why are you dong this point by point? surely you can express the physics as a set of equations and invert the matrix? wouldn't that be a lot faster? you'd replace the iteration over all combinations of points with a faster matrix inversion.
see for example http://www.medwelljournals.com/fulltext/ajit/2006/324-338.pdf page 331 onwards. there's a very nice into to the verlet integration mentioned here - http://teknikus.dk/tj/gdc2001.htm andrew jeffg wrote: > If anyone wants to take this on... I would really really like to have > the spring_layout modified to support multi-threading if at all > possible. > My test data is 20,000, which makes this process 20,000 x 20,000 or > 400,000,000 (400 million) calculations. This is taking somewhere > between 2-3 hours an iteration. > I plan to plot out over 1,000,000 data points or more, which would put > this at 1,000,000,000,000 (1 trillion) calculations. Any help in > making this more efficient would be much appreciated. > > def spring_layout(G, iterations=50, dim=2, node_pos=None, > verbose=False): > """Spring force model layout""" > if node_pos==None : # set the initial positions randomly in 1x1 > box > vpos=random_layout(G, dim=dim) > else: > vpos=node_pos > if iterations==0: > return vpos > if G.order()==0: > k=1.0 > else: > k=N.sqrt(1.0/G.order()) # optimal distance between nodes > disp={} # displacements > > # initial "temperature" (about .1 of domain area) > # this is the largest step allowed in the dynamics > # linearly step down by dt on each iteration so > # on last iteration it is size dt. > t=0.1 > dt=0.1/float(iterations+1) > for i in range(0,iterations): > for v in G: > if verbose==True: > print("Interation: " + str(i + 1) + ", Calculating: " > + str(v.encode('iso-8859-15', "replace"))) > disp[v]=N.zeros(dim) > for u in G: > delta=vpos[v]-vpos[u] > dn=max(sqrt(N.dot(delta,delta)),0.01) > # repulsive force between all > deltaf=delta*k**2/dn**2 > disp[v]=disp[v]+deltaf > # attractive force between neighbors > if G.has_edge(v,u): > deltaf=-delta*dn**2/(k*dn) > disp[v]=disp[v]+deltaf > > # update positions > for v in G: > l=max(sqrt(N.dot(disp[v],disp[v])),0.01) > vpos[v]=vpos[v]+ disp[v]*t/l > t-=dt > return vpos > -- > http://mail.python.org/mailman/listinfo/python-list > > -- http://mail.python.org/mailman/listinfo/python-list
