def gen_group_graph(self):
group_graph = nx.Graph()
seed_groups = set()
groups_dic = {}
for group in self.groups:
group_type = self.get_group_type(self.groups[group])
if group_type == 'Seed':
seed_groups.add(group)
groups_dic[group] = Node(group, group_type)
for group in seed_groups:
groups_dic[group].init_rank = 1 / len(seed_groups)
valid_pairs = {}
for n1 in self.graph.nodes:
neighbors = self.graph.neighbors(n1)
for n2 in neighbors:
for g1 in n1.groups:
for g2 in n2.groups:
valid_pairs[(g1, g2)] = True
pairs = itertools.combinations(self.groups.keys(), 2)
pairs = sorted([(f, t) if f < t else (t, f) for f, t in pairs],
key=lambda pair: str(pair))
for source_group, target_group in pairs:
if (source_group, target_group) not in valid_pairs:
continue
removed = set()
weight = 0
source_nodes = self.groups[source_group]
target_nodes = self.groups[target_group]
for source_node in source_nodes:
if source_node in removed:
continue
for target_node in target_nodes:
if source_node in removed:
break
if target_node in removed:
continue
if not self.graph.has_edge(source_node, target_node):
continue
# set number of common neighbors as the weight of the edge (trustworthy of connection)
n1 = self.graph.neighbors(source_node)
n2 = self.graph.neighbors(target_node)
edge_weight = len(set(list(n1)) & set(list(n2)))
if not edge_weight:
continue
weight += edge_weight
removed.add(source_node)
removed.add(target_node)
if weight > 0:
num = len(source_nodes) + len(target_nodes)
group_graph.add_edge(groups_dic[source_group],
groups_dic[target_group],
weight=weight / num)
return group_graph
def gen_group_graph(self):
group_graph = nx.Graph()
seed_groups = set()
groups_dic = {}
for group in self.groups:
group_type = self.get_group_type(self.groups[group])
if group_type == 'Seed':
seed_groups.add(group)
groups_dic[group] = Node(group, group_type)
for group in seed_groups:
groups_dic[group].init_rank = 1 / len(seed_groups)
pairs = itertools.combinations(self.groups.keys(), 2)
pairs = sorted([(f, t) if f < t else (t, f) for f, t in pairs],
key=lambda pair: str(pair))
for source_group, target_group in pairs:
removed = set()
weight = 0
source_nodes = self.groups[source_group]
target_nodes = self.groups[target_group]
if self.min_group_req > 1:
source_nodes = filter(
lambda n: len(n.groups) >= self.min_group_req,
source_nodes)
target_nodes = filter(
lambda n: len(n.groups) >= self.min_group_req,
target_nodes)
for source_node in source_nodes:
if source_node in removed:
continue
for target_node in target_nodes:
if source_node in removed:
break
if target_node in removed:
continue
if not self.graph.has_edge(source_node, target_node):
continue
removed.add(source_node)
removed.add(target_node)
weight += 1
if weight > 0:
num = len(source_nodes) + len(target_nodes)
group_graph.add_edge(groups_dic[source_group],
groups_dic[target_group],
weight=1.0 * weight / num)
return group_graph