Another optimization request :-)

[andrew cooke]

sorry, that was stupid.  there is no inversion (apart from 1/m), just the
integration.

still, improving the integration would allow larger steps.

andrew



andrew cooke wrote:
>
> 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
>>
>>
>
>
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>
>