On Sun, 13 Jan 2013 12:05:54 -0800, subhabangalore wrote: > Dear Group, > > I have two questions, if I take a subseries of the matrix as in > eigenvalue here, provided I have one graph of the full form in G, how > may I show it, as if I do the nx.draw(G) it takes only the original > graph.
Is this what you mean? If not, you will have to explain your question better. L = = nx.laplacian(G) E = numpy.linalg.eigvals(L) nx.draw(E) > >>> print numpy.linalg.eigvals(L) > [ 8.00000000e+00 2.22044605e-16 1.00000000e+00 1.00000000e+00 > 1.00000000e+00 1.00000000e+00 1.00000000e+00 1.00000000e+00] > for more than 1000 nodes it is coming too slow on Windows 7 machine with > 3GB RAM. Get a faster machine. Or use fewer nodes. Or be patient and wait. Solving a graph problem with 1000 nodes is a fairly big problem for a desktop PC. It will take time. Calculations don't just happen instantly, the more work you have to do the longer they take. The last alternative is to ask on a specialist numpy list. But I expect they will probably tell you the same thing. -- Steven -- http://mail.python.org/mailman/listinfo/python-list
