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Discretization tools for finite volume and inverse problems

Project description

Discretize Logo

discretize

Latest PyPI version Latest conda-forge version MIT license Azure pipelines build status Coverage status https://zenodo.org/badge/DOI/10.5281/zenodo.596411.svg https://img.shields.io/discourse/users?server=http%3A%2F%2Fsimpeg.discourse.group%2F https://img.shields.io/badge/simpeg-purple?logo=mattermost&label=Mattermost https://img.shields.io/badge/Youtube%20channel-GeoSci.xyz-FF0000.svg?logo=youtube

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

https://raw.githubusercontent.com/simpeg/figures/master/finitevolume/cell-anatomy-tensor.png

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}
}

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