llnl-ssapy 1.1.9

SSAPy-Toolkit

SSAPy provides the core propagation and modeling engine. Many higher-level, analysis-ready capabilities built on top of it live in the companion project SSAPy-Toolkit (sometimes abbreviated SSATK), including:

• Higher-level utilities and convenience workflows that wrap common SSAPy tasks

• Plotting tools for orbit and analysis visualization

• Workflow-level wrappers around SSAPy’s coordinate and observer-geometry routines

• Lambertian magnitude / brightness calculations

• Additional related extensions

If your work centers on plotting, dashboards, convenience utilities, or higher-level workflows, SSAPy-Toolkit is often the best place to start — and the natural home for contributions of that kind.

Installation

For installation details, see the Installing SSAPy section of the documentation.

If you are looking for higher-level utilities or plotting-oriented workflows, you may also want to install or explore SSAPy-Toolkit.

Strict dependencies

• Python (3.10+)

The following Python packages are installed automatically when you install SSAPy:

• numpy

• scipy

• astropy

• pyerfa

• emcee

• lmfit

• sgp4

• ipython_genutils

• jplephem

• tqdm

Earth/Moon mesh helpers and other visualization tools are maintained in SSAPy-Toolkit.

Documentation

The documentation is hosted at:

https://software.llnl.gov/SSAPy/

The API documentation may also be explored interactively:

python3

import ssapy
help(ssapy)

Contributing

Contributing to SSAPy is straightforward. Please open a pull request targeting the main branch of the SSAPy repository.

For work that primarily concerns plotting, dashboards, convenience utilities, or higher-level workflows, please also consider whether the contribution belongs in the companion repository SSAPy-Toolkit.

Your PR must pass SSAPy’s required CI checks. For local testing guidance, documentation builds, and Git workflow tips, see the Contribution Guide.

SSAPy’s main branch contains the latest development work.

Releases

For stable installations, we recommend installing the published llnl-ssapy package from PyPI or using one of SSAPy’s versioned source tags.

Code of Conduct

Please note that SSAPy has a Code of Conduct. By participating in the SSAPy community, you agree to abide by its rules.

Authors

SSAPy was developed with support from Lawrence Livermore National Laboratory’s (LLNL) Laboratory Directed Research and Development (LDRD) Program under projects 19-SI-004 and 22-ERD-054, by the following individuals. For software citation order and metadata, use CITATION.cff.

• Joshua E. Meyers (SLAC National Accelerator Laboratory) - Former Lead Developer

• Travis Yeager (LLNL) - Current Lead Developer

• Michael Schneider (LLNL) - Creator, Former Lead Developer

• Edward Schlafly (STScI) - Former Lead Developer

• Julia Ebert (Fleet Robotics)

• Denvir Higgins (LLNL)

• Jason Bernstein (LLNL)

• Daniel Merl (LLNL)

• Imène Goumiri (LLNL)

• Robert Armstrong (LLNL)

• Noah Lifset (UT Austin)

• Alexx Perloff (LLNL)

• Peter McGill (LLNL)

• Nathan Golovich (LLNL)

• Kerianne Pruett (LLNL)

• Caleb Miller (LLNL)

• William A. Dawson (LLNL)

Many thanks go to SSAPy’s additional contributors.

Citing SSAPy

If you use SSAPy in your research, please cite the software using the repository metadata in CITATION.cff. On GitHub, use the “Cite this repository” button to copy the citation in APA or BibTeX format.

The related JOSS paper may also be cited separately:

• Meyers, J. E., Schneider, M. D., Ebert, J. T., Schlafly, E. F., Yeager, T., Perloff, A., Merl, D., Lifset, N., Bernstein, J., Dawson, W. A., Golovich, N., Higgins, D., McGill, P., Miller, C., & Pruett, K. (2025). SSAPy - Space Situational Awareness for Python. Journal of Open Source Software, 10(111), 8147. doi:10.21105/joss.08147

BibTeX:

@article{Meyers2025,
  doi       = {10.21105/joss.08147},
  url       = {https://doi.org/10.21105/joss.08147},
  year      = {2025},
  publisher = {The Open Journal},
  volume    = {10},
  number    = {111},
  pages     = {8147},
  author    = {Meyers, Joshua E. and Schneider, Michael D. and Ebert, Julia T. and Schlafly, Edward F. and Yeager, Travis and Perloff, Alexx and Merl, Daniel and Lifset, Noah and Bernstein, Jason and Dawson, William A. and Golovich, Nathan and Higgins, Denvir and McGill, Peter and Miller, Caleb and Pruett, Kerianne},
  title     = {SSAPy - Space Situational Awareness for Python},
  journal   = {Journal of Open Source Software}
}

You may also cite the following publications (click here for BibTeX entries):

• Yeager, T., Pruett, K., & Schneider, M. (2022). Unaided Dynamical Orbit Stability in the Cislunar Regime. Poster presentation, Cislunar Security Conference, USA.

• Yeager, T., Pruett, K., & Schneider, M. (2023). Long-term N-body Stability in Cislunar Space. Poster presentation, Advanced Maui Optical and Space Surveillance (AMOS) Technologies Conference, USA.

• Yeager, T., Pruett, K., & Schneider, M. (2023, September). Long-term N-body Stability in Cislunar Space. In S. Ryan (Ed.), Proceedings of the Advanced Maui Optical and Space Surveillance (AMOS) Technologies Conference (p. 208). Retrieved from https://amostech.com/TechnicalPapers/2023/Poster/Yeager.pdf

License

SSAPy is distributed under the terms of the MIT license. All new contributions must be made under the MIT license.

See the LICENSE and NOTICE files for details.

SPDX-License-Identifier: MIT

LLNL-CODE-862420

Documentation Inspiration

The structure and organization of this repository’s documentation were inspired by the excellent design and layout of the Coffea project.