#Change to work with real Laplancian numRows = 100 graph = SparseGraph(GeneralVertexList(numRows)) p = 0.1 generator = ErdosRenyiGenerator(p) graph = generator.generate(graph) print(graph) AA = graph.normalisedLaplacianSym() p = 0.001 generator.setP(p) graph = generator.generate(graph, requireEmpty=False) AA2 = graph.normalisedLaplacianSym() U = AA2 - AA #print(U) k = 45 lmbdaA, QA = numpy.linalg.eigh(AA) lmbdaA, QA = Util.indEig(lmbdaA, QA, numpy.flipud(numpy.argsort(lmbdaA))) lmbdaAk, QAk = Util.indEig(lmbdaA, QA, numpy.flipud(numpy.argsort(lmbdaA))[0:k])