Every astronomical observation tells a story written across the sky, but extracting meaningful insights requires defining precise regions of interest - whether you’re studying star formation in nebular clouds, analyzing galaxy morphologies, or masking cosmic ray artifacts in your CCD images. The challenge lies not just in drawing these boundaries, but in translating them seamlessly between different coordinate systems, file formats, and analysis pipelines.
Astropy Regions transforms this complex geometric dance into elegant Python code, offering a comprehensive toolkit for creating, manipulating, and analyzing astronomical regions. From simple circles and polygons to complex compound shapes, the package handles coordinate transformations between pixel and world coordinate systems with mathematical precision. It supports industry-standard formats like DS9 regions, FITS regions, and CRTF files, while providing powerful boolean operations for combining shapes and efficient masking capabilities for photometric analysis. Whether you’re selecting apertures for stellar photometry or defining source extraction regions for spectroscopy, the package handles the coordinate system complexities so you can focus on the science.
Maintained by astronomy software veterans Larry Bradley and Adam Ginsburg, this tool has become indispensable for survey astronomers, exoplanet researchers, and anyone working with spatially-resolved astronomical data. As telescopes generate increasingly complex datasets - from JWST’s infrared mosaics to upcoming LSST survey data - having robust, programmatic region handling becomes not just convenient, but essential for reproducible astronomical research.
⭐ Stars: 65
💻 Language: Python
🔗 Repository: astropy/regions