Every night, telescopes around the world capture millions of photons from distant stars, but those raw measurements are just the beginning of the story. Converting instrumental magnitudes into scientifically meaningful photometry requires sophisticated calibration against reference catalogs, precise astrometric solutions, and correction for atmospheric effects—a complex dance of algorithms that can make or break astronomical research.
Pyrt delivers production-grade photometric calibration through its dophot3 engine, orchestrating tools like SExtractor and IRAF to extract sources, then matching them against comprehensive all-sky catalogs including ATLAS, PanSTARRS, and GAIA. The system performs relative in-frame calibration, applies filter response corrections, and refines astrometric solutions beyond what astrometry.net provides alone. Its NDTree-based star matching algorithm efficiently handles everything from narrow-field observations to challenging 180-degree all-sky frames.
Currently powering automated pipelines at D50 and SBT telescopes, pyrt also drives the real-time photometric monitoring at Ondřejov Observatory’s Makak wide-field camera. With tens of thousands of images successfully processed, this suite represents the practical wisdom of working astronomers distilled into reliable Python tools—just feed it an astrometry.net-solved FITS file and receive publication-ready photometric measurements in return.
⭐ Stars: 5
💻 Language: Python
🔗 Repository: mates14/pyrt