This week felt like a crash course in Interactive Data Language. I spent the majority of this week staring at IDL code, trying to learn it and make sense of it. Especially during the beginning of the week, I was having a lot of trouble with someone else’s programs. I want to modify it to read in Swift XRT windowed timing mode data and process them for our needs. However, even before I began changing the code, I had to deal with several errors. Thankfully, most of the errors disappeared on their own, and most of the rest I was able to fix. We’re still working on a few issues with IDL we have yet to figure out.

From the process of coding and debugging, I have not only learned a bit of IDL, I also better understand how the programs work and what we’re trying to do to the data.

One program I’m working on takes the one-dimensional wt spatial image, rotates it so that it’s parallel to the x-axis, creates and histogram profile of the image (which resembles a Gaussian near the peak), determines the peak, determines a width radius, discards the background, and saves the source events. I’ve gotten up to the point where it can plot the profile, and now I’m working on how to determine what’s defined as background and where the source begins and ends.

Another program takes wt data, creates a light curve, performs a fast Fourier transform, and displays a plot of power versus frequency. If I can get this one to work the way I want it to, I’m going to be looking for frequencies with significant spikes in the power. Right now I’m getting a memory error when I try to run the program at the best time resolution, which I need to use to maximize the frequency range I’m searching.

I’ve also been picking up bits of information about related topics, such as Chandra’s specs (I’m modifying code written for Chandra and other observatories) and magnetars. I hope to read more when I get back from Florida.