import networkx as nx

import matplotlib.pyplot as plt

# define G as the "path graph" w/8 nodes
G=nx.path_graph(8)

# 3 commands needed to draw/plot/save
nx.draw(G)
#plt.savefig("simple_path.png") # save as png
plt.show() # display

# note that networkx handles *really* simple file input 
!rm simple.txt
!touch simple.txt
!echo "0 1" >> simple.txt
!echo "1 2" >> simple.txt
!echo "2 0" >> simple.txt
!cat simple.txt


G = nx.read_edgelist('simple.txt', create_using= nx.DiGraph())
nx.draw(G)
plt.show() # display

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))


# one of the most famous graphs is the 34-node "karate club" graph
G=nx.karate_club_graph()
print("Node Degree")
for v in G:
    print('%s %s' % (v,G.degree(v)))

# here's an example of coloring
pos=nx.spring_layout(G)
nx.draw(G,pos,node_color=range(34),node_size=800,cmap=plt.cm.Blues)
plt.savefig("node_colormap.png") # save as png
plt.show() # display

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))


# let's try this for a 20-node star graph
G=nx.star_graph(20)  
pos=nx.spring_layout(G)
colors=range(20) 
nx.draw(G,pos,node_color='#A0CBE2',edge_color=colors,width=4,edge_cmap=plt.cm.Blues,with_labels=False)
plt.savefig("edge_colormap.png") # save as png
plt.show() # display

for v in G:
    print('%s %s' % (v,G.degree(v)))

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))

# here's an example of networkx syntax for file i/o:
from networkx import *
import sys
G=grid_2d_graph(5,5)  # 5x5 grid



try: # Python 2.6+
    write_adjlist(G,sys.stdout) # write adjacency list to screen
except TypeError: # Python 3.x
    write_adjlist(G,sys.stdout.buffer) # write adjacency list to screen
# write edgelist to grid.edgelist
write_edgelist(G,path="grid.edgelist",delimiter=":") 
# read edgelist from grid.edgelist
H=read_edgelist(path="grid.edgelist",delimiter=":") 


# ok now something cool: an overlay of graph and its degree rank plot
G = nx.gnp_random_graph(100,0.02)

degree_sequence=sorted(nx.degree(G).values(),reverse=True) # degree sequence
#print "Degree sequence", degree_sequence
dmax=max(degree_sequence)

plt.loglog(degree_sequence,'b-',marker='o')
plt.title("Degree rank plot")
plt.ylabel("degree")
plt.xlabel("rank")

# draw graph in inset 
plt.axes([0.45,0.45,0.45,0.45])
Gcc=sorted(nx.connected_component_subgraphs(G), key = len, reverse=True)[0]
pos=nx.spring_layout(Gcc)
plt.axis('off')
nx.draw_networkx_nodes(Gcc,pos,node_size=20)
nx.draw_networkx_edges(Gcc,pos,alpha=0.4)

plt.savefig("degree_rank_plot.png")
plt.show()



#!/usr/bin/env python
"""
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

"""
__author__ = """Aric Hagberg (hagberg@lanl.gov)"""
#    Copyright (C) 2007 by 
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.

try:
    import pyparsing
except ImportError as e:
    raise ImportError(str(e)+". Check http://pyparsing.wikispaces.com/")
    
from networkx import *

url="http://www-personal.umich.edu/~mejn/netdata/football.zip"

try: # Python 3.x
    import urllib.request as urllib
except ImportError: # Python 2.x
    import urllib
import io
import zipfile

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=parse_gml(gml) # parse gml data

print(txt)
# print degree for each team - number of games
for n,d in G.degree_iter():
    print('%s %d' % (n, d))