Now that we’ve agreed on the structure of the co-alignment API and also laid down its foundation, all that’s left is to validate it through actual tests and generate some gallery examples. First try with coaligning EIS raster with AIA map Let’s take a closer look at the EIS raster first. I found an AIA image close to the date_average of the raster. EIS raster AIA Full-disc image Updated EIS At first glance, the results seemed promising, but a more detailed analysis revealed some discrepancies.

While the mentors are waiting for community reviews on the new coalignment API, I’ve been diving into some fun side quests. Side Quest 1: ASDA Example The long-needed Automated Swirl Detection Algorithm (ASDA) example gallery in the sunkit-image is now ready. The ASDA module is for identifying the swirls or vortices in the 2D flow field of the solar atmosphere. ASDA offers a robust tool for detecting and analyzing the vortices in the solar atmosphere.