https://github.com/EdiGlacUQ/fenics_ice

https://github.com/EdiGlacUQ/fenics_ice

Last synced: about 1 month ago
JSON representation

• Host: GitHub
• URL: https://github.com/EdiGlacUQ/fenics_ice
• Owner: EdiGlacUQ
• License: lgpl-3.0
• Created: 2017-08-26T20:24:36.000Z (over 7 years ago)
• Default Branch: main
• Last Pushed: 2024-07-09T09:04:25.000Z (6 months ago)
• Last Synced: 2024-08-03T16:08:16.907Z (5 months ago)
• Language: Python
• Size: 76.2 MB
• Stars: 4
• Watchers: 4
• Forks: 7
• Open Issues: 14
• Metadata Files:
  • Readme: README.rst
  • License: COPYING
  • Authors: AUTHORS

Awesome Lists containing this project

• cryosphere-links - Fenics Ice - Ice Sheet model with Bayesian Uncertainty Quantification ([p](https://doi.org/10.5194/gmd-2021-90)). (Ice Sheets and Glaciers / ISG Software)

README

        
FEniCS_ice

----------

**FEniCS_ice is a finite element model framework, 

that quantifies the initialization uncertainty 

for time-dependent ice sheet models.**

FEniCS_ice is a Python code intended for Bayesian quantification of uncertainty 

of large-scale parameter sets within an ice-sheet flow model. 

The implementation consist of a combination of data assimilation and bayesian inference.

This involves 1) inferring unobserved model parameters from data; 2) determining

the uncertainty of the inferred model parameters; 3) running the forward model to make a

prediction about a quantity of interest (e.g. ice mass loss); 4) Propagating the uncertainty 

in the inferred parameters to the model prediction. 

The code contains a dynamic solver for ice-sheet flow which implements the 

Shallow-Shelf Approximation (`MacAyeal et al, 1989.`_)

and approximates parameter covariance using a low-rank approximation to 

the inverse of the cost-function Hessian. The code uses Algorithmic Differentiation 

to find sensitivity of time-evolving Quantities of Interest to parameter sets, 

allowing projections of parameter uncertainty forward in time.

.. _MacAyeal et al, 1989.: https://doi.org/10.1029/JB094iB04p04071

Installation, documentation

---------------------------

The documentation website is currently in construction,

but there is a `User guide`_ and a basic installation info below.

.. _User guide: https://github.com/EdiGlacUQ/fenics_ice/tree/main/user_guide

Conda installation:

------------------

1. Clone the repository::

    git clone https://github.com/EdiGlacUQ/fenics_ice.git

2. To install via `Conda`_ use `install.sh`_, this script will install and test FEniCS_ice.

Be sure to set **CONDA_HOME** before installing, and add the line below to your .bashrc::

    export FENICS_ICE_BASE_DIR="/path/to/fenics_ice/repo"

3. Run install.sh.

4. Run all serial tests::

    pytest -v --order-scope=module --color=yes

5. Run all parallel tests::

    mpirun -n 2 pytest -v --order-scope=module --color=yes

Install via Mamba:

------------------

1. Clone the repository and create `Mamba`_ environment::

    cd fenics_ice

    mamba env create -f environment.yml

    pip install -e .

Make sure the environment "fenics_ice" is activated.

2. Install `tlm_adjoint`_::

    git clone https://github.com/EdiGlacUQ/tlm_adjoint.git

    cd tlm_adjoint

    pip install -e .

3. Run all serial tests::

    pytest -v --order-scope=module --color=yes

4. Run all parallel tests::

    mpirun -n 2 pytest -v --order-scope=module --color=yes

Code source

------------

- View the source code `on GitHub`_.

- Report bugs or share your ideas on the `issue tracker`_.

- Improve the model by submitting a `pull request`_.

.. _on GitHub: https://github.com/EdiGlacUQ/fenics_ice

.. _issue tracker: https://github.com/EdiGlacUQ/fenics_ice/issues

.. _pull request: https://github.com/EdiGlacUQ/fenics_ice/pulls

.. _Conda: https://docs.conda.io/en/latest/miniconda.html

.. _install.sh: https://github.com/EdiGlacUQ/fenics_ice/blob/main/install.sh

.. _Mamba: https://mamba.readthedocs.io/en/latest/installation.html#micromamba

.. _tlm_adjoint: https://github.com/EdiGlacUQ/tlm_adjoint

About

-----

:Version:

    .. image:: https://img.shields.io/badge/python-3.8%2B-blue

        :target: https://www.python.org/

        :alt: Pypi version

        

:Citation:

    .. image:: https://img.shields.io/badge/Citation-GMD%20paper-orange.svg

        :target: https://doi.org/10.5194/gmd-14-5843-2021

        :alt: GMD Paper

    .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.5153231.svg

        :target: https://zenodo.org/record/5153231

        :alt: Zenodo

:Tests:       

    .. image:: https://img.shields.io/badge/test-passing-green

        :target: https://github.com/EdiGlacUQ/fenics_ice/actions/workflows/test-fice.yml

        :alt: Linux build status

    .. image:: 

        :target: 

        :alt: Documentation in construction

:License:

    .. image:: https://img.shields.io/badge/license-GNU--LGPL--v3-green

        :target: https://github.com/EdiGlacUQ/fenics_ice/blob/main/COPYING

        :alt: GNU LGPL version 3

:Authors:

    See the `link`_ for a list of all contributors.

    .. _link: https://github.com/EdiGlacUQ/fenics_ice/people