And Then There Were Plots!

 

These plots are reproduced from Boerner et al. (2012), which utilized initial calibrations of AIA.  I have now developed enough of the response module to analyse updated instrumental properties to get my own calibrations using AIA instrument outfiles from SSW.

Filter Calibration

The transmittance is a ratio of the signal received through the instrument filters.  The values match the lowest lines modelled in Figure 2 of the paper.

 Mirror Calibration

 

This shows the reflectance of the mirrors per wavelength, and it is exactly like Figure 5 in the paper. Huzzah!

CCD Calibration  

Updated: Here the quantum efficiency of the CCD is shown per wavelength, and now it looks like Figure 6 after loading in the UV channels.

Effective Area Functions

Each effective area function displays the efficiency of the optics around the center wavelength of each instrument channel. It is calculated using the instrument calibration properties shown in the other plots.
Updated: Since re-factoring my code, I now get the shapes expected from the paper. These show the calculated effective area in blue and the effective area loaded in from the .genx file dashed in red.


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GSoC AIA Response Functions

 

Project Details:

 

First:  A bit of a delay...

The past few weeks have been quite busy, yet rewarding. The culmination of finals week, graduation, family visiting the West coast for the first time, and finishing my senior research by doing some final remote observations have been taking up more time than anticipated. I'm sad to say that all of this stunted my progress in the GSoC project.

Then:  Back to Work!

So, in hopes to catch up, this last week I've worked with a technician on UW campus to get SSW working. Several days later, we finally just root installed ftp to get it to download. Now, I have access to an idl version of what I'm trying to redo! This has helped already to see what each piece of the code outputs.

Code:

First, I read in the idl .genx files from ssw with python.  My mentor Will sent me documentation on how to do this with scipy.io. I need some properties in these files to make the instrument response function. I was warned that this would make numpy.recarray, and have found this to be a challenging object that works with fields...? It took me a few days to figure out just how nested these objects can be!

My first function I completed was utilizing the information from the .genx files and putting them into pandas dataframes. I used each channel as a key in my next function, which is to load each channel individually.

The past few days I have been working on implementing the response function with these properties. So far, I'm having issues loading in the parameters to calculate an effective area. Mostly, it's been getting past multiplying floats and arrays. My first attempt as this has been to use numpy.ones to make everything the same size, but then the division throws errors. I am still working on it!

Goals: 

1. I made a pull request in Sunpy to make it easier for the developing team to see my work. My goal for this next week especially is to make the habit of committing code to github as I go, rather than in a big bundle like I did for this past commit. It will help to show my gradual progress, and it will help my mentors to guide the work as well.  
2. I plan to do another post this week to make up for missing one last week. It will include the pull requests that I have been working through for the past week. 
3.  Get some plots of the instrument response functions asap for midterm evaluation!!
4. Be ready and on time for the developers meeting on Wednesday, 9 am my time!!!

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