Improved User Information for XRTpy Abundance Feature

[joyvelasquez]

Description

I would like to suggest an enhancement to provide better print/return information for users utilizing the abundance feature. Currently, when users use the abundance option, they do not receive any feedback regarding which abundance model is being used in the calculations.

Proposed Solution:

I propose implementing a return statement that informs the user about the specific abundance model being utilized in the calculations. This information should be displayed whenever the user employs the abundance feature within the XRTpy package. Furthermore, adding more details to the doc string within the function.

This enhancement will significantly improve the user experience and help users have a clear understanding of the abundance models used in their calculations, facilitating better interpretation and utilization of the results.

[jslavin]

In general I agree with the ideas behind this. However, the broader issue is the spectral model, given that we've talked about allowing more spectral models in addition to the Chianti ones. Maybe we should separate those two, i.e. the assumed abundance set and the spectral modeling code.
Here's a suggested approach: Make two new attributes of TemperatureResponseFundamental objects, the model_source and abundance_set. These attributes will be set when the TemperatureResponseFundamental is instantiated, so a mechanism for getting those values from included Chianti model data and from any other input plasma emission model would need to be implemented.
Do any other Sunpy affilliated packages do something like this?

[joyvelasquez]

Thank you, @jslavin , for the insightful suggestion! I agree with the approach to expand the scope of user feedback to include not just the abundance model but also the broader spectral model being used.

Regarding the suggested attributes:

• model_source: Implementing an attribute like model_source to inform users about the source of the spectral model is a great idea. This attribute will provide transparency and context, especially when users are utilizing models from various sources such as Chianti, other databases, or custom models.
• abundance_set: Similarly, the abundance_set attribute would be invaluable for users to easily identify the specific abundance model being employed in their calculations. This aligns directly with the initial enhancement I proposed and takes it a step further in providing comprehensive feedback.

We should discuss how best to implement these considerations. For the Chianti model data, this might involve parsing metadata. For other input models, we may need a flexible method that can adapt to different data formats. Should we also consider a required format for other input models?

I'm not sure if Sunpy affiliated packages do something like this. Perhaps we should tag @wtbarnes for insight? I am wondering if Sunpy/AIApy would be interested in developing a structured approach together to address this issue?

[wtbarnes]

I wonder if the proposed SourceSpectra object in sunpy/sunkit-instruments#111 would address this, though much more generally. It would give the user an interface to specify any spectra they want, but xrtpy (or perhaps some other upstream source like sunkit-instruments) could also provide a set of precomputed spectra, e.g. using coronal and photospheric abundances.