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| sbpy | |
|---|---|
| Name | sbpy |
| Programming language | Python |
| Operating system | Cross-platform |
| Genre | Astronomy software |
sbpy
sbpy is a Python library for small-body planetary astronomy focused on analysis of comets, asteroids, and trans-Neptunian objects. It provides utilities for physical parameter computation, orbit handling, photometry, and spectrum processing, integrating with prevailing astronomy ecosystems for research and mission science. sbpy aims to interoperate with prominent tools and archives used in observational and theoretical studies.
sbpy is designed to support workflows common to investigators using facilities and projects such as Hubble Space Telescope, James Webb Space Telescope, Pan-STARRS, Sloan Digital Sky Survey, and Gaia. It complements astronomy packages like Astropy, SunPy, Photutils, Specutils, and Astroquery while enabling interfaces to data centers and surveys including NASA Exoplanet Archive, Minor Planet Center, European Space Agency, Space Telescope Science Institute, and Virtual Observatory. sbpy addresses tasks relevant to missions and programs such as OSIRIS-REx, Hayabusa2, New Horizons, Rosetta, and NEOWISE.
sbpy implements routines for photometric reduction, spectral reflectance computation, thermal modeling, and nucleus/coma decomposition used in campaigns like Deep Impact and EPOXI. It supports conversion between coordinate representations used by International Celestial Reference Frame, JPL Horizons, and Minor Planet Center formats, and computes quantities applied in studies by teams associated with Planetary Science Division (NASA), Jet Propulsion Laboratory, Caltech, and European Southern Observatory. sbpy provides helpers for magnitude systems employed by Vega, AB magnitude system, and surveys such as Pan-STARRS1 Photometric System.
Built in Python (programming language), sbpy follows modular design patterns similar to Astropy Project subpackages, using object-oriented models for bodies, spectra, and orbits. It interoperates with numerical and plotting libraries like NumPy, SciPy, Matplotlib, and integrates with data-access tools such as Astroquery clients for services including NASA Planetary Data System and International Astronomical Union Minor Planet Center. The codebase emphasizes test-driven development, continuous integration systems used by projects like Travis CI and GitHub Actions, and documentation practices akin to Read the Docs.
sbpy installs via package managers and build tools that are common in the community, compatible with environments produced by Conda (package manager), pip (package manager), and container platforms like Docker (software). Typical usage workflows mirror examples found in tutorials for Astropy and Photutils: import core modules, construct objects representing small bodies, and call methods to perform photometric, spectral, or orbital computations. sbpy is used in notebooks compatible with Jupyter Notebook and JupyterLab for reproducible analyses similar to those published in journals like The Astrophysical Journal, Astronomy & Astrophysics, and Monthly Notices of the Royal Astronomical Society.
The development of sbpy follows collaborative models used by open-source scientific software projects hosted on platforms like GitHub and coordinated via communication channels such as Slack (software), GitHub Issues, and mailing lists modeled after those of the Astropy Project. Contributors often include members from institutions like NASA Goddard Space Flight Center, California Institute of Technology, Massachusetts Institute of Technology, University of Arizona, and Max Planck Institute for Solar System Research. The project adopts code style and review practices influenced by community standards exemplified by PEP 8 and continuous integration tooling used by CircleCI and GitHub Actions.
sbpy has been applied in analyses accompanying missions and surveys including OSIRIS-REx, Hayabusa2, Rosetta, NEOWISE, and follow-up observations from facilities such as Very Large Telescope, Keck Observatory, Subaru Telescope, and Arecibo Observatory. Use cases include deriving albedos and diameters for objects cataloged by the Minor Planet Center, modeling cometary comae as studied during the Rosetta mission, and preparing observation planning compatible with proposals to Hubble Space Telescope and James Webb Space Telescope. Community tutorials demonstrate workflows integrating sbpy with data products from Pan-STARRS, Sloan Digital Sky Survey, and Gaia.
sbpy is distributed under licensing consistent with many community astronomy packages; development and releases are published via repositories and package indices used by Python Package Index and distribution channels managed by projects like Conda Forge. Source code, issue tracking, and contribution guidelines are hosted on collaborative platforms modeled after GitHub repositories for major community packages. Binary distributions and documentation follow practices used by projects hosted on Read the Docs and archived in services such as Zenodo.
Category:Astronomy software