Ezra-Mel Pasikatan's blog

Last night I succumbed to a sudden bout of uncharacteristic sentimentalism.  With my internship was drawing to an end, I had a sudden urge to learn Good Riddance (Time of Your Life) by Greenday on guitar at 1 AM.  As I was strummed and sang, my brain automatically translated some of the lyrics into Matlab code.  This is gonna sound lame, but it demonstrates how far Matlab has merged with my psyche.

It's something unpredictable
But in the end it's right
I hope you had the time of your life

Monday this week was just another day at the office.  Writing a research proposal, debugging the program, basically all the normal work activities.  But Tuesday was a lot more interesting.

This week has mostly been about debugging the program.  In its current state, the .m file of my code just for the graphical user interface is just a little over 900 lines long.  That means 900 opportunities for the code to glitch on me.  Most of the glitches were due to my errors:  letting loops run too long or using specialized function for the first time.  I think I must have gotten a good percentage of the error messages in the Matlab dictionary this week.  There's still a few issues  with the code, but it's basically functional as a beta version.

My GUI (Graphical User Interface) has gone through several iterations this week as I slowly get it to work.  This is actually my first time programming a GUI, so my coding progress is less steady than I would like.  Errors popped up a little too frequently for my taste week.

This week consisted of a good amount of debugging and modifying the program.  I finally made the hassle of all the popup menus on the original program optional and created a version of the program that processed the data autonomously.  It's still a little slow though, taking about 18 minutes to go through 150 sets of data, but it's better than the old way of processing the data individually. 

This week was mostly tying up loose ends of the code.  I wrote the measurement placement subroutine and added it to the main program, and tested it using full runs of data.  Those runs are about 200 files each, so they took a while to process. 

This week mostly consisted of figuring out how to write the most difficult part of the code.  The problem sounds relatively straightforward.  Find the flat areas of each time series plot to get base, sample and calibration measurements.  Use MATLAB algorithms to find these more consistently and faster than a human. 

Because of the Finals schedule at Oregon State University, two weeks worth of work was rolled into one.