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CCDLAB provides graphical user interface functionality for FITS image viewing and data reduction based on the JPFITS FITS-file interface. It can view, manipulate, and save FITS primary image data and image extensions, view and manipulate FITS image headers, and view FITS Bintable extensions. The code enables batch processing, viewing, and saving of FITS images and searching FITS files on disk. CCDLAB also provides general image reduction techniques, source detection and characterization, and can create World Coordinate Solutions automatically or manually for FITS images.
Fastrometry is a Python implementation of the fast world coordinate solution solver for the FITS standard astronomical image. When supplied with the approximate field center (+-25%) and the approximate field scale (+-10%) of the telescope and detector system the astronomical image is from, fastrometry provides WCS solutions almost instantaneously. The algorithm is also originally implemented with parallelism enabled in the Windows FITS image processor and viewer CCDLAB (ascl:2206.021).
FITS File interaction written in Visual Studio C# .Net.
JPFITS is not based upon any other implementation and is written from the ground-up, consistent with the FITS standard, designed to interact with FITS files as object-oriented structures.
JPFITS provides functionality to interact with FITS images and binary table extensions, as well as providing common mathematical methods for the manipulation of data, data reductions, profile fitting, photometry, etc.
JPFITS also implements object-oriented classes for Point Source Extraction, World Coordinate Solutions (WCS), WCS automated field solving, FITS Headers and Header Keys, etc.
The automatic world coordinate solver is based on the trigonometric algorithm as described here:
https://iopscience.iop.org/article/10.1088/1538-3873/ab7ee8
All function parameters, methods, properties, etc., are coded with XML descriptions which will function with Visual Studio. Other code editors may or may not read the XML files.
Everything which is reasonable to parallelize in order to benefit from the computation speed increase for multi-threaded systems has been done so. In all such cases function options are given in order to specify the use of parallelism or not. Generally, most image manipulation functions are highly amenable to parallelism. No parallelism is forced, i.e., any code which may execute parallelized is given a user option to do so or not.