Skip to main content

A SEAMM plug-in for Thermal Conductivity

Project description

SEAMM Thermal Conductivity Plug-in

GitHub pull requests Build Status Code Coverage Code Quality Documentation Status PyPi VERSION

A SEAMM plug-in for Thermal Conductivity

Features

  • Please edit this section!

Acknowledgements

This package was created with the molssi-seamm/cookiecutter-seamm-plugin tool, which is based on the excellent Cookiecutter.

Developed by the Molecular Sciences Software Institute (MolSSI), which receives funding from the National Science Foundation under award CHE-2136142.

History

2023.5.6 – Bugfix
  • Fixed an error handling Nan’s and Inf’s that caused a crash

  • Added the predictions from the derivatives of the Helfand moments to the output to give a better feel for the quality of the results.

2023.5.5 – Improved analysis
  • Considerable improvements to the analysis, results now seem solid

  • Fixed issues with fitting the linear portion of the Helfand moments

  • Added plot of the slope from the Helfand moments, which is similar to the Green-Kubo integral.

  • Cleaned up both the output and graphs.

2023.4.24 – Initial working version
  • Initial tests seem to work but needs more thorough testing.

  • Needs documentation!

2023.4.18 (2023-04-18)
  • Plug-in created using the SEAMM plug-in cookiecutter.

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

thermal_conductivity_step-2023.5.6.tar.gz (313.3 kB view details)

Uploaded Source

Built Distribution

thermal_conductivity_step-2023.5.6-py2.py3-none-any.whl (25.2 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file thermal_conductivity_step-2023.5.6.tar.gz.

File metadata

File hashes

Hashes for thermal_conductivity_step-2023.5.6.tar.gz
Algorithm Hash digest
SHA256 a260896684fb9ab839e0946c527cf8737dfe7dc0b404c0c730964c98e8254dbe
MD5 b58534a8ed3d62eff5eae6b7c0ec07c5
BLAKE2b-256 55964348d00124f16c8293c3852b793fcb47f32dc753b40468fed741e9f443d2

See more details on using hashes here.

File details

Details for the file thermal_conductivity_step-2023.5.6-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for thermal_conductivity_step-2023.5.6-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 67c140d8fbc358ec287c0576924e617a49cea49020060fe0b2912b143ecaf80f
MD5 4133c6c43ab62918832d92c0e31d5fc0
BLAKE2b-256 e013e8e3fdec0c3cb8c68897347f8300acdc4f0af1ce933472fa7dea78157d14

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