Today I wrote code in C++ to see if it performed differently then what I was doing in matlab. I actually took more time to compute. I believe this is because it not only has to go through the large arrays that are getting imputed, but perform the marginalization as well before I can get data out. I ended up having to just modify my arrays in excel to add brackets and commas and then copy and paste them directly into the code since I could not figure out how to read a vector let alone a two dimensional array into C++ code.
After marginalizing to get a least squares for both time and distance modulus, they were both disparate from the published data and what looks like a good fit. So I have the code, and it computes, but it needs work still.
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It's going to be more important for you to compile the K-giant target list before the next Keck run, so after you do the photometry exercise you should turn your attention to the targets. After that is squared away, you can go back to the isochrone fitting.
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