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)