Skip to main content

Discretization tools for finite volume and inverse problems

Project description

Latest PyPI version MIT license Travis CI build status Coverage status codacy status

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 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-0.3.0.tar.gz (549.8 kB view details)

Uploaded Source

Built Distributions

discretize-0.3.0-py3.6-linux-x86_64.egg (2.5 MB view details)

Uploaded Source

discretize-0.3.0-py2.7-linux-x86_64.egg (2.2 MB view details)

Uploaded Source

discretize-0.3.0-cp36-cp36m-win_amd64.whl (465.8 kB view details)

Uploaded CPython 3.6m Windows x86-64

discretize-0.3.0-cp36-cp36m-win32.whl (373.3 kB view details)

Uploaded CPython 3.6m Windows x86

discretize-0.3.0-cp35-cp35m-win_amd64.whl (460.3 kB view details)

Uploaded CPython 3.5m Windows x86-64

discretize-0.3.0-cp35-cp35m-win32.whl (368.5 kB view details)

Uploaded CPython 3.5m Windows x86

discretize-0.3.0-cp27-cp27m-win_amd64.whl (501.6 kB view details)

Uploaded CPython 2.7m Windows x86-64

discretize-0.3.0-cp27-cp27m-win32.whl (401.4 kB view details)

Uploaded CPython 2.7m Windows x86

File details

Details for the file discretize-0.3.0.tar.gz.

File metadata

  • Download URL: discretize-0.3.0.tar.gz
  • Upload date:
  • Size: 549.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for discretize-0.3.0.tar.gz
Algorithm Hash digest
SHA256 3bb0f08837890801c883b3bc098fcbc85d39554f91b5d0353f23c1e2f8ae5bab
MD5 4038bc41fab323464303dd09baaba2cf
BLAKE2b-256 fb57e1e5e4855f687a9a58ffd2776fbaca10f560bca46fba828ceb90538f0142

See more details on using hashes here.

Provenance

File details

Details for the file discretize-0.3.0-py3.6-linux-x86_64.egg.

File metadata

File hashes

Hashes for discretize-0.3.0-py3.6-linux-x86_64.egg
Algorithm Hash digest
SHA256 22cf1081389a1a42fbf31bc89cddbb4545b7950c6dc33acaf99553ee3e698bc2
MD5 0aacedac768dfc16ad83380f2a7bcc5d
BLAKE2b-256 89c8315320d974cff53a6b1d279ed3758008cdafaa95b4f3fcdd3d07bcc38e9f

See more details on using hashes here.

Provenance

File details

Details for the file discretize-0.3.0-py2.7-linux-x86_64.egg.

File metadata

File hashes

Hashes for discretize-0.3.0-py2.7-linux-x86_64.egg
Algorithm Hash digest
SHA256 19d7c52e69c8a232121e070cae323bac762dc67329309d64e0aedaa2c4008f0c
MD5 e760d0509a18087bfdc07b4cb28226d5
BLAKE2b-256 ae3b1be0f846a70af6b1b1a3b0d82b43d676910a6a0d67d9fafde3605705ea4e

See more details on using hashes here.

Provenance

File details

Details for the file discretize-0.3.0-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for discretize-0.3.0-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 06467fe7ec76aa36ee062651486b7102f299b1acb4f3f1c6afc7ca26c62c414e
MD5 a7d65d36bc105039fec8978dc5d8c4f2
BLAKE2b-256 bbe8d0fed5b466209ac06520a852d217e8a93e4ccefe8415329be790d808b953

See more details on using hashes here.

Provenance

File details

Details for the file discretize-0.3.0-cp36-cp36m-win32.whl.

File metadata

File hashes

Hashes for discretize-0.3.0-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 93c4cb04ba9ee0f376524737afffc2ddcd519477f95b7afd5a48245cde2140ba
MD5 45146551d5da504f049c43b4490bfaf2
BLAKE2b-256 0bb14bfa3422a132eb0ca92dfa5df3b1bcb1a21b49d0e690e59164a300730f1f

See more details on using hashes here.

Provenance

File details

Details for the file discretize-0.3.0-cp35-cp35m-win_amd64.whl.

File metadata

File hashes

Hashes for discretize-0.3.0-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 77005c801ae48ff6bc92f868a07a5bd31b19e2729e4555901652132c0b286200
MD5 c4d70a589bb4795b3bf735d56f896225
BLAKE2b-256 fe1ab9e0713a11a3da16ad9c6966e926c8fd4c9d1acdeb6fab35843e4ea27ece

See more details on using hashes here.

Provenance

File details

Details for the file discretize-0.3.0-cp35-cp35m-win32.whl.

File metadata

File hashes

Hashes for discretize-0.3.0-cp35-cp35m-win32.whl
Algorithm Hash digest
SHA256 6adb36af80dfe9a8b0b548216065251e5738eec135c2bddf279434a500465ce6
MD5 99c1bc943690aab162650d504f66ae7c
BLAKE2b-256 4e763d03b59a414114cbaa4d22609a413bb0bfd355f5f9bd93199988e65d1d53

See more details on using hashes here.

Provenance

File details

Details for the file discretize-0.3.0-cp27-cp27m-win_amd64.whl.

File metadata

File hashes

Hashes for discretize-0.3.0-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 bf19bc8b31c19153883a401af6f1dc5e57071109a28a71029208006cc383c257
MD5 4f0eae9fe34889d52ae20de04adee821
BLAKE2b-256 9a9fc4899ca3c8cdb6c152ac9e4f0c556491e574725352b9b60f591e008c309b

See more details on using hashes here.

Provenance

File details

Details for the file discretize-0.3.0-cp27-cp27m-win32.whl.

File metadata

File hashes

Hashes for discretize-0.3.0-cp27-cp27m-win32.whl
Algorithm Hash digest
SHA256 a4d7f02f24b75ccf87baa6cf74fc0c9ac7ab2dd927c6eebac978ca8cf7fb6d43
MD5 e58dcf82a97f96d04ac9a1ffab0a7cd5
BLAKE2b-256 982dba67e8d4881075bfdb3ba160434b7bdfb28dd3f599cb273c0328b4bfb94e

See more details on using hashes here.

Provenance

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