| Name | riid JSON |
| Version |
2.1.0
JSON |
| download |
| home_page | None |
| Summary | Machine learning-based models and utilities for radioisotope identification |
| upload_time | 2024-08-09 01:15:58 |
| maintainer | None |
| docs_url | None |
| author | Tyler Morrow, Nathan Price, Travis McGuire, Tyler Ganter, Aislinn Handley, Paul Thelen, Alan Van Omen, Leon Ross, Alyshia Bustos |
| requires_python | <3.11,>=3.8 |
| license | # BSD 3-Clause License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
pyriid
riid
machine learning
radioisotope identification
gamma spectrum
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
|
<p align="center">
<img src="https://user-images.githubusercontent.com/1079118/124811147-623bd280-df1f-11eb-9f3a-a4a5e6ec5f94.png" alt="PyRIID">
</p>
[](https://badge.fury.io/py/riid)
[](https://badge.fury.io/py/riid)
PyRIID is a Python package providing modeling and data synthesis utilities for machine learning-based research and development of radioisotope-related detection, identification, and quantification.
## Installation
Requirements:
- Python version: 3.8 to 3.10
- Operating systems: Windows, Mac, or Ubuntu
A virtual environment is recommended.
Tests and examples are run via Actions on many combinations of Python version and operating system.
You can verify support for your platform by checking the workflow files.
### For Use
To use the latest version on PyPI (note: changes are slower to appear here), run:
```sh
pip install riid
```
**For the latest features, run:**
```sh
pip install git+https://github.com/sandialabs/pyriid.git@main
```
### For Development
If you are developing PyRIID, clone this repository and run:
```sh
pip install -e ".[dev]"
```
## Examples
Examples for how to use this package can be found [here](https://github.com/sandialabs/PyRIID/blob/main/examples).
## Tests
Unit tests for this package can be found [here](https://github.com/sandialabs/PyRIID/blob/main/tests).
Run all unit tests with the following:
```sh
python -m unittest tests/*.py -v
```
You can also run one of the `run_tests.*` scripts, whichever is appropriate for your platform.
## Docs
API documentation can be found [here](https://sandialabs.github.io/PyRIID).
Docs can be built locally with the following:
```sh
pip install -r pdoc/requirements.txt
pdoc riid -o docs/ --html --template-dir pdoc
```
## Contributing
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](https://github.com/sandialabs/PyRIID/blob/main/CODE_OF_CONDUCT.md).
## Contacts
Maintainers and authors can be found [here](https://github.com/sandialabs/PyRIID/blob/main/pyproject.toml).
## Copyright
Full copyright details can be found [here](https://github.com/sandialabs/PyRIID/blob/main/NOTICE.md).
## Acknowledgements
**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:
- Paul Thelen (also an author)
- Ben Maestas
- Greg Thoreson
- Michael Enghauser
- Elliott Leonard
## Citing
When citing PyRIID, please reference the U.S. Department of Energy Office of Science and Technology Information (OSTI) record here:
[10.11578/dc.20221017.2](https://doi.org/10.11578/dc.20221017.2)
## Related Reports, Publications, and Projects
1. Alan Van Omen, *"A Semi-Supervised Model for Multi-Label Radioisotope Classification and Out-of-Distribution Detection."* Diss. 2023. doi: [10.7302/7200](https://dx.doi.org/10.7302/7200).
2. Tyler Morrow, *"Questionnaire for Radioisotope Identification and Estimation from Gamma Spectra using PyRIID v2."* United States: N. p., 2023. Web. doi: [10.2172/2229893](https://doi.org/10.2172/2229893).
3. Aaron Fjeldsted, Tyler Morrow, and Douglas Wolfe, *"Identifying Signal-to-Noise Ratios Representative of Gamma Detector Response in Realistic Scenarios,"* 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD), Vancouver, BC, Canada, 2023. doi: [10.1109/NSSMICRTSD49126.2023.10337860](https://doi.org/10.1109/NSSMICRTSD49126.2023.10337860).
4. Alan Van Omen and Tyler Morrow, *"A Semi-supervised Learning Method to Produce Explainable Radioisotope Proportion Estimates for NaI-based Synthetic and Measured Gamma Spectra."* United States: N. p., 2024. Web. doi: [10.2172/2335904](https://doi.org/10.2172/2335904).
- [Code, data, and best model](https://zenodo.org/doi/10.5281/zenodo.10223445)
5. Alan Van Omen and Tyler Morrow, *"Controlling Radioisotope Proportions When Randomly Sampling from Dirichlet Distributions in PyRIID."* United States: N. p., 2024. Web. doi: [10.2172/2335905](https://doi.org/10.2172/2335905).
6. Alan Van Omen, Tyler Morrow, et al., *"Multilabel Proportion Prediction and Out-of-distribution Detection on Gamma Spectra of Short-lived Fission Products."* Annals of Nuclear Energy 208 (2024): 110777. doi: [10.1016/j.anucene.2024.110777](https://doi.org/10.1016/j.anucene.2024.110777).
- [Code, data, and best models](https://zenodo.org/doi/10.5281/zenodo.12796964)
7. Aaron Fjeldsted, Tyler Morrow, et al., *"A Novel Methodology for Gamma-Ray Spectra Dataset Procurement over Varying Standoff Distances and Source Activities,"* Nuclear Instruments and Methods in Physics Research Section A (2024): 169681. doi: [10.1016/j.nima.2024.169681](https://doi.org/10.1016/j.nima.2024.169681).
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