The purpose of this exercise is to produce aesthetically pleasing mission long movies of AIA images. The results here are not a measuremet of the degredation of the instuments because solar variability is not taken into account.

The sun_intensity module the brightness of AIA images in order to normalize them to the standard brightness from the beginning of the mission. The 304 AA images from AIA have been the most greatly affected by changes in brightness, decreasing to less than a twelfth of their original brightness at the beginning of the mission.

The sun_intensity.py module contains all the code necessary for collecting and processing the original data, however this is rather computationally expensive and will take some time. That code is here mostly to show how the values are obtained. The best way to get the normalization values is to use the get_dim_factor function in the sun_intensity.py module. I recommend cloning this repository and using imp to import the module into your program.

import imp
sun_intensity = imp.load_source('sun_intensity', '/path/to/sun_intensity.py')

Use the get_dim_factor function to get the brightness factor for a given day. This value is the what the image data is multiplied by to produce an image that is the same brightness as images from the start of the mission.

from datetime import datetime
wavelength = '304'
date = datetime(2013, 5, 19)
dim_factor = sun_intensity.get_dim_factor(date, wavelength)

All the data is stored in the CSV and JSON files aia_rescaling_data.csv/.json. If you want to implement the rescaling in a program other than python, accessing the dim factors from these files is the simplest way to do it.

The mov_img module contains functions for producing AIA images using this rescaling. It produces the same images that appear on the sdowww.lmsal.com website.

It can also produce movies of using a sequence of AIA images.