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https://github.com/arm61/kinisi

A Python package for estimating diffusion properties from molecular dynamics simulations.

https://github.com/arm61/kinisi

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
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    DOI references
  • ✓
    Academic publication links
    Links to: joss.theoj.org
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    Academic email domains
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    Institutional organization owner
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (11.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

A Python package for estimating diffusion properties from molecular dynamics simulations.

Basic Info
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Fork of Harry-Rich/kinisi
Created over 1 year ago · Last pushed over 1 year ago

https://github.com/arm61/kinisi/blob/master/ 


  
  
  The kinisi logo


Pronunciation: *kee-nee-see*

[![JOSS Status](https://joss.theoj.org/papers/1ae102ffb6b3c63b04c002976440815d/status.svg)](https://joss.theoj.org/papers/1ae102ffb6b3c63b04c002976440815d)
[![Test Coverage](https://api.codeclimate.com/v1/badges/3e64239fb6cb6c837b62/test_coverage)](https://codeclimate.com/github/bjmorgan/kinisi/test_coverage)
[![Documentation Status](https://readthedocs.org/projects/kinisi/badge/?version=latest)](https://kinisi.readthedocs.io/en/latest/?badge=latest)
[![PyPI version](https://badge.fury.io/py/kinisi.svg)](https://badge.fury.io/py/kinisi)

`kinisi` is an open-source package focussed on accurately quantifying the uncertainty in atomic and molecular displacements, and using this to more completely understand diffusion in materials.

## Installation

`kinisi` is available from the [PyPI](https://pypi.org/project/kinisi/) repository so can be installed using `pip` or alternatively `clone` [this repository](https://github.com/bjmorgan/kinisi) and install the latest development build with the commands below.

```
pip install .
```

## Contributing

If you would like to contribute to `kinisi`, have a look at the [CONTRIBUTING.md](https://github.com/bjmorgan/kinisi/blob/master/CONTRIBUTING.md) that outlines the different ways to help out.

Owner

  • Name: Andrew McCluskey
  • Login: arm61
  • Kind: user
  • Location: Copenhagen
  • Company: European Spallation Source

instrument data scientist @essneutron (he/him)

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