def calculate(graph):
if nx.number_of_nodes(graph) < 2:
return 0
elif nx.is_connected(graph):
return Utils.SecondLargestEigen(
inv_other.DistanceMatrix.calculate(graph))
else:
return 10**10
def calculate(graph):
if nx.is_connected(graph):
return Utils.SecondLargestEigen(
inv_other.SignlessLaplacianMatrix.calculate(graph))
else:
return 10**10
def calculate(graph):
if nx.number_of_nodes(graph) > 1:
return Utils.SecondLargestEigen(
inv_other.NormalizedLaplacianMatrix.calculate(graph))
else:
return 0
def calculate(graph):
if nx.number_of_nodes(graph) > 1:
return Utils.SecondLargestEigen(
inv_other.SeidelMatrix.calculate(graph))
else:
return 0