def computegtmod(filename, weighted):
fnetwork = 0
#with open(filename+'_ml_network.pickle') as handle:
# fnetwork = pickle.load(handle)
ml_network, layer, node_l, node_c, top, bot, couple, edge_l, edge_c, mu, commu = read_raw_network(
filename, weighted)
status = Status()
status.layer = layer
status.node_l = node_l
status.node_c = node_c
status.top = top
status.bot = bot
status.edge_l = edge_l
status.edge_c = edge_c
status.couple = couple
status.mu = mu
mod = __modularity(commu, status, ml_network)
return mod, commu
def getSeries(filename, weighted):
'''network_name = "networks_low_couple/" + filename.split('/')[-1]
# commented code block
fp=open(network_name,'r')
line=fp.readline()
line=line.rstrip()
n_layer=int(line)
layer={}
node_l={}
l_ID=1
edge_l={}
edge_c={}
# f_el = open(filename+'_edges_list_commod'+str(g), 'w')
for i in range(0,n_layer):
line=fp.readline()
line=line.rstrip()
line=line.split()
layer[l_ID]=set()
##print line
for n in line:
layer[l_ID].add(int(n))
line=fp.readline()
line=int(line.rstrip())
n_edge=line
##print n_edge
edge_l[l_ID]=n_edge
for j in range(0,n_edge):
line=fp.readline()
line=line.rstrip()
line=line.split()
n1=int(line[0])
n2=int(line[1])
if n1 not in node_l:
node_l[n1]=set()
node_l[n1].add(n2)
if n2 not in node_l:
node_l[n2]=set()
node_l[n2].add(n1)
# f_el.write(str(n1-1)+' '+str(n2-1)+'\n')
l_ID+=1
line=fp.readline()
line=line.rstrip()
n_couple=int(line)
##print n_couple
node_c={}
top={}
bot={}
c_ID=1
couple={}
for i in range(0,n_couple):
line=fp.readline()
##print line
line=line.rstrip()
line=line.split()
top[c_ID]=int(line[0])
bot[c_ID]=int(line[1])
couple[c_ID]=layer[top[c_ID]].union(layer[bot[c_ID]])
line=fp.readline()
line=int(line.rstrip())
n_edge=line
##print n_edge
edge_c[c_ID]=n_edge
count_edge = 0
for j in range(0,n_edge):
line=fp.readline()
line=line.rstrip()
line=line.split()
n1=int(line[0])
n2=int(line[1])
if n1 not in node_c:
node_c[n1]=set()
node_c[n1].add(n2)
if n2 not in node_c:
node_c[n2]=set()
node_c[n2].add(n1)
count_edge += 1
# f_el.write(str(n1-1)+' '+str(n2-1)+'\n')
edge_c[c_ID] = count_edge
c_ID=c_ID+1
line=fp.readline()
line=line.rstrip()
##print line
n_comm=int(line)
commu={}
com_ID=1
for i in range(0,n_comm):
line=fp.readline()
line=line.rstrip()
line=line.split()
commu[com_ID]=set()
for n in line:
commu[com_ID].add(int(n))
com_ID+=1
mu=0'''
#with open(filename+'_ml_network.pickle') as handle:
# fnetwork = pickle.load(handle)
ml_network, layer, node_l, node_c, top, bot, couple, edge_l, edge_c, mu, commu = read_raw_network(
filename, weighted)
#ml_network =build_network(layer, node_l, node_c, top, bot, couple, edge_l, edge_c)
#with open(filename+'_ml_network.pickle', 'w') as handle:
# pickle.dump([ml_network, layer, node_l, node_c, top, bot, couple, edge_l, edge_c, mu, commu], handle)
dendogram, mod = louvain(ml_network, layer, node_l, node_c, top, bot,
couple, edge_l, edge_c, mu)
status = Status()
status.layer = layer
status.node_l = node_l
status.node_c = node_c
status.top = top
status.bot = bot
status.edge_l = edge_l
status.edge_c = edge_c
status.couple = couple
status.mu = mu
mod_old = mod
commu = _get_com_wise_nodes(
partition_at_level(dendogram,
len(dendogram) - 1))
#commu =_get_commu_dict(partition_at_level(dendogram, len(dendogram)-1))
mod = __modularity(commu, status, ml_network)
#print "--------- BEF RET ---------"
#print mod_old, mod
#print "----------------"
return mod, dendogram
def louvain(graph, layer, node_l, node_c, top, bot, couple, edge_l, edge_c,
mu):
current_graph = graph.copy()
status = Status()
status.layer = layer
status.node_l = node_l
status.node_c = node_c
status.top = top
status.bot = bot
status.edge_l = edge_l
status.edge_c = edge_c
status.couple = couple
status.mu = mu
status.init(current_graph)
old_status = status.copy()
status_list = list()
level_count = 0
mod = __modularity(_get_commu_dict(status.node2com), status, graph)
#print "Modularity before First Iteration ",mod
__one_level(graph, old_status, current_graph, status, status_list,
level_count)
partition = __renumber(status.node2com)
status_list.append(partition)
current_graph, part, status = induced_graph_multilayer(
partition, current_graph, status)
mod1 = __modularity(_get_com_wise_nodes(part), status, current_graph)
p = _get_com_wise_nodes(
partition_at_level(status_list,
len(status_list) - 1))
new_mod = __modularity(p, old_status, graph)
#print "-> merge mod after level 0 : ", mod1
#print "-> Modularity after level 0: ",new_mod, "\n"
##print("Louvain, partition: ",partition)
#print("Louvain partition: ",part)
A = nx.adjacency_matrix(current_graph)
##print(A.todense())
status.init(current_graph)
while True:
level_count += 1
##print level_count
modif = __one_level(graph, old_status, current_graph, status,
status_list, level_count, 1)
partition = __renumber(status.node2com)
status_list.append(partition)
new_mod = __modularity(
_get_commu_dict(partition_at_level(status_list, level_count)),
old_status, graph)
#print "-> Modularity after level ",level_count,": ",new_mod, "\n"
#new_mod = __modularity(_get_commu_dict(partition), status, current_graph)
#new_mod = __modularity(_get_com_wise_nodes(partition), status, current_graph)
if modif == False:
#if new_mod - mod < __MIN :
break
mod = new_mod
#current_graph = induced_graph(partition, current_graph)
current_graph, part, status = induced_graph_multilayer(
partition, current_graph, status)
#status.init(current_graph)
status.init(current_graph, part)
##print("Louvain, partition: ",partition)
# #print("Louvain, part after: ",part)
# A = nx.adjacency_matrix(current_graph)
##print(A.todense())
return status_list, mod
