On 20 July 2013 21:22, <pablobarhamal...@gmail.com> wrote: > Ok, I'm working on a predator/prey simulation, which evolve using genetic > algorithms. At the moment, they use a quite simple feed-forward neural > network, which can change size over time. Each brain "tick" is performed by > the following function (inside the Brain class): > <CODE> > > The function is actually quite fast (~0.040 seconds per 200 calls, using 10 > input, 20 hidden and 3 output neurons), and used to be much slower untill I > fiddled about with it a bit to make it faster. However, it is still somewhat > slow for what I need it. > > My question to you is if you an see any obvious (or not so obvious) way of > making this faster. I've heard about numpy and have been reading about it, > but I really can't see how it could be implemented here.
Currently we're just guessing; if you gave us an appropriate stand-in for "self" (so that we can call the function) we could be helpful much more easily. -- http://mail.python.org/mailman/listinfo/python-list
