Skip to main content

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/Slack-simpeg-4B0082.svg?logo=slack 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)

Installing

discretize is on conda-forge

conda install -c conda-forge discretize

discretize is on pypi

pip install discretize

To install from source

git clone https://github.com/simpeg/discretize.git
python setup.py 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}
}

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

discretize-0.7.3.tar.gz (781.7 kB view details)

Uploaded Source

Built Distributions

discretize-0.7.3-cp39-cp39-win_amd64.whl (659.6 kB view details)

Uploaded CPython 3.9 Windows x86-64

discretize-0.7.3-cp38-cp38-win_amd64.whl (665.2 kB view details)

Uploaded CPython 3.8 Windows x86-64

discretize-0.7.3-cp37-cp37m-win_amd64.whl (638.7 kB view details)

Uploaded CPython 3.7m Windows x86-64

discretize-0.7.3-cp36-cp36m-win_amd64.whl (638.0 kB view details)

Uploaded CPython 3.6m Windows x86-64

File details

Details for the file discretize-0.7.3.tar.gz.

File metadata

  • Download URL: discretize-0.7.3.tar.gz
  • Upload date:
  • Size: 781.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12

File hashes

Hashes for discretize-0.7.3.tar.gz
Algorithm Hash digest
SHA256 274696dc38b7b01b335ac8a44ff6f94eab0edf392e574f261da70cd9e2187adf
MD5 4b29670cc94499cb90afa6acd8c6c19e
BLAKE2b-256 dd32d043c1ec7e4db3c176a10fcc50eba0eae5992103d32c25c7cda08eba6fa0

See more details on using hashes here.

File details

Details for the file discretize-0.7.3-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: discretize-0.7.3-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 659.6 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10

File hashes

Hashes for discretize-0.7.3-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 42eb1d7118f5ca2fc7c77abb3448548474ee158fcaf6c57551cf4346c3484e33
MD5 64dee0635be320a06a1a1d3a4daa42bd
BLAKE2b-256 3402fc054127577d46e231005de9cd8577f4ad6a3b904ad041c299c61a36aac8

See more details on using hashes here.

File details

Details for the file discretize-0.7.3-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: discretize-0.7.3-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 665.2 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.10

File hashes

Hashes for discretize-0.7.3-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 2c27d4a0bda75426bd56ad4359d70f8c0fc0680f5f3a3511f7e2fc0294ad95ea
MD5 504859fecd0bf1ed56047f6d685a01f0
BLAKE2b-256 e2fdf15349e0e2371820e4dbada32480c0966c21d39ecec46a9db30a453c1e3b

See more details on using hashes here.

File details

Details for the file discretize-0.7.3-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: discretize-0.7.3-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 638.7 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.9

File hashes

Hashes for discretize-0.7.3-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 958ab2ceecbfa4d87308103beecc69274b9bf79b757d3bb8f5b8121a08f027e1
MD5 7dd87c9424c48c86962ab4157e3d1bb6
BLAKE2b-256 3651de6e95b1697f2df8528986731bd5f9e145dc93cabfc3f73490dbf4ce1a09

See more details on using hashes here.

File details

Details for the file discretize-0.7.3-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: discretize-0.7.3-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 638.0 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.8

File hashes

Hashes for discretize-0.7.3-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 a48d5e97759bacb94e8f2d9327fc4d4fa3909864c4bde3c5a29f1831b86ac945
MD5 baa8188fab27380d7d08551e8e855175
BLAKE2b-256 47cdd4e97b96604bcda31d6bf1230cd1a41d7b0bfb9afc84479b6d9fb4379ef1

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page