def communityGraph(fName,G,pos=None,ax=None,lbs=None):
#for the name of the graph add .G
# for the name of communities add .C
wFile=os.getcwd()+'/CSV/WalkTrap/'+fName+'.C'
wFile2=os.getcwd()+'/CSV/WalkTrap/'+fName+'.Clabel'
ff=open(wFile2,'w')
fn=wFile
try:
f=open(fn,'r')
except IOError:
print 'Could not open '+fn
return
a=sorted(G.nodes())
C=0
for k,line in enumerate(f):
C=C+1
t1=line.strip(' {}\t\n')
t2=t1.split(',')
cc = pickColor(k).strip()
for ww in t2:
n=a[int(ww)]
ff.write(' '+n+' ')
G.node[n]['color'] = cc
ff.write('\n')
print "Number of communities: "+str(C)
if C<1:
lab=str(C)+' community'
else:
lab=str(C)+' communities'
myDraw(G,s=0,pos=pos,tit=lab,ax=ax,labels=lbs)
print '---------------------'
f.close()
return pos
def communityGraph(fName,w,pos=None,s=1):
#for the name of the graph add .G
# for the name of communities add .C
tit=w.replace('.G','').replace('s','/')
gFile=os.getcwd()+'/CSV/Graphs/'+fName+'/'+w+'.G'
pDir=os.getcwd()+'/PIC/'+fName
wFile=os.getcwd()+'/CSV/WalkTrap/'+fName+'/'+w+'.C'
if (not os.path.exists(gFile)) or (not os.path.exists(wFile)):
print 'Error: '+gFile+' or '+wFile+' not found'
return 101
if (not os.path.exists(pDir)):
os.mkdir(pDir)
print '--------------------'
G=nx.read_graphml(gFile)
fn=wFile
try:
f=open(fn,'r')
except IOError:
print 'Could not open '+fn
return
a=sorted(G.nodes())
#~ b=[str(xx) for xx in range(len(a))]
#~ myDic=list2dic(b,a)
C=0
for k,line in enumerate(f):
C=C+1
t1=line.strip(' {}\t\n')
t2=t1.split(',')
cc = pickColor(k).strip()
for ww in t2:
#~ n=myDic[ww.strip()]
n=a[int(ww)]
#~ G.node[n[0].strip()]['color'] = cc
G.node[n]['color'] = cc
print w
print "Number of communities: "+str(C)
if C<1:
lab=str(C)+' community'
else:
lab=str(C)+' communities'
if pos is None:
myDraw(G,pDir+"/"+w+".png",s)
else:
myDraw(G,pDir+"/"+w+".png",s,pos=pos,tit=tit+'\n'+lab)
print '---------------------'
f.close()
def communityGraph(fName):
#for the name of the graph add .G
# for the name of communities add .C
G=nx.read_graphml("CSV/"+fName+'.G')
a=sorted(G.nodes())
b=[str(xx) for xx in range(len(a))]
myDic=list2dic(b,a)
C=0
with open('CSV/'+fName+'.C','r') as f:
for k,line in enumerate(f):
C=C+1
t1=line.strip(' {}\t\n')
t2=t1.split(',')
cc = pickColor(k).strip()
for w in t2:
n=myDic[w.strip()]
G.node[n[0].strip()]['color'] = cc
print "Number of communities: "+str(C)
myDraw(G,"PIC/C_"+fName+".png")
def csv2gml(fName,eps=.3):
""" this function reads csv file with heading :
test_id , minRTT , .... , server
and then makes edges between clients if their similarities
is above eps and returns the graph """
p = readCol(fName)
lIP = ['a'*9]*len(p)
lS = ['a'*9]*len(p)
minRTT=[0]*len(p)
sim={}
E=[]
axial={}
for i,xx in enumerate(p):
lIP[i] = xx[0].strip()
try:
lS[i] = ipClass(xx[-1]).sub('/24').string().strip()
minRTT[i] = float(xx[1])
except ValueError:
continue
try:
axial[(lS[i],lIP[i])]=axial[(lS[i],lIP[i])]+1
except KeyError:
axial[(lS[i],lIP[i])]=1
ll=len(axial)
to_del=[]
for i in range(ll):
if axial[(lS[i],lIP[i])]<2:
to_del.append(i)
lS=del_indices(lS,to_del)
lIP=del_indices(lIP,to_del)
minRTT=del_indices(minRTT,to_del)
myDic=list2dic(lS,zip(lIP,minRTT))
ll=len(myDic)
print 'Number of servers : '+ str(ll)
if ll<2:
return 0
for i,w in enumerate(myDic.keys()):
occur={}
l=len(myDic[w])
print '\n loop '+str(i+1)+' of '+str(ll)+' :'
print ' '+str(l)+' clients -> '+str(l*(l-1)/2)+' loops'
v=[ww[1] for ww in myDic[w]]
sigma=num.std(v)
if sigma < 1:
continue
for comb in combinations(myDic[w],2):
a=comb[0][0]
b=comb[1][0]
if a==b:
continue
delta=abs(comb[0][1]-comb[1][1])
link=(a,b)
if link in occur.keys():
occur[link]=occur[link]+1
else:
occur[link]=0
if link not in sim.keys():
sim[link]=[math.exp(-delta/sigma)]
elif (link in sim.keys() and occur[link]==0):
sim[link]=sim[link]+[math.exp(-delta/sigma)]
else:
pass # This definitely has to be changed
G=nx.Graph()
for w in sim.keys():
#~ G.add_node(w[0])
#~ G.add_node(w[1])
weight=combSum(sim[w])
if weight > eps:
G.add_edge(w[0],w[1],weight=weight)
if G.size()==0 or G.order()==0:
return 0
G=score(G,1) # Added robustness
if G.size()==0 or G.order()==0:
return 0
if not nx.is_connected(G):
print "Graph is not connected, Largest component is used\n"
G=nx.connected_component_subgraphs(G)[0]
nx.write_graphml(G,"CSV/"+fName+'.G')
myDraw(G,'PIC/Raw_'+fName+'.png')
return G.size()
def formCluster(fName,eps,draw=False):
epsilon=.5
S=4
minRTT=[]
lIP=[]
lS=[]
sim={}
E=[]
city={}
with open('csv/'+fName,'r') as f:
val=csv.reader(f)
i=0
for row in val:
if i==0:
i=1
continue
if test_id_2_ip(row[0]) is None:
continue
lIP.append(test_id_2_ip(row[0]))
lS.append(ipClass(row[-1]).sub('/24').string())
minRTT.append(int(row[1]))
city[test_id_2_ip(row[0])]=row[2]
myDic=list2dic(lS,zip(lIP,minRTT))
for i,w in enumerate(myDic.keys()):
occur={}
l=len(myDic[w])
print '\n loop:'
print l*(l-1)/2
if l>500:
print 'Jumped'
continue
v=[ww[1] for ww in myDic[w]]
sigma=num.std(v)
print sigma
for comb in combinations(myDic[w],2):
a=comb[0][0]
b=comb[1][0]
delta=abs(comb[0][1]-comb[1][1])
link=(a,b)
if link in occur.keys():
occur[link]=occur[link]+1
else:
occur[link]=0
if link not in sim.keys():
sim[link]=[math.exp(-delta/sigma)]
elif (link in sim.keys() and occur[link]==0):
sim[link]=sim[link]+[math.exp(-delta/sigma)]
else:
pass # This definitely has to be changed
G=nx.Graph()
for w in sim.keys():
G.add_node(w[0],labels=city[w[0]])
G.add_node(w[1],labels=city[w[1]])
weight=combSum(sim[w])
if weight > epsilon:
G.add_edge(w[0],w[1],width=weight)
G=s_core(G,S)
if draw:
myDraw(G,'labels')
Gn=nx.connected_components(G)
return Gn
def csv2gml(fName,eps=.1):
""" this function reads csv file with heading :
test_id , minRTT , .... , server
and then makes edges between clients if their similarities
is above eps and returns the graph """
p = readCol(fName)
lIP = ['a'*9]*len(p)
lS = ['a'*9]*len(p)
minRTT=[0]*len(p)
sim={}
E=[]
axial={}
with open('Files/serverMap','r') as f:
st=f.read()
serverMap=eval(st)
uds=0
to_del=[]
for i,xx in enumerate(p):
try:
lIP[i] = ipClass(xx[0].strip()).sub('/24').string().split('/')[0].strip()
#~ lIP[i] = xx[0].strip()
#~ lS[i] = ipClass(xx[-1]).sub('/24').string().strip()
lS[i]=serverMap[xx[-1]][0]
minRTT[i] = float(xx[1])
except ValueError:
to_del.append(i)
continue
except KeyError:
to_del.append(i)
uds=uds+1
continue
try:
axial[lIP[i]]=[lS[i]]+axial[lIP[i]]
except KeyError:
axial[lIP[i]]=[lS[i]]
print 'Unrecognized test (no server info):'+str(uds)
ll=len(p)
for i in range(ll):
try:
if len(set(axial[lIP[i]])) < 2:
to_del.append(i)
except KeyError:
to_del.append(i)
lS=del_indices(lS,to_del)
lIP=del_indices(lIP,to_del)
minRTT=del_indices(minRTT,to_del)
myDic=list2dic(lS,zip(lIP,minRTT))
ll=len(myDic)
print 'Number of servers : '+ str(ll)
if ll<2:
return 0
for i,w in enumerate(myDic.keys()):
print '--------------------------------'
print w
occur={}
l=len(myDic[w])
print 'loop '+str(i+1)+' of '+str(ll)+' :'
print ' '+str(l)+' clients -> '+str(l*(l-1)/2)+' loops'
print '--------------------------------'
print '\n\n'
v=[ww[1] for ww in myDic[w]]
sigma=num.std(v)
if sigma < 1:
continue
for comb in combinations(myDic[w],2):
a=comb[0][0]
b=comb[1][0]
if a==b:
continue
delta=abs(comb[0][1]-comb[1][1])
if a > b :
link=(a,b)
else:
link=(b,a)
#~ if link in occur.keys():
#~ occur[link]=occur[link]+1
#~ else:
#~ occur[link]=0
#~ if link not in sim.keys():
#~ sim[link]=[math.exp(-delta/sigma)]
#~ elif (link in sim.keys() and occur[link]==0):
#~ sim[link]=sim[link]+[math.exp(-delta/sigma)]
#~ else:
#~ pass # This definitely has to be changed
try:
occur[link]=occur[link]+1
except KeyError:
occur[link]=0
try:
if occur[link]==0:
sim[link]=sim[link]+[math.exp(-delta/sigma)]
else:
sim[link][-1]=max(sim[link][-1],math.exp(-delta/sigma))
except KeyError:
sim[link]=[math.exp(-delta/sigma)]
G=nx.Graph()
for w in sim.keys():
weight=combSum(sim[w]) # weighting function 1
#~ if len(sim[w]) < 2: # weighting function 2
#~ weight=0
#~ else:
#~ weight=float(num.mean(sim[w]))
if weight > eps:
G.add_edge(w[0],w[1],weight=weight)
if G.size()==0 or G.order()==0:
return 0
#~ G=score(G,1) # Added robustness
#~ if G.size()==0 or G.order()==0:
#~ print 'SCORE Nullification'
#~ return 0
if not nx.is_connected(G):
print "Graph is not connected, Largest component is used\n"
G=nx.connected_component_subgraphs(G)[0]
nx.write_graphml(G,"CSV/"+fName+'.G')
myDraw(G,'PIC/Raw_'+fName+'.png')
return G.size()
lab=str(C)+' communities'
if pos is None:
myDraw(G,pDir+"/"+w+".png",s)
else:
myDraw(G,pDir+"/"+w+".png",s,pos=pos,tit=tit+'\n'+lab)
print '---------------------'
f.close()
#~ raw_input('=============>')
if __name__=='__main__':
fName='ndt201311'
pD='PIC/'+fName
if os.path.exists(pD):
print 'Remove '+pD+' for PIC/ then rerun'
else:
os.mkdir(pD)
fn=[]
if fn==[]:
for u1,u2,u3 in os.walk('CSV/WalkTrap/'+fName+'/'):
fn=[xx.replace('.w','') for xx in u3 if ('.w' in xx)]
break
for w in fn:
gF='CSV/Graphs/'+fName+'/'+w.replace('/','s')+'.G'
pl.figure()
pl.subplot(121)
G=nx.read_graphml(gF)
pos=myDraw(G)
pl.subplot(122)
communityGraph(fName,w,pos)
raw_input('====================>')
