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## iof-tools / networkxMiCe / networkx-master / examples / basic / plot_properties.py @ 5cef0f13

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 1 ```#!/usr/bin/env python ``` ```""" ``` ```========== ``` ```Properties ``` ```========== ``` ``` ``` ```Compute some network properties for the lollipop graph. ``` ```""" ``` ```# Copyright (C) 2004-2019 by ``` ```# Aric Hagberg ``` ```# Dan Schult ``` ```# Pieter Swart ``` ```# All rights reserved. ``` ```# BSD license. ``` ```import matplotlib.pyplot as plt ``` ```from networkx import nx ``` ```G = nx.lollipop_graph(4, 6) ``` ```pathlengths = [] ``` ```print("source vertex {target:length, }") ``` ```for v in G.nodes(): ``` ``` spl = dict(nx.single_source_shortest_path_length(G, v)) ``` ``` print('{} {} '.format(v, spl)) ``` ``` for p in spl: ``` ``` pathlengths.append(spl[p]) ``` ```print('') ``` ```print("average shortest path length %s" % (sum(pathlengths) / len(pathlengths))) ``` ```# histogram of path lengths ``` ```dist = {} ``` ```for p in pathlengths: ``` ``` if p in dist: ``` ``` dist[p] += 1 ``` ``` else: ``` ``` dist[p] = 1 ``` ```print('') ``` ```print("length #paths") ``` ```verts = dist.keys() ``` ```for d in sorted(verts): ``` ``` print('%s %d' % (d, dist[d])) ``` ```print("radius: %d" % nx.radius(G)) ``` ```print("diameter: %d" % nx.diameter(G)) ``` ```print("eccentricity: %s" % nx.eccentricity(G)) ``` ```print("center: %s" % nx.center(G)) ``` ```print("periphery: %s" % nx.periphery(G)) ``` ```print("density: %s" % nx.density(G)) ``` ```nx.draw(G, with_labels=True) ``` ```plt.show() ```