This repository contains the PyRIID package (as well as tests and examples) which provides utilities that support machine learning-based research and solutions to radioisotope identification.
These instructions assume you meet the following requirements:
- Python version: 3.8 to 3.10
- Operating systems: Windows, Mac, or Ubuntu
A virtual environment is recommended.
Tests and examples are ran via Actions on many combinations of Python version and operating system. You can verify support for your platform by checking the workflow files.
To use the latest version on PyPI (note: changes are currently slower to appear here), run:
pip install riid
For the latest features, run:
pip install git+https://github.com/sandialabs/pyriid.git@main
If you are developing PyRIID, clone this repository and run:
pip install -e ".[dev]"
If you have trouble with Pylance resolving imports for an editable install, try this:
pip install -e ".[dev]" --config-settings editable_mode=compat
Examples for how to use this package can be found here.
Unit tests for this package can be found here.
Run all unit tests with the following command:
python -m unittest tests/*.py -vYou can also run one of the run_tests.* scripts, whichever is appropriate for your platform.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate and adhere to our code of conduct.
Maintainers and authors can be found here.
Full copyright details are outlined here
Thank you to the U.S. Department of Energy, National Nuclear Security Administration,
Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D) for funding that has led to version 2.x.
Additionally, thank you to the following individuals who have provided invaluable subject-matter expertise:
- Ben Maestas
- Greg Thoreson
- Michael Enghauser