Refactoring the codebase

 I am refactoring the whole codebase to make it more maintainable and in that hoping to solve the issue with HoloViews. I am making the codebase fully pragmatic and declarative and using Parameterised classes. I hope so it resolves the issue with HoloViews. 

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Watching the tutorials in depth

 I am facing a serious bug now, I can't render bokeh plots at all. HoloViews objects is not able to render anything out at all. I have to find the solution because our whole project depends on HoloViews objects and its capabilities. Otherwise we are just plotting simple matplotlib plots. So currently I am going through the tutorials and documentation of all HoloViz ecosystem, be it Panel, or HoloViews or hvplot in detail. I am hoping to find the solution, maybe raise the issue through github, as I have seen some similar issue with people in the github issues of Panel.

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Midterm Evaluations Are Close!

So, in the past two weeks, upon discussion with my mentors, I started working on the stretch goal, which involves using Astroquery’s TAP Plus for making the URL calls. Additionally, I had to clean up some code and remove the instruments SPICE and PHI from returning wavelength data due to their individual issues.

For SPICE, the `wavemin’ and `wavemax` values are only available for the first spectral window in SOAR, so the data is not entirely representative of what a user might be searching for. Similarly, for PHI, the issue is that two different units are used to represent wavelength, which results in very
different `wavemin’ and `wavemax` data due to the data being in both angstrom and nanometer units. Unfortunately, this is not specified anywhere in SOAR, so to ensure that `sunpy-soar` does not
return any misleading data to the user, we’ve decided to exclude the wavelength data for these instruments.

Coming to the change in table fetching methods. TAP Plus basically uses SQL to fetch tables, which is different from the normal TAP that uses ADQL to fetch tables. This avoids the entire process of manually constructing Astropy tables after calling the SOAR API with TAP.

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Blog 3: Side Quests Week

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.

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Filling the Temporal Gaps in AGN Light Curve Data

 Introduction to the Challenge

In our ongoing quest to understand Active Galactic Nuclei (AGNs), handling the discontinuous nature of AGN light curve data remains the main goal. The gaps in observation data, caused by unavoidable operational and environmental constraints, obscure the complete picture of these AGN data. To address several methods are taken into account to approach the temporal data interpolation, combining traditional techniques with advanced machine learning models.

Traditional Interpolation Techniques

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Partition functions

Support has been added for the species-specific partition functions that are usually included along with the new linelists. In doing so, a new config parameter was added to allow the user to enable RADIS to automatically modify the local database files and update the config file accordingly.

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