Metadata-Version: 2.1
Name: kperm
Version: 0.1.1
Summary: Toolkit for Analysis of Permeation Cycles in Potassium Channels
License: GPL-3.0
Author: Chun Kei (Tom) Lam
Author-email: chun-kei.lam@mpinat.mpg.de
Requires-Python: >=3.8,<3.12
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: MDAnalysis (>=2.4.3,<3.0.0)
Requires-Dist: jupyter (>=1.0.0,<2.0.0)
Requires-Dist: matplotlib (>=3.7.1,<4.0.0)
Requires-Dist: networkx (>=3.1,<4.0)
Requires-Dist: numpy (>=1.24.3,<2.0.0)
Requires-Dist: pandas (>=2.0.1,<3.0.0)
Requires-Dist: scipy (>=1.10.1,<2.0.0)
Description-Content-Type: text/markdown

# KPerm - Toolkit for Analysis of Permeation Cycles in Potassium Channels


[![License](https://img.shields.io/github/license/deGrootLab/KPerm)](https://www.gnu.org/licenses/gpl-3.0.en.html) [![DOI](https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.3c00061-purple)](https://pubs.acs.org/doi/10.1021/acs.jctc.3c00061)

This package allows you to identify permeation cycles in potassium channels from molecular dynamics (MD) simulation trajectories.

## Conda
You are recommended to install KPerm in a conda environment. If you have installed [Anaconda](https://www.anaconda.com/), create a new environment by running:

```bash
conda create -n kperm python=3.11
```

Once the environment is set up, run:
```bash
conda activate kperm
```
## Installation
Tested with Python 3.11, MDAnalysis 2.4.2, and Numpy 1.24.1.
```bash
git clone https://github.com/tomcklam/KPerm
cd KPerm
pip install .
# you may need to add the kernel
# ipython kernel install --name "kperm" --user
```

You can now try our tutorial (tutorials/charge-scaling/charge-scaling.ipynb).

