def __init__(self,
lang,
xmlsize=None,
inputfilename=None,
forcedistrust=False,
threshold=0,
verbose=False):
sax.handler.ContentHandler.__init__(self)
#lang of wikipedia network
self.lang = lang
self.read = False
self.validdisc = False # valid discussion
self.xmlsize = xmlsize
self.inputfilename = inputfilename
self.count = 0
self.last_perc_print = ''
self.threshold = threshold
self.verbose = verbose
#set parse parameter for this language
self.i18n = i18n[self.lang]
#made the comparison case insensitive
self.i18n = (self.i18n[0].lower(), self.i18n[1].lower(),
self.i18n[2].lower())
self.allusers = set()
#this three parameters contains the Network,
#the first as XDiGraph
#the second/third as list of tuple
self.network = Network()
self.edges = []
self.nodes = []
if inputfilename:
assert 'current' in inputfilename
def getNetwork(self):
W = Network()
for user, authors in self.pages:
W.add_node(node(user))
for a, num_edit in authors.iteritems():
# add node
W.add_node(node(a))
#add edges
# add edge from 'a' who have done the edit
# a 'user' who receive the edit
W.add_edge(node(a), node(user), pool({'value': str(num_edit)}))
return W
def main():
m = Network()
#read users
occupation = {
"0": "other",
"1": "academic/educator",
"2": "artist",
"3": "clerical/admin",
"4": "college/grad student",
"5": "customer service",
"6": "doctor/health care",
"7": "executive/managerial",
"8": "farmer",
"9": "homemaker",
"10": "K-12 student",
"11": "lawyer",
"12": "programmer",
"13": "retired",
"14": "sales/marketing",
"15": "scientist",
"16": "self-employed",
"17": "technician/engineer",
"18": "tradesman/craftsman",
"19": "unemployed",
"20": "writer",
}
users = {}
for x in [(int(x[0]), x[0] + ' ' + x[1] + ' ' + x[2] + occupation[x[3]])
for x in
[x.strip().split('::') for x in file('users.dat').readlines()]]:
users[x[0]] = x[1]
#error: the file 'users.dat' is not in the SVN. There is the .tar.gz file but then it would make more sense to have a line to untar, unzip this file at the beginning of this script. REMOVE this comment if/when fixed.
#read ratings
# [(userid, movieid, rating)]
ratings = [
tuple(map(int,
x.strip().split('::')[:-1]))
for x in file('ratings.dat').readlines()
]
#print ratings
#build graph
m = Network()
for u in users:
m.add_node(users[u])
for u in enumerate(users):
print int(100.0 * (u[0] + 1) / len(users)), "%"
u = u[1]
for v in users:
if u < v:
#this can be slow
#list -> dict
# (id,movie,rating) -> [movie] = rating
#user u
ur = {}
for t in filter(lambda x: x[0] is u, ratings):
ur[t[1]] = t[2]
#user v
vr = {}
for t in filter(lambda x: x[0] is v, ratings):
vr[t[1]] = t[2]
#print u,v,len(ur),len(vr)
uvm = [] #common movies
for i in ur:
if i in vr:
uvm.append(i)
if uvm:
#creation of egde
s = 0
for movie in uvm:
s += abs(ur[movie] - vr[movie])
if not s:
value = 1.0 #users u and v completly agree
else:
value = 1.0 * len(uvm) / s # 1 / avg
# s==0 and s==1 is the same
m.add_edge(u, v, {'value': str(value)})
m.add_edge(v, u, {'value': str(value)})
write_dot(m, 'graph.dot')
