Build a directed graph of 1022 categories and 5075 cross-references as defined in the 1879 version of Roget’s Thesaurus contained in the datafile roget_dat.txt. This example is described in Section 1.2 in Knuth’s book (see [1] and [2]).

Note that one of the 5075 cross references is a self loop yet it is included in the graph built here because the standard networkx DiGraph class allows self loops. (cf. 400pungency:400 401 403 405).


[1]Donald E. Knuth, “The Stanford GraphBase: A Platform for Combinatorial Computing”, ACM Press, New York, 1993.


Loaded roget_dat.txt containing 1022 categories.
digraph has 1022 nodes with 5075 edges
21 connected components

from __future__ import print_function

# Authors: Brendt Wohlberg, Aric Hagberg (
# Date: 2005-04-01 07:56:22 -0700 (Fri, 01 Apr 2005)

#    Copyright (C) 2004-2017 by
#    Aric Hagberg <>
#    Dan Schult <>
#    Pieter Swart <>
#    All rights reserved.
#    BSD license.

import gzip
import re
import sys

import matplotlib.pyplot as plt
from networkx import nx

def roget_graph():
    """ Return the thesaurus graph from the roget.dat example in
    the Stanford Graph Base.
    # open file roget_dat.txt.gz (or roget_dat.txt)
    fh ='roget_dat.txt.gz', 'r')

    G = nx.DiGraph()

    for line in fh.readlines():
        line = line.decode()
        if line.startswith("*"):  # skip comments
        if line.startswith(" "):  # this is a continuation line, append
            line = oldline + line
        if line.endswith("\\\n"):  # continuation line, buffer, goto next
            oldline = line.strip("\\\n")

        (headname, tails) = line.split(":")

        # head
        numfind = re.compile("^\d+")  # re to find the number of this word
        head = numfind.findall(headname)[0]  # get the number


        for tail in tails.split():
            if head == tail:
                print("skipping self loop", head, tail, file=sys.stderr)
            G.add_edge(head, tail)

    return G

if __name__ == '__main__':
    G = roget_graph()
    print("Loaded roget_dat.txt containing 1022 categories.")
    print("digraph has %d nodes with %d edges"
          % (nx.number_of_nodes(G), nx.number_of_edges(G)))
    UG = G.to_undirected()
    print(nx.number_connected_components(UG), "connected components")

    options = {
        'node_color': 'black',
        'node_size': 1,
        'line_color': 'grey',
        'linewidths': 0,
        'width': 0.1,
    nx.draw_circular(UG, **options)

Total running time of the script: ( 0 minutes 0.221 seconds)

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