def input_type_fun(input_type):
if input_type==1:
C = nx.read_gml(filelist[file_num])
elif input_type==2:
C = nx.Graph(formal_edgelist(base +'/benchmark_LFR_OC_UU/network.dat'))
# get true.dat
f = file(base +'/benchmark_LFR_OC_UU/community.dat', 'r')
fw = file(base +'/evaluations/mutual3/true.dat','w+')
d={}
for line in f:
kx = line.strip().split('\t')
kv = []
if ' ' in kx[1]:
kc = kx[1].strip().split(' ')
kv.append(int(kx[0]))
for x in kc:
kv.append(int(x))
else:
kv =[int(kx[0]), int(kx[1])]
for kk in kv[1:]:
if d.get(kk):
d[kk].append(kv[0])
else:
d[kk]=[kv[0]]
ground_truth = []
for x in d:
ground_truth.append(d[x])
print "lens of ground_truth: ", len(ground_truth)
print "ground_truth is:", ground_truth
for line in ground_truth:
content = " ".join([str(x) for x in line])
fw.write(content)
fw.write('\n')
f.close()
fw.close()
elif input_type==3:
from inputs.friendster_dataset.friendster_graph import get_friendster_graph
# C = nx.Graph()
C = get_friendster_graph()
print len(C)
return C
from random import random
from common.transform import split_list
from multiprocessing import Process, Pool
from inputs.formal_edgelist import *
# from SeedDrivenDete import *
from socket import gethostname
hn = gethostname()
exec ("from config.%s import *" % hn)
if input_type == 1:
C = nx.read_gml(filelist[file_num])
elif input_type == 2:
C = nx.Graph(formal_edgelist(base + "/benchmark_LFR_OC_UU/network.dat"))
elif input_type == 3:
from inputs.friendster_dataset.friendster_graph import get_friendster_graph
C = get_friendster_graph()
# print "nodes_______",len(C.nodes())
# print C.edges()
# print len(C.edges())
# exit()
len_C = len(C)
nodes_C = C.nodes()
degree_dict = C.degree()
betweenness_dict = nx.betweenness_centrality(C)
__author__ = 'nourl'
import networkx as nx
from inputs.formal_edgelist import *
from sys import exit
from copy import deepcopy
C = nx.DiGraph(formal_edgelist('./benchmark_directed_networks/network.dat'))
print C.in_edges(2)
print C.out_edges(2)
eg = nx.DiGraph()
outedges = C.out_edges(2)
out_edges_final = deepcopy(outedges)
a = len(outedges)
print a
for x in outedges:
out_two = C.out_edges(x[1])
out_edges_final += out_two
print len(out_edges_final), "_______", out_edges_final
out_edges_weighted = []
for x in out_edges_final:
out_edges_weighted.append((x[0], x[1], 1))
eg.add_weighted_edges_from(out_edges_weighted)
egnodes = eg.nodes()
nw = {}
for x in egnodes:
weight = eg.degree(x, weight=True) * nx.closeness_centrality(C, x)
nw[x] = weight
#print "node_weighted: ",nw
__author__ = 'nourl'
import networkx as nx
from inputs.formal_edgelist import *
from sys import exit
from copy import deepcopy
C = nx.DiGraph(formal_edgelist('./benchmark_directed_networks/network.dat'))
print C.in_edges(2)
print C.out_edges(2)
eg = nx.DiGraph()
outedges = C.out_edges(2)
out_edges_final = deepcopy(outedges)
a = len(outedges)
print a
for x in outedges:
out_two = C.out_edges(x[1])
out_edges_final += out_two
print len(out_edges_final),"_______",out_edges_final
out_edges_weighted = []
for x in out_edges_final:
out_edges_weighted.append((x[0],x[1],1))
eg.add_weighted_edges_from(out_edges_weighted)
egnodes=eg.nodes()
nw = {}
for x in egnodes:
weight = eg.degree(x,weight=True) * nx.closeness_centrality(C,x)
nw[x] = weight
#print "node_weighted: ",nw
import networkx as nx
import pickle
from random import random
from common.transform import split_list
from multiprocessing import Process, Pool
from inputs.formal_edgelist import *
#from SeedDrivenDete import *
from socket import gethostname
hn = gethostname()
exec("from config.%s import *" % hn)
if input_type == 1:
C = nx.read_gml(filelist[file_num])
elif input_type == 2:
C = nx.Graph(formal_edgelist(base + '/benchmark_LFR_OC_UU/network.dat'))
elif input_type == 3:
from inputs.friendster_dataset.friendster_graph import get_friendster_graph
C = get_friendster_graph()
#print "nodes_______",len(C.nodes())
#print C.edges()
#print len(C.edges())
#exit()
len_C = len(C)
nodes_C = C.nodes()
degree_dict = C.degree()
betweenness_dict = nx.betweenness_centrality(C)
len_max = len_C
__author__ = 'nourl'
from common.transform import *
from PyCommDete import *
from networkx import nx
from inputs.formal_edgelist import *
from multiprocessing import Pool
from sys import exit
#C = nx.read_gml(filelist[1])
C = nx.Graph(formal_edgelist('./benchmarks/network.dat'))
print "length:", len(C)
betw_ori = nx.betweenness_centrality(C)
degr_ori = C.degree()
nodes = C.nodes()
betw_ori = sorted(betw_ori.iteritems(), key=lambda x: x[1], reverse=True)
average = sum(x[1] for x in betw_ori) / len(betw_ori)
betw = [x for x in betw_ori if x[1] >= 0.2 * average]
betw_ex_nei = [x[0] for x in betw]
bitmap = [0] * len(betw_ori)
print "len of betw_ex_nei:", len(betw_ex_nei)
for x in betw_ex_nei:
bitmap[x - 1] = x
recover = []
for x in betw_ex_nei:
if bitmap[x - 1] > 0:
recover.append(x)
nei = C.neighbors(x)
__author__ = 'nourl'
from common.transform import *
from PyCommDete import *
from networkx import nx
from inputs.formal_edgelist import *
from multiprocessing import Pool
from sys import exit
#C = nx.read_gml(filelist[1])
C = nx.Graph(formal_edgelist('./benchmarks/network.dat'))
print "length:",len(C)
betw_ori = nx.betweenness_centrality(C)
degr_ori = C.degree()
nodes = C.nodes()
betw_ori = sorted(betw_ori.iteritems(), key=lambda x:x[1],reverse=True)
average = sum(x[1] for x in betw_ori)/len(betw_ori)
betw=[x for x in betw_ori if x[1]>=0.2*average]
betw_ex_nei=[x[0] for x in betw]
bitmap = [0]*len(betw_ori)
print "len of betw_ex_nei:",len(betw_ex_nei)
for x in betw_ex_nei:
bitmap[x-1]=x
recover=[]
for x in betw_ex_nei:
if bitmap[x-1] >0:
recover.append(x)
nei = C.neighbors(x)
