SLDTk is a commandline program for fast and robust modelling and correction of limb darkening in solar images. It is not yet ready for primetime, but I would love to hear your feedback and ideas for how to make SLDTk better.

SLDTk is written for Python 3. The following packages are required:

• numpy>=1
• opencv-python>=3
• matplotlib>=2

Note that in addition to opencv-python, the underlying OpenCV library must be installed. There are currently plans to include an optional dependency on scikit-image for systems without OpenCV.

SLDTk can be installed using pip:

$ pip install sldtk

$ sldtk -i IMAGE [optional arguments]

The program takes a range of optional arguments for everything from detection threshold to output directory. A complete list can be seen by calling

$ sldtk -h

For now, the codebase provides the best source of information on SLDTk's features and implementation specific details, as auto-generation of the documentation is still in the works.

Currently only images in the jpg and png formats are supported.

The position and size of the solar disk is automatically determined using computer vision. The disk is subsequently unwrapped and cleaned of outliers (e.g. sunspots and facula) before an average intensity profile is derived.

A pluggable modelling system allows user specified models (e.g. a 2nd degree polynomial) to be fitted to the intensity profile of the solar disk, and the results to be plotted together with the original profile for visual analysis. Reference models with known coefficients can also be overlaid on the produced graph.

Using a fitted model, the solar disk is flat-field corrected to a user selectable bias point. The result can further be fed back into the pipeline to assess its flatness, with a linear model fitted and plotted together with the corrected intensity profile.

Do you have an idea for how to make SLDTk better? Have you found a bug? Head over to the issue tracker to open a new issue or contribute to an existing discussion.

If you are interested in contributing to the codebase, fork SLDTk on GitHub to get started. You can install the project in development mode by using $ pip install -e . from the cloned project root.

Have you found a solution to an existing issue or added a new feature? Pull requests are always welcome.

SLDTk is released under the MIT open source license. Please see LICENSE.txt for details.

The Solar Limb Darkening Toolkit began as an experimental physics project together with Matt Wingham and Sam Heron at Aberystwyth University in the fall of 2017. It is written and maintained by Ariel Ladegaard.