Metadata-Version: 2.4
Name: zonolayer
Version: 0.5.0
Summary: Last-layer uncertainty modeling via zonotopic representations.
Author: Matthew McCann, Marco De Angelis
License-Expression: MIT
Project-URL: Homepage, https://github.com/MattCodes03/zonolayer
Project-URL: Repository, https://github.com/MattCodes03/zonolayer
Project-URL: Bug Tracker, https://github.com/MattCodes03/zonolayer/issues
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: torch
Requires-Dist: matplotlib
Requires-Dist: PyIPM
Requires-Dist: scipy
Dynamic: license-file

# Zonolayer

**Matthew McCann**  
_University of Strathclyde, 2025_

Developed with guidance and support from **[Marco de Angelis](https://github.com/marcodeangelis)**, University of Strathclyde

[![Python Version](https://img.shields.io/badge/python-3.9%2B-blue.svg)](https://www.python.org/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)
[![PyPI Version](https://img.shields.io/pypi/v/zonolayer)](https://pypi.org/project/zonolayer/)

**Zonolayer** is a Python package for **last-layer uncertainty modeling via zonotopic representations**.  
It provides **zonotopic output bounds** and **statistical prediction intervals** for neural networks with interval-bounded outputs, enabling precise and interpretable uncertainty quantification in regression tasks.

---

## Features

- Compute **zonotopic bounds** for last-layer outputs.
- Combine **statistical prediction intervals** with interval uncertainty.
- Compatible with PyTorch networks exposing latent features.
- Modular, research-friendly, and easy to use.

By default, Zonolayer relies on **NumPy** for all numerical computations and interval handling.  

If you require more advanced interval arithmetic (e.g., using [`pyinterval`](https://pypi.org/project/pyinterval/) or other specialized packages), you can install the optional dependencies and modify the code accordingly, or submit a request for support to be added. I appreciate any and all feedback.

IPM support using the [PyIPM library by J. Sadeghi](https://github.com/JCSadeghi/PyIPM)

---

## Installation

Ensure all requirements from `requirements.txt` are installed to reduce any potential issues.

```bash
pip install zonolayer
```

---
## Getting Started
See `basic_usage.py` in the examples directory for the quickest method to get up and running and start experimenting with the library.

### Example Plots

Zonolayer produces zonotopic bounds and statistical prediction intervals. Example outputs:

![Zonotopic bounds](examples/ExampleOutput.png)
![Zonotopic bounds 2](examples/ExampleOutput2.png)

---
## License
MIT License

Copyright (c) 2025 Matthew McCann

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

