gmat-run 0.3.0

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

gmat-run

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

What this is

A thin, Pythonic wrapper around NASA GMAT's own gmatpy runtime. You bring a working .script; gmat-run loads it, lets you override fields from Python, runs the mission headlessly, and returns ReportFile / ephemeris / ContactLocator output as pandas DataFrames.

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 — that's a future astro-tools project (gmat-sweep) built on top.

Requirements

• Python 3.10, 3.11, or 3.12.
• A local GMAT install. gmat-run does not ship GMAT binaries — install GMAT separately from gmat.gsfc.nasa.gov.

Supported GMAT versions

GMAT release	Status	CI
R2026a	Primary development target	Exercised on every PR (Ubuntu + Windows + macOS)
R2025a	Expected to work	Not exercised in CI
R2024a	Expected to work	Not exercised in CI
R2023a	Expected to work	Not exercised in CI
R2022a	Expected to work	Not exercised in CI

A wider CI matrix is planned for a follow-up release; report any version-specific breakage as an issue and we'll add a CI cell for it.

Installation

pip install gmat-run

Optional extras unlock format- and feature-specific code paths. Each is named after the dependency it pulls in:

Extra	Pulls in	Unlocks
[spiceypy]	spiceypy	SPK (NASA SPICE binary) ephemeris parsing.
[ccsds-ndm]	ccsds-ndm	CCSDS-OEM export via Results.write_oem.
[astropy]	astropy	Leap-second-correct time-scale conversion via gmat_run.time.

Install one or more at once:

pip install gmat-run[spiceypy]
pip install gmat-run[astropy,ccsds-ndm]

Quick start

Load a script, override a field, run the mission, and read each output GMAT wrote as a pandas DataFrame:

from gmat_run import Mission

mission = Mission.load("flyby.script")
mission["Sat.SMA"] = 7000
result = mission.run()

# ReportFile → DataFrame, with UTCGregorian / *ModJulian epoch columns
# promoted to datetime64[ns].
result.reports["ReportFile1"].plot(x="UTCGregorian", y="Sat.Earth.Altitude")

# EphemerisFile → DataFrame, dispatching on file format.
ephem = result.ephemerides["EphemerisFile1"]

# ContactLocator → DataFrame; df.attrs["report_format"] carries the variant.
contacts = result.contacts["ContactLocator1"]

Mission.load discovers a local GMAT install (honouring the GMAT_ROOT environment variable or a gmat_root= argument), bootstraps gmatpy, and parses the script into the live GMAT object graph. Subscript access reads and writes fields against that graph with type coercion. mission.run() executes the mission sequence headlessly, captures GMAT's log, and returns a Results exposing three lazy mappings — reports, ephemerides, and contacts — each keyed by the GMAT resource name and parsing to a DataFrame on first access. See Outputs below for the formats covered.

A gmat-run console script is also installed for shell-script and smoke-test use:

gmat-run run flyby.script --out results/

See the CLI reference for flags, exit codes, and sample output.

Outputs

Results exposes three mappings, each keyed by the GMAT resource name as declared in the .script:

• ReportFile → DataFrame, with UTCGregorian and *ModJulian epoch columns promoted to datetime64[ns].
• EphemerisFile → DataFrame, dispatching on file format: CCSDS-OEM and STK-TimePosVel are read out of the box; SPK (NASA SPICE binary) is read with the [spiceypy] extra installed. Code-500 (GSFC binary) is not implemented — see Known limitations.
• ContactLocator → DataFrame, supporting Legacy and the five tabular ReportFormat variants. df.attrs["report_format"] carries the variant name so downstream code can branch on it without inspecting the column set.

Documentation

Full docs at https://astro-tools.github.io/gmat-run/, including a getting-started guide, GMAT install instructions, the CLI reference, and the API reference.

Runnable example notebooks:

• Load / run / plot — load a stock GMAT sample, run it, and plot altitude over time end-to-end.
• Parameter sweep — vary Sat.SMA across a range, 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.
• Export to CCSDS-OEM — run a stock GMAT sample that emits an STK ephemeris, convert it to a CCSDS-OEM file with Results.write_oem, re-parse the result, and visualise the trajectory in 3D.
• Time-scale conversion — propagate across the 2017-01-01 leap-second boundary and convert the resulting ReportFile's epoch columns between A1, TAI, UTC, TT, and TDB with gmat_run.time and the parser-level convert_to= keyword.

Development

To work on gmat-run itself:

git clone https://github.com/astro-tools/gmat-run.git
cd gmat-run
uv sync --all-groups

See CONTRIBUTING.md for the full branch / PR / test workflow.

Licence

MIT. See LICENSE.