def calculate(graph): if nx.is_connected(graph): return bool( Utils.approx_to_int( la.det(inv_other.DistanceMatrix.calculate(graph))) != 0) else: return False
def calculate(graph): if nx.is_connected(graph): return Utils.approx_to_int( la.det( inv_other.SignlessLaplacianDistanceMatrix.calculate( graph))) else: return 10**10
def calculate(graph): return Utils.approx_to_int(nx.estrada_index(graph))
def calculate(graph): if nx.is_connected(graph): return Utils.approx_to_int(nx.wiener_index(graph)) else: return 10**10
def calculate(graph): if nx.number_of_nodes(graph) > 1: return Utils.approx_to_int( inv_other.LaplacianSpectrum.calculate(graph)[1]) else: return 0
def calculate(graph): return Utils.approx_to_int( la.det(inv_other.NormalizedLaplacianMatrix.calculate(graph)))
def calculate(graph): return Utils.approx_to_int( la.det(inv_other.SeidelMatrix.calculate(graph)))
def calculate(graph): return Utils.approx_to_int( la.det(inv_other.SignlessLaplacianMatrix.calculate(graph)))
def calculate(graph): return Utils.approx_to_int( la.det(inv_other.AdjacencyMatrix.calculate(graph)))
def calculate(graph): return bool( Utils.approx_to_int( la.det(inv_other.LaplacianMatrix.calculate(graph))) != 0)