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net.py
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net.py
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import igraph
from synthetic.randomwalkers import RandomWalkers
def create_net(nodes, directed):
graph = igraph.Graph(n=nodes, directed=directed)
return Net(graph)
def create_random_net(nodes, edges, directed):
graph = igraph.Graph.Erdos_Renyi(n=nodes, m=edges, directed=directed)
return Net(graph)
def load_net(file_path, directed):
graph = igraph.Graph.Load(file_path)
# force directed / undirected
if graph.is_directed() and not directed:
graph = graph.as_undirected()
if not graph.is_directed() and directed:
graph = graph.as_directed()
graph = graph.simplify()
assert (graph.is_directed() == directed)
return Net(graph)
class Net:
def __init__(self, graph):
self.graph = graph
self.u_random_walkers = RandomWalkers(self, False)
if graph.is_directed():
self.d_random_walkers = RandomWalkers(self, True)
else:
self.d_random_walkers = None
def degree(self, node):
return self.graph.degree(node, mode=igraph.ALL)
def in_degree(self, node):
return self.graph.degree(node, mode=igraph.IN)
def out_degree(self, node):
return self.graph.degree(node, mode=igraph.OUT)
def neighbors(self, node):
return self.graph.neighbors(node, mode='all')
def in_neighbors(self, node):
return self.graph.neighbors(node, mode='in')
def out_neighbors(self, node):
return self.graph.neighbors(node, mode='out')
# custom
def get_feature(self, node, feat):
feat_cleaned = feat.replace("targ_", "").replace("orig_", "")
return self.graph.vs[node].attributes()[feat_cleaned]