Efficient estimation of diffusion processes from molecular dynamics.
Project description
Pronunciation: kee-nee-see
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 repository so can be installed using pip or alternatively clone this repository 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 that outlines the different ways to help out.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file kinisi-1.1.1.tar.gz.
File metadata
- Download URL: kinisi-1.1.1.tar.gz
- Upload date:
- Size: 32.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 3fe9cb079eb95c8a187282e8c7485824c3fb60dce23d2d4ef6d7c9225ef5ea50 |
|
| MD5 | a6c5a46817eea1d66d6d3eae48ba0f14 |
|
| BLAKE2b-256 | d4cddea762f08730abda078c0306aecec40197fa25afccb670460bc66d7a6205 |
File details
Details for the file kinisi-1.1.1-py3-none-any.whl.
File metadata
- Download URL: kinisi-1.1.1-py3-none-any.whl
- Upload date:
- Size: 33.1 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 99888fe0f3ef79725ac93eeeec09f30a9d3b7acd929b7d19039d1616a6828274 |
|
| MD5 | ee1e193edf880ba3b95467dcfb613a0d |
|
| BLAKE2b-256 | 9627cda2fc37961b1dde56dfc45f2a2395ee1d204c4e0ec967ecfee40a7d3df7 |
