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