tau = 1.0
lmbda = 0.1
linearKernel = LinearKernel()
permutationKernel = PermutationGraphKernel(tau, linearKernel)
randomWalkKernel = RandWalkGraphKernel(lmbda)
K1 = numpy.zeros((numGraphs, numGraphs))
K2 = numpy.zeros((numGraphs, numGraphs))
for i in range(0, numGraphs):
print(("i="+str(i)))
for j in range(0, numGraphs):
print(("j="+str(j)))
K1[i, j] = permutationKernel.evaluate(graphs[i], graphs[j])
K2[i, j] = randomWalkKernel.evaluate(graphs[i], graphs[j])
D1 = KernelUtils.computeDistanceMatrix(K1)
D2 = KernelUtils.computeDistanceMatrix(K2)
numPairs = numGraphs/2
windowSize = 3
pairIndices = numpy.array([list(range(numPairs)), list(range(numPairs))]).T
pairIndices[:, 1] = numPairs + pairIndices[:, 1]
error1 = Evaluator.evaluateWindowError(D1, windowSize, pairIndices)
error2 = Evaluator.evaluateWindowError(D2, windowSize, pairIndices)
print(("Error 1: " + str(error1)))
print(("Error 2: " + str(error2)))
