tatc 3.4.7

Tradespace Analysis Toolkit for Constellations (TAT-C)

Tradespace Analysis Toolkit for Constellations (TAT-C)

The Tradespace Analysis Toolkit for Constellations (TAT-C) provides low-level data structures and functions for systems engineering analysis and design of Earth-observing space missions suitable for pre-Phase A concept studies.

Documentation: https://tatc.readthedocs.io

Repository: https://github.com/code-lab-org/tatc

Installation

TAT-C uses the pip build system to manage dependencies. Install the tatc library in "editable" mode:

pip install -e .

Note: the following optional dependencies are available with bracket notation:

• pip install -e ".[dev]": for development (unit testing, coverage, and linting)
• pip install -e ".[docs]": for generating documentation
• pip install -e ".[examples]": for running optional examples
• pip install -e ".[osse]": for running optional observing system simulation experiment (OSSE) examples

Multiple optional dependencies can be installed with a comma-separated list (e.g., pip install -e ".[dev,examples]")

Development Tools

Development tools are applicable when working with the source code.

Unit Tests

Run unit tests with:

python -m unittest

Optionally, run a test coverage report:

coverage run -m unittest

including html output:

coverage html

Documentation

Generate documentation from the docs directory using the command:

make html

Code Style

This project uses the black code style, applied from the project root:

black .

Contact

Paul T. Grogan [e-mail]

Acknowledgements

This project was supported in part by the National Aeronautics and Space Administration (NASA) Earth Science Division (ESD) Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program. Financial support is acknowledged under NASA grant numbers: NNX17AE06G, 80NSSC17K0586, 80NSSC20K1118, 80NSSC21K1515, 80NSSC22K1705, 80NSSC24K0575, 80NSSC24K0921; NASA Jet Propulsion Laboratory subcontracts: 1689594, 1686623, 1704657, 1705655; Texas A & M University subaward M2403907.

Current Project Team

• PI: Paul T. Grogan [e-mail]
• I. Josue Tapia-Tamayo [e-mail]
• Suvan Kumar [e-mail]

Project Alumni

• Isaac Feldman
• Hayden Daly
• Lindsay Portelli
• Matthew Sabatini
• Evan Abel
• Sigfried Hache