Metadata-Version: 2.4
Name: PINNICLE
Version: 0.2
Summary: A Python library for solving ice sheet modeling problems using Physics Informed Neural Networks
Author-email: Cheng Gong <gong.cheng@dartmouth.edu>, Mansa Krishna <mansa.krishna.gr@dartmouth.edu>, Mathieu Morlighem <Mathieu.Morlighem@dartmouth.edu>
Project-URL: Homepage, https://github.com/ISSMteam/PINNICLE
Project-URL: Documentation, https://pinnicle.readthedocs.io
Project-URL: Bug Tracker, https://github.com/ISSMteam/PINNICLE/issues
Keywords: Ice sheet modeling,Numerical method,Deep learning,Physics-informed neural networks
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Lesser General Public License v2 (LGPLv2)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: tensorflow>=2.11.0
Requires-Dist: tensorflow-probability[tf]>=0.19.0
Requires-Dist: matplotlib
Requires-Dist: pandas
Requires-Dist: mat73
Requires-Dist: deepxde
Dynamic: license-file


# PINNICLE
Physics Informed Neural Networks for Ice and CLimatE

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[![Documentation Status](https://readthedocs.org/projects/pinnicle/badge/?version=latest)](https://pinnicle.readthedocs.io/en/latest/?badge=latest)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.14889235.svg)](https://doi.org/10.5281/zenodo.14889235)

A Python library for solving ice sheet modeling problems using a unified framework with Physics Informed Neural Networks


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**NOTE**

   This project is under active development.

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**Documentation**: [pinnicle.readthedocs.io](https://pinnicle.readthedocs.io)

![](docs/images/pinn.png)

## Physics

- Momentum Conservation (stress balance):
  - Shelfy Stream Approximation (SSA)
  - MOno-Layer Higher-Order (MOLHO) ice flow model

- Mass Conservation (mass balance):
  - Thickness evolution

- Coupuling:
  - stress balance + mass balance

- Time dependent problems

## Data format

- [ISSM](https://issm.jpl.nasa.gov) `model()` type, directly saved from ISSM by `saveasstruct(md, filename)`
- Scattered data


## More

- [Install and Setup](https://pinnicle.readthedocs.io/en/latest/installation.html#installation)
- [An example of stress balance](https://pinnicle.readthedocs.io/en/latest/examples/ssa.html)

