Vehicle-Anti-Theft-Face-Rec.../venv/share/doc/networkx-2.5/examples/graph/plot_football.py

47 lines
1.1 KiB
Python

"""
========
Football
========
Load football network in GML format and compute some network statistcs.
Shows how to download GML graph in a zipped file, unpack it, and load
into a NetworkX graph.
Requires Internet connection to download the URL
http://www-personal.umich.edu/~mejn/netdata/football.zip
"""
import urllib.request as urllib
import io
import zipfile
import matplotlib.pyplot as plt
import networkx as nx
url = "http://www-personal.umich.edu/~mejn/netdata/football.zip"
sock = urllib.urlopen(url) # open URL
s = io.BytesIO(sock.read()) # read into BytesIO "file"
sock.close()
zf = zipfile.ZipFile(s) # zipfile object
txt = zf.read("football.txt").decode() # read info file
gml = zf.read("football.gml").decode() # read gml data
# throw away bogus first line with # from mejn files
gml = gml.split("\n")[1:]
G = nx.parse_gml(gml) # parse gml data
print(txt)
# print degree for each team - number of games
for n, d in G.degree():
print(f"{n:20} {d:2}")
options = {
"node_color": "black",
"node_size": 50,
"linewidths": 0,
"width": 0.1,
}
nx.draw(G, **options)
plt.show()