powerlaw_cluster_graph.py

import networkx as nx
import matplotlib.pyplot as plt


def generateGraph(nodeCount, edgesPerNode):
    # https://networkx.github.io/documentation/networkx-1.10/reference/generated/networkx.generators.random_graphs.powerlaw_cluster_graph.html
    G = nx.random_graphs.powerlaw_cluster_graph(nodeCount, edgesPerNode, 0.5)
    nodes = [x for x in G.nodes()]
    edges = [x for x in G.edges()]
    return nodes, edges, G


def writeFile(fileName, nodes, edges):
    file = open(fileName, 'w')
    file.writelines('nodes:\n')
    file.writelines('{}\n'.format(node) for node in nodes)
    file.writelines('edges:\n')
    file.writelines('{},{}\n'.format(
        str(edge[0]), str(edge[1])) for edge in edges)
    file.close()


def drawGraph(G):
    nx.draw(G, with_labels=True)
    plt.show()


if __name__ == "__main__":
    nodes, edges, G = generateGraph(100, 3)
    writeFile('data-{nodeLength}-{edgeLength}.txt'.format(
        nodeLength=len(nodes), edgeLength=len(edges)), nodes, edges)
    drawGraph(G)