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For now, my priority is to focus on extensive user-testing cases from real-life experimental spectra, instead of the synthetic ones in first phase of the project. One of the very first experimental spectra I get, is from Mr. Nicolas MinesiMinesi, or Mr. Minou, a Post-doctoral Researcher at Universify of California, L.A. He specializes in laser spectroscopy and also one of my mentors in RADIS.
1. The spectrum
Mr. Minou introduced an absorbance CO spectrum near 2011 cm-1. He stored the data in a MAT (Matlab) file, which is extracted by this script:
The first half of the coding period is almost done, and here I am with the updates! As stated at the end of the last blog, I started the 3rd week by improving the second PR. I performed pretty intensive memory and performance analysis on the functions in fourier.jl, using BenchmarkTools and .mem files to analyze bottlenecks in the program. With my mentors’ help, I removed many allocation and type-stability related issues during that time. I also had some problems with non-idiomatic code, like I could use multiple-dispatch or dot broadcast in functions, some of which I solved, and some are due for refactoring after the mid-evaluation. After finishing the improvements and getting my second PR merged, I planned to work on LightCurves and implement periodograms and other APIs so that users can easily manipulate photon count data. But my mentor suggested I implement file reading and mechanisms to manage the GTIs (Good Time Intervals) obtained from these files.
Working out the GTI mechanisms
I had learned a lot from the previous PR, and one of the things was I should try to implement some of the methods in my way rather than using the python algorithms with an idiomatic Julian code in mind. I started the 4th week with methods for reading GTIs from a FITS file (For those unfamiliar, it is a file format for storing, processing, and transmitting scientific data, especially images). I used the FITSIO.jl package, and experimenting on the terminal led me to manipulate HDUs and their data. One thing I thoroughly thought of was the appropriate data structure of the GTIs. Should I use Intervals from the Intervals.jl package? Or a vector of vector like the python library does? I finally decided to use what I was using in the fourier.jl, an AbstractMatrix of Reals. It was easy to access data from them, and you could use slices to get a list of start and end times. For the operations, I had to convert among matrix, intervals frequently, and vectors as the Intervals.jl provided many ways to manipulate GTIs like union or intersection or getting its complement, i.e., Bad Time Intervals. With some more methods like creating masks and GTIs from conditions and implementing Tests for all of these functions, I was finished with the gti.jl file. A little performance analysis told me that the code was efficient. After some refactoring, like removing code duplication by merging union and intersection in the same function, I was done with the PR. It has some minor changes currently to be made before it gets merged.
It is time to write a blog about my experience in the coding period so far. So here it goes.
The official coding period for GSoC’22 started on the 13th of June. After discussing with mentors I decided that the first task would be to create a base structure of the code for Bexvar. As the method was already implemented by Dr. Johannes Buchner (who also suggested implementing this method in Stingray)and David Bogensberger, we decided to use this implementation as a reference.
In this final week, I fully dedicate myself into user-testing cases. As pointed out by Mr. Erwan Pannier, “Things will definitely change after user feedback so don’t waste too much time before that”. Thus, I must quickly bring up several notebooks for the users - our spectroscopic scientists - to test and provide feedbacks, and from then I can shape my fitting modules closer to the real usages and needs. Firstly, I will talk about several additional updates in this final week of phase 1:
1. Non-LTE support
Now the fitting module supports non-LTE input. The module will automatically switch to non-LTE mode when Tvib is detected inside the input meterials.