gmat-run

Run GMAT mission scripts from Python and get results as pandas DataFrames.

What this is

gmat-run drives NASA's General Mission Analysis Tool (GMAT) from Python. You bring a working .script; gmat-run discovers your GMAT install, loads the mission, lets you override fields from Python with type coercion, runs it headlessly, and parses GMAT's ReportFile, ephemeris, ContactLocator, and solver-log output into typed pandas DataFrames.

from gmat_run import Mission

mission = Mission.load("flyby.script")
mission["Sat.SMA"] = 7000
result = mission.run()
result.reports["ReportFile1"].plot(x="UTCGregorian", y="Sat.Earth.Altitude")

What this is not

• Not a way to build GMAT missions from scratch in Python — see gmatpyplus for that.
• Not a .script text generator — see pygmat.
• Not a parallel sweep runner — see gmat-sweep, an astro-tools project built on top of gmat-run.

Where to next

• Getting started — install gmat-run and run your first mission.
• Install GMAT — get the GMAT engine on your machine.
• Run gmat-run in your CI — wire astro-tools/setup-gmat into a GitHub Actions workflow.
• Example notebooks — end-to-end Jupyter notebooks that exercise the API on stock GMAT missions.
• API reference — the public Python API.
• Known limitations — gmatpy single-init constraint and other gotchas.