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AiiDA plugin for FANS, an FFT-based homogenization solver.

Project description

aiida-fans

PyPI Package Docs Status Build Status

This is a plugin for AiiDA that facilitates the use of FANS. FANS is an FFT-based homogenisation solver for microscale and multiphysics problems. It is an open-source project under active development at the Institute of Applied Mechanics, University of Stuttgart. This plugin aims to bring the full value of provenance tracking and database integration to the results produced by FANS.

The design goals of this plugin are primarily to provide as simplistic a user experience as is reasonably possible. Secondarily, more featureful additions will be made to extend the users' options for queryability and optimisation.

Upcoming

Please note: This plugin is currently in the planning stage of development, with substantial contributions coming soon.

Pre-launch

  • basic functionality capable of completing the example simulations presented by FANS with minimal database integration
  • documentation hosted on aiida-fans.readthedocs.io
  • documentation outline
  • publish package on PyPI

Post-launch

  • documentation expansion
  • input validation developed in cooperation with the FANS team
  • file sharing optimisations
  • greater database integration via output analysis/extraction

Installation

The plugin is currently unavailable via PyPI at this stage in development, but it is intended to be published upon an upcoming functional release.

The package can always be installed by cloning this repository and installing it locally like so...

$ pip install ./aiida-fans

You must also ensure that FANS, AiiDA, and their various dependencies are installed. Please consult the FANS repository and the AiiDA installation guide for more information.

Contributing

Development

  1. Branch off dev with a name appropriate for what you are working on (e.g. feat/myfeature or bug/badbug).
  2. Implement, commit, and push your changes.
  3. Open a Pull Request dev ← feat/myfeature, then merge and delete.

Release

  1. Open a Pull Request main ← dev, then squash and merge.
  2. Draft a new Release, named after the release version (e.g. v1.2.3).
  3. Create and assaign a new Tag, identically named.
  4. Generate release notes and publish.

Contact

You can contact ethan.shanahan@gmail.com with regard to this plugin specifically.

Project details


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Source Distribution

aiida_fans-0.2.1.tar.gz (1.1 MB view details)

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aiida_fans-0.2.1-py3-none-any.whl (12.7 kB view details)

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File metadata

  • Download URL: aiida_fans-0.2.1.tar.gz
  • Upload date:
  • Size: 1.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

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Provenance

The following attestation bundles were made for aiida_fans-0.2.1.tar.gz:

Publisher: release.yml on DataAnalyticsEngineering/AiiDA-FANS

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file aiida_fans-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: aiida_fans-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 12.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for aiida_fans-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 5e008b081f2a42d43562ebc1e68e3d1a6ba0c676a7f95da96715822aba5c2bf9
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BLAKE2b-256 c9cb29ae0e6797cffdb308eb2ec35f10b5a88487434911698d160661dcb715ec

See more details on using hashes here.

Provenance

The following attestation bundles were made for aiida_fans-0.2.1-py3-none-any.whl:

Publisher: release.yml on DataAnalyticsEngineering/AiiDA-FANS

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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