Skip to main content

Python tools for constructing meshes and geometry matrices used in tomography problems

Project description

Tokamesh

Documentation Status

Tokamesh is a Python package which provides tools for constructing meshes and geometry matrices used in tomographic inversion problems in toroidal fusion-energy devices such as MAST-U.

Features

  • Advanced geometry matrix calculation
    • Tokamesh constructs geometry matrices using barycentric linear-interpolation rather than the typical zeroth-order interpolation. This allows for accurate tomographic inversions with a significantly lower number of basis functions. geo matrix example

  • Tomography-optimised mesh construction
    • Tokamesh provides tools to create meshes that are optimised for tomography problems, e.g. local-refinement of triangles to increase mesh density in areas where it is needed without greatly increasing the size of the mesh. Example mesh

Jupyter notebook demos

Jupyter notebooks are available which demonstrate mesh construction and geometry matrix calculation.

Installation

Tokamesh is available from PyPI, so can be easily installed using pip as follows:

pip install tokamesh

Documentation

The package documentation is available at tokamesh.readthedocs.io.

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

tokamesh-0.5.4.tar.gz (579.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tokamesh-0.5.4-py3-none-any.whl (38.2 kB view details)

Uploaded Python 3

File details

Details for the file tokamesh-0.5.4.tar.gz.

File metadata

  • Download URL: tokamesh-0.5.4.tar.gz
  • Upload date:
  • Size: 579.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for tokamesh-0.5.4.tar.gz
Algorithm Hash digest
SHA256 f262c97d7bbec8069978070f11c5e67f99228a1ba4c94979de5d72c3b5c40a02
MD5 3cd22855c346776671e3df52f8949183
BLAKE2b-256 4b17d3aa1d145eeb3d35f898be70d11a5cdde021c2362135ab5400afe217ac93

See more details on using hashes here.

File details

Details for the file tokamesh-0.5.4-py3-none-any.whl.

File metadata

  • Download URL: tokamesh-0.5.4-py3-none-any.whl
  • Upload date:
  • Size: 38.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for tokamesh-0.5.4-py3-none-any.whl
Algorithm Hash digest
SHA256 ce3b149a143461b79c7d074a2a2ba7861030788a3cb1e7656f3f7dcd7f3c1820
MD5 fdfda8ad50372a8f755bdca0a01554b2
BLAKE2b-256 2d8796ea4d99bb00253e2f6810419501f157f3762160cb499e703b6715c7e418

See more details on using hashes here.

Supported by

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