aiapy 0.12.1

``aiapy`` is a Python package for analyzing data from the Atmospheric Imaging Assembly (AIA) instrument onboard NASA's Solar Dynamics Observatory (SDO) spacecraft.

aiapy is a Python package for analyzing data from the Atmospheric Imaging Assembly (AIA) instrument onboard NASA’s Solar Dynamics Observatory (SDO) spacecraft.

For more information, see the aiapy documentation.

For some examples of using aiapy, see our gallery.

Citing

If you use aiapy in your scientific work, we would appreciate you citing it in your publications. The latest citation information can be found in the documentation, or obtained with aiapy.__citation__.

Usage of Generative AI

We expect authentic engagement in our community. Be wary of posting output from large language models or similar generative AI as comments on GitHub or any other platforms, as such comments tend to be formulaic and low‑quality content. Do not post the output from Large Language Models or similar generative AI as code, issues or comments on GitHub or any other platform. If you use generative AI tools as an aid in developing code or documentation changes, ensure that you fully understand the proposed changes and can explain why they are the correct approach and an improvement to the current state. For more information see our documentation on fair and appropriate AI usage.

Contributing

We love contributions! aiapy is open source, built on open source, and we’d love to have you hang out in our community.

Please checkout the contributing guide for more information on how to contribute to aiapy.

Imposter syndrome disclaimer: We want your help. No, really.

There may be a little voice inside your head that is telling you that you’re not ready to be an open source contributor; that your skills aren’t nearly good enough to contribute. What could you possibly offer a project like this one?

We assure you - the little voice in your head is wrong. If you can write code at all, you can contribute code to open source. Contributing to open source projects is a fantastic way to advance one’s coding skills. Writing perfect code isn’t the measure of a good developer (that would disqualify all of us!); it’s trying to create something, making mistakes, and learning from those mistakes. That’s how we all improve, and we are happy to help others learn.

Being an open source contributor doesn’t just mean writing code, either. You can help out by writing documentation, tests, or even giving feedback about the project (and yes - that includes giving feedback about the contribution process). Some of these contributions may be the most valuable to the project as a whole, because you’re coming to the project with fresh eyes, so you can see the errors and assumptions that seasoned contributors have glossed over.

Note: This disclaimer was originally written by Adrienne Lowe for a PyCon talk, and was adapted by irispy-lmsal based on its use in the README file for the MetPy project.