Blog 1: Rethinking Coalignment from Ground-up

The Very Essence of Coalignment

At its core, coalignment is all about making sure our solar images match up as best they can. It uses a few different techniques, like template matching and solar rotation correction, to get this done. This is really important when we’re trying to accurately track and study what’s happening on a part of sun over time. We re-thought the entire process of what our new API be providing to the users as well as its structure.

Naive Refactor

This was one of the idea that was very naive version, but focused entierly for the user’s comfort in applying the coalignment methods.

The Basic Structure we finally agreed Upon

Internal Sturcture

We agreed to have this as the very basic structure which we would be working/developing upwards. The following example demonstrates the way it would work.

aia_map1 =
aia_map2 =
### Creating a template from aia_map1
bottom_left = SkyCoord(600 * u.arcsec, -500 * u.arcsec, frame=aia_map1.coordinate_frame)
top_right = SkyCoord(800 * u.arcsec, -200 * u.arcsec, frame=aia_map1.coordinate_frame)
submap = aia_map1.submap(bottom_left, top_right=top_right)

coaligned_map = coalignment_interface("match_template",aia_map2, submap)

combined image

I am currently implementing the decorator structure for the sunkit-image, but that would be covered in another blog.