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| astroplan | |
|---|---|
| Name | astroplan |
| Developer | Astropy Project |
| Released | 2014 |
| Programming language | Python |
| Operating system | Cross-platform |
| License | BSD |
astroplan
astroplan is an open-source Python library for observation planning, visibility calculations, and scheduling for ground- and space-based astronomical facilities. It provides high-level routines for target visibility, altitude and azimuth computations, constraint handling, and observation scheduling built on top of established astronomical software and standards. The project is widely used by researchers, observatories, and educators to integrate astrometry, time standards, and ephemerides into practical observing workflows.
astroplan integrates precise timekeeping from International Astronomical Union standards and ephemerides from projects like Jet Propulsion Laboratory to compute target positions and observability. It complements and extends components from the Astropy Project core, leveraging libraries such as NumPy, SciPy, and Matplotlib for numerical routines and visualization. The package supports site definitions for historical locations like Mauna Kea, La Silla Observatory, and Palomar Observatory as well as space platforms such as Hubble Space Telescope and James Webb Space Telescope. Designed for interoperability, astroplan adheres to conventions used by institutions including European Southern Observatory and observatory scheduling systems at National Optical-Infrared Astronomy Research Laboratory.
astroplan offers routines for rise, set, transit times and altitude-azimuth calculations using algorithms compatible with standards from the International Earth Rotation and Reference Systems Service and the International Celestial Reference Frame. It implements constraint frameworks for moon avoidance, airmass limits, and twilight definitions applied by observatories like Keck Observatory and Subaru Telescope. The scheduling module supports both fixed and flexible observation blocks similar to systems used at Large Synoptic Survey Telescope planning studies and observatory tools at Gemini Observatory. Visualization helpers produce charts resembling planning products from Space Telescope Science Institute and site planners used by European Space Agency missions.
astroplan is architected as a modular Python package layered atop Astropy Project's coordinate transforms and time handling, with a clear separation between core astronomical computations and higher-level scheduling logic. Core components interact with data models and tables from Pandas and arrays from NumPy; plotting interfaces rely on Matplotlib and optional integration with Bokeh or Plotly for interactive displays. Ephemeris lookup can be performed using data from JPL Horizons or packaged ephemerides maintained by Astropy Project. The design promotes testability and reproducibility following practices advocated by organizations such as Software Carpentry and Mozilla Science Lab.
astroplan is applied to classical observing preparation at facilities like Mount Wilson Observatory, queue scheduling at Gemini Observatory, and time allocation planning for campaigns coordinated with National Radio Astronomy Observatory instruments. It supports educational labs in university courses at institutions such as Harvard University and California Institute of Technology and is used in outreach projects by museums like the Smithsonian Institution and planetariums such as Hayden Planetarium. Astronomers use it for multi-observatory campaign coordination involving facilities like Atacama Large Millimeter Array, Very Large Telescope, and small aperture networks exemplified by Las Cumbres Observatory.
Development occurs within the collaborative ecosystem of the Astropy Project with contributions from researchers affiliated with organizations such as NASA, European Southern Observatory, and universities including University of Washington and University of California, Berkeley. The project follows community governance models similar to NumFOCUS-backed initiatives and uses hosting services like GitHub for issue tracking and pull requests. Documentation and tutorials are maintained with tools used by projects like Read the Docs and continuous integration services such as Travis CI and GitHub Actions ensure code quality. Regular contributors have presented work at meetings of societies like the American Astronomical Society and workshops held by PASP and regional conferences.
Introductory examples illustrate target altitude plots, rise/set calculations, and scheduling snippets mirroring demonstrations given at institutes like Space Telescope Science Institute and in course material from Massachusetts Institute of Technology. Tutorials cover integration with catalog services such as Simbad and mission ephemerides from JPL Horizons, and example notebooks often accompany publications in journals like The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society. Community-contributed notebooks are hosted alongside example sets produced by projects like AstroHackWeek and data carpentry sessions.
astroplan is implemented in Python and depends on Astropy Project for coordinates and time, NumPy for array operations, SciPy for optimization routines, and Matplotlib for plotting. Optional integrations and performance improvements may use Cython or rely on external ephemeris services such as JPL Horizons and data formats used by Virtual Observatory standards from the International Virtual Observatory Alliance. The package supports major operating systems endorsed by the Python Software Foundation and aligns with packaging tools like pip and Conda for distribution, consistent with practices at repositories like PyPI.
Category:Astronomy software