{ "info": { "author": "Ariel Ladegaard", "author_email": "legendin@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Environment :: Console", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Operating System :: POSIX :: Linux", "Programming Language :: Python :: 3 :: Only", "Topic :: Scientific/Engineering :: Astronomy", "Topic :: Scientific/Engineering :: Physics" ], "description": "================================\nThe Solar Limb Darkening Toolkit\n================================\n\nSLDTk is a commandline program for fast and robust modelling and correction\nof limb darkening in solar images.\n\n\nGetting Started\n===============\nPrerequisites\n-------------\nSLDTk is written for Python 3. The following packages are required:\n\n- ``numpy>=1``\n- ``opencv-python>=3``\n- ``matplotlib>=2``\n\nNote that in addition to ``opencv-python``, the underlying OpenCV library must\nbe installed. There are currently plans to include an optional dependency on\n``scikit-image`` for systems without OpenCV.\n\nInstallation\n------------\nSLDTk can be installed using pip:\n\n.. code-block:: console\n\n $ sudo pip install sldtk\n\nUsage\n-----\n\n.. code-block:: console\n\n $ sldtk -i IMAGE [optional arguments]\n\nThe program takes a range of optional arguments for everything from detection\nthreshold to output directory. A complete list can be seen by calling\n\n.. code-block:: console\n\n $ sldtk -h\n\nFeatures\n========\nFor now, the codebase provides the best source of information on SLDTk's\nfeatures and implementation specific details, as auto-generation of\ndocumentation has not yet been set up.\n\nInput Formats\n-------------\nCurrently only images in the ``jpg`` and ``png`` formats are supported.\n\nDetection\n---------\nThe position and size of the solar disk is automatically determined using\ncomputer vision. The disk is subsequently unwrapped and cleaned of outliers\n(e.g. sunspots and facula) before an average intensity profile is generated.\n\nModelling\n---------\nA pluggable modelling system allows user specified models (e.g. a 2nd degree\npolynomial) to be fitted to the intensity profile of the solar disk, and the\nresults to be plotted together with the original profile for visual analysis.\nReference models with known coefficients can also be overlaid on the produced\ngraph.\n\nCorrection\n----------\nUsing a fitted model, the solar disk is flat-field corrected to a user\nselectable bias point. The result can further be fed back into the pipeline\nto assess its flatness, with a linear model fitted and plotted together\nwith the corrected intensity profile.\n\nContributing\n============\nDo you have an idea for how to make SLDTk better? Have you found a bug? Head\nover to the `issue tracker `_ to\nopen a new issue or contribute to an existing discussion.\n\nIf you are interested in contributing to the codebase,\n`fork SLDTk on GitHub `_\nto get started. You can install the project in development mode by using\n``$ sudo pip install -e .`` from the cloned project root.\n\nHave you found a solution to an existing issue or added a new feature?\n`Pull requests `_ are always welcome.\n\nLicense\n=======\nSLDTk is released under the MIT open source license. Please see\n`LICENSE.txt `_\nfor details.\n\nAcknowledgments\n===============\nThe Solar Limb Darkening Toolkit began as an experimental physics project\ntogether with Matt Wingham and Sam Heron at Aberystwyth University in the\nfall of 2017. 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