol=1e-8) |
| deg = adj.sum(1) |
| isolated = np.sum(deg==0) |
| return {"n":adj.shape[0], "m":int(adj.sum()), "sym":sym, "self_loops":has_self, |
| "avg_deg":float(deg.mean()), "isolated_nodes":int(isolated)} |
