Skip to main content

Basix Python interface

Project description

Basix

Basix CI

Basix is a finite element definition and tabulation runtime library. Basix allows users to:

  • evaluate finite element basis functions and their derivatives at a set of points;
  • access geometric and topological information about reference cells;
  • apply push forward and pull back operations to map data between a reference cell and a physical cell;
  • permute and transform DOFs to allow higher-order elements to be use on arbitrary meshes; and
  • interpolate into a finite element space and between finite element spaces.

Basix includes a range of built-in elements, and also allows the user to define their own custom elements.

Basix is one of the components of FEniCSx, alongside UFL, FFCx, and DOLFINx.

Installing Basix

To install Basix:

pip install .

For advanced installation instructions see the detailed install instructions

Documentation

Documentation of Basix can be found at https://docs.fenicsproject.org/basix/main/.

Support

If you find a bug in Basix, you can report it on the GitHub issue tracker.

Questions about using Basix can be asked on the FEniCS discourse group.

Contributing

Information about how to contribute to Basix can be found here.

Supported elements

Interval

In Basix, the sub-entities of the reference interval are numbered as follows:

The numbering of a reference interval

The following elements are supported on an interval:

Triangle

In Basix, the sub-entities of the reference triangle are numbered as follows:

The numbering of a reference triangle

The following elements are supported on a triangle:

Quadrilateral

In Basix, the sub-entities of the reference quadrilateral are numbered as follows:

The numbering of a reference quadrilateral

The following elements are supported on a quadrilateral:

Tetrahedron

In Basix, the sub-entities of the reference tetrahedron are numbered as follows:

The numbering of a reference tetrahedron

The following elements are supported on a tetrahedron:

Hexahedron

In Basix, the sub-entities of the reference hexahedron are numbered as follows:

The numbering of a reference hexahedron

The following elements are supported on a hexahedron:

Prism

In Basix, the sub-entities of the reference prism are numbered as follows:

The numbering of a reference prism

The following elements are supported on a prism:

Pyramid

In Basix, the sub-entities of the reference pyramid are numbered as follows:

The numbering of a reference pyramid

The following elements are supported on a pyramid:

Project details


Download files

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

Source Distribution

fenics-basix-0.5.0.tar.gz (604.7 kB view details)

Uploaded Source

Built Distributions

fenics_basix-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (11.0 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

fenics_basix-0.5.0-cp310-cp310-macosx_10_9_x86_64.whl (664.1 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

fenics_basix-0.5.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (11.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

fenics_basix-0.5.0-cp39-cp39-macosx_10_9_x86_64.whl (664.2 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

fenics_basix-0.5.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (11.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

fenics_basix-0.5.0-cp38-cp38-macosx_10_9_x86_64.whl (664.1 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

fenics_basix-0.5.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (11.0 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

fenics_basix-0.5.0-cp37-cp37m-macosx_10_9_x86_64.whl (660.0 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file fenics-basix-0.5.0.tar.gz.

File metadata

  • Download URL: fenics-basix-0.5.0.tar.gz
  • Upload date:
  • Size: 604.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for fenics-basix-0.5.0.tar.gz
Algorithm Hash digest
SHA256 5dace846ebb769e14e70fe42c8d1648ab108e9f9ca6e4bd8559e564f569e7433
MD5 60d9f8e5ff4a3bae9486bf5e5ee4ae05
BLAKE2b-256 dc1ce84f268888ae85dd9f07f06bb1303c03d07dbd5b816795e6b80d3ed3012f

See more details on using hashes here.

File details

Details for the file fenics_basix-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for fenics_basix-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b2ed5baf1b11f25f0add5d94186db0c8f1598a21f869e3e62492db648125c3a3
MD5 86158a359902ffdddfa324f2990d2f3f
BLAKE2b-256 aa7f3ac76ba5d709b34ff3667ef13581ddbf7238ccacb7bf27e4b13d86124625

See more details on using hashes here.

File details

Details for the file fenics_basix-0.5.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for fenics_basix-0.5.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 75ec3945ba8be70a239a32d97e7491dbc850c49cedc1ae279c8ff9cf6d98cee9
MD5 d7607b739a6d9d37b6fead52a1760d54
BLAKE2b-256 a40fb5150b4c2c2f3118d9249f4b2459d88ff0ab91f6f820446b747bed3b5db4

See more details on using hashes here.

File details

Details for the file fenics_basix-0.5.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for fenics_basix-0.5.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 351b702b94a3e7398a7f169e6c2eae987b16fa7628fb4f7396536a294a46e15d
MD5 a6c72733b0be7eaacff9065c361acb50
BLAKE2b-256 46bbb5157bd2ad52825fb7c0c3d20858db13e043d091e65a6b11a11d122cde14

See more details on using hashes here.

File details

Details for the file fenics_basix-0.5.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for fenics_basix-0.5.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8b88dc4c40af16fc756d14bf0b78d03dbe827aa92e15d3d5189db4569eb9b86a
MD5 c11cccca571e7543428386576ee94f0b
BLAKE2b-256 610003da2ab1a057276323846c4e0dc5aaad8f2ba4b7334f8337e8b9d55b9637

See more details on using hashes here.

File details

Details for the file fenics_basix-0.5.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for fenics_basix-0.5.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c0c762306363e21009d3ede5da77ae8981b48a9c94e531c9d8025b92727acfcd
MD5 ab1a473c768ebb37a074f83775645f3d
BLAKE2b-256 277f6a3165fa6e2a7b2d871a171e8fcbc26b8cc1104816236dd1371b723ff21a

See more details on using hashes here.

File details

Details for the file fenics_basix-0.5.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for fenics_basix-0.5.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 bd88fe456e535d8ea70a4c9b53fee5c6d1ab2be419fee94c056854cc94d6638d
MD5 0ece1f2c20a4394eb1ffccf6403f80a8
BLAKE2b-256 0a1d889c8bc87feb56624d5e9f82feaa694a0cc4c1593e917690433db3bc3d83

See more details on using hashes here.

File details

Details for the file fenics_basix-0.5.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for fenics_basix-0.5.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1efd8665f40a0078d2f41ef2e45aab08e4bb1e8dc0fcf240643df68cb444b81d
MD5 8da40b59d6d488114084401de0dec4b8
BLAKE2b-256 26b503aaa089775c5bc49cb9327497663d11dddb27ed2329608b356138a7837f

See more details on using hashes here.

File details

Details for the file fenics_basix-0.5.0-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for fenics_basix-0.5.0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 10e4a14afdf17a71dcf3684c6941b48c823a8d40ae870cdf5b5592da067b7768
MD5 6783b7c1911c87262d1eef002b5ad9e3
BLAKE2b-256 ab94dc47deba0d400a04f52c84b7784b368b858f88c81a071c37747c3c7c5426

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