Various current status

OpenOpt: I was able to get OpenOpt to work. It can produce the expected results for the optimal solution for a problem where I already knew the answer. But OpenOpt has a limitation. The default solver does not produce a "sensitivity analysis" and the developer does not plan to add one. The optional solver may have one, but I would have to focus my energy in a different forum to find out. Since I have limits on my time, I think I should focus on a Linear Programming tool that is designed to what I want to accomplish. Hence I will move my focus in Open Source linear programming tools to GLPK.

Home Project: I live in an area of Southern California where it gets hot. My house has various hot spots. For some time I have been wanting to address these hot spots but I did not want to do so with guess work. Also for each fix, I wanted to know how much of an improvement each fix provided so I could determine some kind of return on investment. I found a solution. The open source program OWFS can read 1-wire network temperature sensors and log the data. I just finished configuring the OWFS with the hardware. I now have three separate sensors that report each sensor's temperature. When I am finished with configuring OWFS for my needs I will start a project where I will have one sensor in my garage (which faces west and gets very hot), one sensor in the part of the house above the garage, and one outside. More to come as I configure OWFS prepare for this project.

OWFS: Be sure to check out the examples section, especially the garden
Hobby Boards: 1-Wire USB Adaptor, Adaptor Cable RJ45 to RJ11, Temperature Sensor


Podcast of the week:
Normally the podcast "Bloomberg on the Economy" does not rank as one of my favorites. Often the host acts like a alumi insider by dropping names as if we all know who the players are. But once in a while he does have an interesting guest. This time the guest was Gillian Tett, an editor of the Financial Times. She was promoting her book "Fool's Gold: How the Bold Dream of a Small Tribe at J.P. Morgan Was Corrupted by Wall Street Greed and Unleashed a Catastrophe.''. As per the podcast she mentioned how the original group in J.P. Morgan modeled the credit derivatives. The part that was interesting was the original model revealed the problem we see today. So the original team took steps to prevent problems. When others in the industry learned of the models they learned how to implement the same investments make the money but did not implement the safeguards of the original team.

This is following a theme I have been learning lately. A good model is only useful in the long run when you understand it's limitations and flaws, then take steps/implement processes to address the limits and/or flaws. Hence the need for "sensitivity analysis" for models that support them and the need to examine models under great to terrible conditions.

Bloomberg On the Economy: Search for "Tett Discusses `Fools Gold,' Her Book About J.P.Morgan" on the page and download the mp3 file.