def test(): G = NX.DiGraph() edges = [(1,2), (1,3), (3,1), (3,2), (3,5), (4,5), (4,6), (5,4), (5,6), (6,4)] G.add_edges_from(edges) M = page_rank.google_matrix(G, alpha=0.9) e, ev = numpy.linalg.eig(M.T) p = numpy.array(ev[:,0] / ev[:,0].sum())[:,0] print "exact ", p pr = page_rank.page_rank(G,alpha=0.9,tol=1.0e-8) print "networkx", pr.values() np = page_rank.page_rank_numpy(G,alpha=0.9) print "numpy ", np try: ns = page_rank.page_rank_scipy(G,alpha=0.9) print "scipy ", ns except Error: print "scipy not working"
def test(): G = NX.DiGraph() edges = [(1, 2), (1, 3), (3, 1), (3, 2), (3, 5), (4, 5), (4, 6), (5, 4), (5, 6), (6, 4)] G.add_edges_from(edges) M = page_rank.google_matrix(G, alpha=0.9) e, ev = numpy.linalg.eig(M.T) p = numpy.array(ev[:, 0] / ev[:, 0].sum())[:, 0] print "exact ", p pr = page_rank.page_rank(G, alpha=0.9, tol=1.0e-8) print "networkx", pr.values() np = page_rank.page_rank_numpy(G, alpha=0.9) print "numpy ", np try: ns = page_rank.page_rank_scipy(G, alpha=0.9) print "scipy ", ns except Error: print "scipy not working"
print "Finished reading the dataset --> Number of nodes of dataset = %s" % len(G.nodes()) #print G.edges() print "Do you want to run numpy.linalg.eig? (y/n) [It might be very heavy]" answer=sys.stdin.readline()[:-1] if answer == "y": import numpy M=NX_future_page_rank.google_matrix(G,alpha=0.9) e,ev=numpy.linalg.eig(M.T) p=numpy.array(ev[:,0]/ev[:,0].sum())[:,0] print "exact ", p print "Do you want to run page_rank? (y/n) [It might be very heavy]" answer=sys.stdin.readline()[:-1] if answer == "y": pr = NX_future_page_rank.page_rank(G,alpha=0.9,tol=1.0e-8) print "networkx", pr.values() print "Do you want to run page_rank numpy? (y/n) [It might be very heavy]" answer=sys.stdin.readline()[:-1] if answer == "y": np=NX_future_page_rank.page_rank_numpy(G,alpha=0.9) print "numpy ", np print "Do you want to run page_rank scipy? (y/n) [It might be very heavy]" answer=sys.stdin.readline()[:-1] if answer == "y": ns=NX_future_page_rank.page_rank_scipy(G,alpha=0.9) print "scipy ", ns
G.nodes()) #print G.edges() print "Do you want to run numpy.linalg.eig? (y/n) [It might be very heavy]" answer = sys.stdin.readline()[:-1] if answer == "y": import numpy M = NX_future_page_rank.google_matrix(G, alpha=0.9) e, ev = numpy.linalg.eig(M.T) p = numpy.array(ev[:, 0] / ev[:, 0].sum())[:, 0] print "exact ", p print "Do you want to run page_rank? (y/n) [It might be very heavy]" answer = sys.stdin.readline()[:-1] if answer == "y": pr = NX_future_page_rank.page_rank(G, alpha=0.9, tol=1.0e-8) print "networkx", pr.values() print "Do you want to run page_rank numpy? (y/n) [It might be very heavy]" answer = sys.stdin.readline()[:-1] if answer == "y": np = NX_future_page_rank.page_rank_numpy(G, alpha=0.9) print "numpy ", np print "Do you want to run page_rank scipy? (y/n) [It might be very heavy]" answer = sys.stdin.readline()[:-1] if answer == "y": ns = NX_future_page_rank.page_rank_scipy(G, alpha=0.9) print "scipy ", ns
def scipyPR(G): try: ns = page_rank.page_rank_scipy(G,alpha=0.9) return ns except "bad scipy": print "scipy not working"
def scipyPR(G): try: ns = page_rank.page_rank_scipy(G, alpha=0.9) return ns except "bad scipy": print "scipy not working"