Examples

End-to-end Jupyter notebooks that exercise the gmat-run API on stock GMAT sample missions. Each notebook is committed with cell outputs so you can read through it on the docs site without running anything; you can also run them locally after pip install gmat-run[examples] and the matplotlib dependency.

• Load, run, and plot — the canonical loop: Mission.load a stock sample, run it, pull the resulting ReportFile back as a DataFrame, derive altitude, plot.
• Parameter sweep — vary Sat.SMA across a range of values, run the same script for each, and overlay the resulting orbits.
• Ground track — read an EphemerisFile from Results.ephemerides and plot the spacecraft's ground track on a Cartopy world map.