Discretization tools for finite volume and inverse problems
Project description
discretize
discretize - A python package for finite volume discretization.
The vision is to create a package for finite volume simulation with a focus on large scale inverse problems. This package has the following features:
modular with respect to the spacial discretization
built with the inverse problem in mind
supports 1D, 2D and 3D problems
access to sparse matrix operators
access to derivatives to mesh variables
Currently, discretize supports:
Tensor Meshes (1D, 2D and 3D)
Cylindrically Symmetric Meshes
QuadTree and OcTree Meshes (2D and 3D)
Logically Rectangular Meshes (2D and 3D)
Triangular (2D) and Tetrahedral (3D) Meshes
Installing
discretize is on conda-forge, and is the recommended installation method.
conda install -c conda-forge discretize
Prebuilt wheels of discretize are on pypi for most platforms
pip install discretize
To install from source, note this requires a c++ compiler supporting the c++17 standard.
git clone https://github.com/simpeg/discretize.git
cd discretize
pip install .
Citing discretize
Please cite the SimPEG paper when using discretize in your work:
Cockett, R., Kang, S., Heagy, L. J., Pidlisecky, A., & Oldenburg, D. W. (2015). SimPEG: An open source framework for simulation and gradient based parameter estimation in geophysical applications. Computers & Geosciences.
BibTex:
@article{cockett2015simpeg,
title={SimPEG: An open source framework for simulation and gradient based parameter estimation in geophysical applications},
author={Cockett, Rowan and Kang, Seogi and Heagy, Lindsey J and Pidlisecky, Adam and Oldenburg, Douglas W},
journal={Computers \& Geosciences},
year={2015},
publisher={Elsevier}
}
Links
Website: http://simpeg.xyz
Documentation: http://discretize.simpeg.xyz
Code: https://github.com/simpeg/discretize
Tests: https://travis-ci.org/simpeg/discretize
Bugs & Issues: https://github.com/simpeg/discretize/issues
Questions: http://simpeg.discourse.group/
Project details
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