Every night, astronomical surveys capture millions of celestial objects, generating enormous datasets that contain the secrets of stellar evolution, galactic structure, and cosmic phenomena. But raw survey data is notoriously difficult to work with - imagine trying to find specific stars among billions of entries scattered across countless files. This is where the universe-scale data organization challenge begins.
hats-import is the essential bridge between chaotic survey data and scientific discovery, transforming massive astronomical catalogs into the efficient HATS (Hierarchical Triangular Mesh) partitioned format. Built in Python with robust error handling and scalable processing, it intelligently organizes celestial coordinates using spherical geometry, creating spatially-aware data structures that enable lightning-fast queries across the entire sky. The tool handles everything from coordinate transformations to metadata preservation, ensuring that your precious photometric and astrometric measurements remain intact through the conversion process.
This isn’t just another data conversion tool - it’s the foundation that powers modern astronomical research pipelines. From the Rubin Observatory’s Legacy Survey of Space and Time to custom survey projects, hats-import enables researchers to perform complex cross-matching operations, variability studies, and large-scale statistical analyses that would be impossible with traditional flat-file approaches. Whether you’re hunting for rare transient events or mapping the Milky Way’s structure, this tool transforms your data workflow from painful to powerful.
⭐ Stars: 12
💻 Language: Python
🔗 Repository: astronomy-commons/hats-import