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March 7, 2022 15:51
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Plot degree distribution (Freq, CDF, CCDF) from edgelist data
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| import sys | |
| import numpy as np | |
| import networkx as nx | |
| import matplotlib.pyplot as plt | |
| def plot(data,filename,degreetype): | |
| """ Plot Distribution """ | |
| plt.plot(range(len(data)),data,'bo') | |
| plt.yscale('log') | |
| plt.xscale('log') | |
| plt.ylabel('Freq') | |
| plt.xlabel('Degree') | |
| plt.savefig(filename + '_' + degreetype + '_distribution.eps') | |
| plt.clf() | |
| """ Plot CDF """ | |
| s = float(data.sum()) | |
| cdf = data.cumsum(0)/s | |
| plt.plot(range(len(cdf)),cdf,'bo') | |
| plt.xscale('log') | |
| plt.ylim([0,1]) | |
| plt.ylabel('CDF') | |
| plt.xlabel('Degree') | |
| plt.savefig(filename + '_' + degreetype + '_cdf.eps') | |
| plt.clf() | |
| """ Plot CCDF """ | |
| ccdf = 1-cdf | |
| plt.plot(range(len(ccdf)),ccdf,'bo') | |
| plt.xscale('log') | |
| plt.yscale('log') | |
| plt.ylim([0,1]) | |
| plt.ylabel('CCDF') | |
| plt.xlabel('Degree') | |
| plt.savefig(filename + '_' + degreetype + '_ccdf.eps') | |
| plt.clf() | |
| edgelist_file = sys.argv[1] | |
| """ Load graph """ | |
| G = nx.read_edgelist(edgelist_file, nodetype=int, create_using=nx.DiGraph()) | |
| """ To sparse adjacency matrix """ | |
| M = nx.to_scipy_sparse_matrix(G) | |
| indegrees = M.sum(0).A[0] | |
| outdegrees = M.sum(1).T.A[0] | |
| indegree_distribution = np.bincount(indegrees) | |
| outdegree_distribution = np.bincount(outdegrees) | |
| plot(indegree_distribution, edgelist_file, 'indegree') | |
| plot(outdegree_distribution, edgelist_file, 'outdegree') |
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how does this thing work?