jeffg wrote: > To be honest, this is not my code and I'm new to python. It's part of > the open source project NetworkX, but I'm using this one call > extensively. I'm also not that familiar with the math behind the > physics. I'll read the documents and see if I can figure it > out. :-) Thank you for the links and suggestions. I really need to > get this code performing at peak levels.
the maths is quite simple really, if you know any physics. it imagines that a spring connects each point, and then works out what the total effect of all the springs is. that gives the net "push" on each point. it then goes through and moves each point a small amount in the direction of the push (there's a "max" that makes no sense physically but probably gives better numeric stability). once they have moved, their positions have changed, so everything needs to be calculated again, hence the iteration. terry's suggestion was that, rather than working particle by particle, if you can generalise the code to use matrices then you can use numpy. that would mean more of the calculation is done using C rather than Python, and so would be a big speed-up. that means that you need to rewrite the program so that you don't have the for-loops in Python (for u.. and for v...). instead you need to call numpy to do array calculations. that is going to give you much more speedup than what i recommended (modifying the integration step at the end). to be honest, although this is not hard if you are used to this kind of thing, if the above isn't obvious it is quite a job. you would probably be better looking for a different library. unfortunately i don't know of one (i looked for exactly this a month or two ago and concluded i would have to write my own; i didn't have time so i used a simpler layout). i'm really busy, or i would do this for you, because it's interesting and useful. but the code you have looks "amateur" - it wasn't written by someone who does numerical work for a living. that doesn't mean it's not correct or that the original author was stupid, but it does mean that to make it efficient means looking at the problem in a different way. there are certainly (very good) java libraries that do this. could you use jpython and call out to one of those? if so, that's probably your best approach. andrew -- http://mail.python.org/mailman/listinfo/python-list
