Notes

The other day I was playing to see how much I could squeeze out of a genetic algorithm written in Python. The code below shows the example I used. The first part implements a simple two loop version of a traditional allele random mutation. The second part is coded using numpy 2D arrays. The code also measures the time spent on both implementations using cProfile. from numpy import * pop_size = 2000 l = 200 z = zeros((pop_size,l)) def mutate () : for i in xrange(pop_size): for j in xrange(l) : if random.random()<0.5 : z[i,j] = random.random() import cProfile cProfile.run('mutate()') def mutate_matrix () : r = random.random(size=(pop_size,l))<0.5 v = random.random(size=(pop_size,l)) k = r*v + logical_not(r)*z cProfile.run('mutate_matrix()') If you run the code listed above you may get something similar to ...

If you are switching between mac and do not use mobile.me, but you want to carry your mail rule’s around you can play a little trick. The file that contains the mail rules is located at ~/Library/Mail/MessageRules.plist You can just manually copy it from one box to another (you may want to make sure that the target machine does not run Mail), or you can create a little cron entry that uses rsync to keep them in sync. ...

I have been looking over eReaders for a while, but I never found one that look quite right and cosy like good’old paper. Yes, Sony has his own eReader and Amazon launched Kindle, but still feel they are too small—not to mention aesthetics criteria. However, Plastic Logic is getting ready to release their take to eReaders based on their plastic electronics technology. Slim, light weight, days of battery life, and the ability to visualize all sorts of document formats (not like the Sony or Amazon ones) are some of the claims about the device. There is a presentation video on the Plastic Logic site, and a life demo on TGDaily—found via Engadget. ...

Have you ever wondered who does your intranet link to? I was sitting the other day in a meeting (yes, I know, breaking news) and I was wondering what would be a fast way to be able to answer the question. The basic sketch I did in my mind was simple: Set up a web crawler to the domain I want to analyze Run the crawling job Get the links collected on the web map Process the links to only keep the site they refer to Remove duplicates Visualize the graph Simple isn’t it? So, what do I need to get it to work? Basically three pieces of software (a web crawler, a graph manipulation library, and a visualization package) and some glue. Going over the things I been playing for the last year I draw three candidates: Nutch, RDFlib, and prefuse. Oh, the glue will be just two Python scripts. ...

Every new semester has its quickoff overhead. Besides trying to get back on track after travelling, and having meeting after meeting, now I am sitting at the inagural act of the Institute for Advanced Computing Applications and Technologies at the University of Illinois at Urbana-Champaign. A list and description of the three kicking off projects of the center is also available. These three themes are: Next-Generation Acceleration Systems for Advanced Science and Engineering Applications Multiscale Simulation in Science and Engineering Synergistic Research on Parallel Programming for Petascale Applications Quite and interesting mix to follow. ...