I learned about an interesting book today, The Architecture of Open Source Applications, edited by Amy Brown and Greg Wilson. The introduction caught my attention:
Architects look at thousands of buildings during their training, and study critiques of those buildings written by masters. In contrast, most software developers only ever get to know a handful of large programs well—usually programs they wrote themselves—and never study the great programs of history. As a result, they repeat one another’s mistakes rather than building on one another’s successes.
This book’s goal is to change that. In it, the authors of twenty-five open source applications explain how their software is structured, and why. What are each program’s major components? How do they interact? And what did their builders learn during their development? In answering these questions, the contributors to this book provide unique insights into how they think.
If you are a junior developer, and want to learn how your more experienced colleagues think, this book is the place to start. If you are an intermediate or senior developer, and want to see how your peers have solved hard design problems, this book can help you too.
There are chapters on several software packages that I’ve enjoyed using, and chapters on several scientific/data analysis tools, but nothing on the tools I’m using day to day. Still interesting. Let me know if there is a great chapter you come across, since I’m going to be too busy to read the whole thing in the near future.
To take my mind off my meetings, I spent a little time modifying the Spatial Preferred Attachment model from Aiello, Bonato, Cooper, Janssen, and Prałat’s paper A Spatial Web Graph Model with Local Influence Regions so that it changes over time. Continue reading
I’m supposed to be doing the final edits on the journal version of this old paper of mine (jointly with Greg Sorkin and David Gamarnik), but I’ve thought of a way to procrastinate.
Instead of checking the proofs that the length of the shortest path in my weigthed width-2 strip is , I’ll make a quick blog post about verifying this claim numerically (in python with networkx). This also gives me a chance to try out the new networkx, which is currently version 1.0rc1. I think it has changed a bit since we last met.
from pylab import *
from networkx import *
G = Graph()
for u, v in grid_2d_graph(100, 2).edges():
G.add_edge(u, v, weight=rand() < .5)
wt, p = bidirectional_dijkstra(G, (0,0), (99,1))
I haven’t had time to write anything this week because I am up to my neck in this Seven-Samurai-style software engineering project. You know, where a bunch of untrained villagers (that’s me) need to defend themselves against marauding bandits (that’s the Global Burden of Disease 2005 Study), so they have to learn everything about being a samurai (that’s writing an actual application that people other than this one villager can use) as quickly as possible.
I guess this analogy is stretching so thin that you could chop it with Toshirō Mifune’s wooden sword. But, if anyone knows how a mild-mannered theoretical computer scientist can get a web-app built in two weeks, holler. If you prefer to explain in terms of wild-west gunslingers, that is fine.
Here’s my game plan so far: I’m going to make the lightest of light-weight Python/Django apps to hold all the Global Disease Data, and then try to get my epidemologist doctors to interact with it on the command-line via an interactive python session.
The rest of this post is basically a repeat of the Django tutorial, but specialized for building a data server for global population data. As far as interesting theoretical math stuff, hidden somewhere towards the end, I’ll do some interpolation with PyMC’s Gaussian Processes using the exotic (to me) Matérn covariance function. Continue reading
Since 1995, presidential decree has designated the first full week of April to be National Public Health Week in the United States. The American Public Health Association is kicking things off with an online “viral video” campaign. Public health has much more experience trying to stop the spread of viruses, so this campaign has some underdog appeal. It’s also got nice motion graphics, but definitely not my first choice for inspirational music.
(Hey, this soundtrack would be so easy to remix, if only it had an appropriate Creative Commons license. APHA could probably get a bit of notice from folks who wouldn’t otherwise see a public health video by changing the license today and send CC and friends a nice press release. Hint hint.)
This is the final item in my series on Matching Algorithms and Reproductive Health, and it brings the story full circle, returning to the algorithms side of the show. Today I’ll demonstrate how to actually find minimum-weight perfect matchings in Python, and toss in a little story about . Continue reading
MIT faculty makes scholarly articles freely and openly available to the entire world.
Google Summer of Code returns, and suggested Python projects. (A nice way for students to spend the summer, especially during an “economic downturn”).
And for those of you that are looking for NSF grants to apply to: Foundations of Data and Visual Analytics.