semvec/pypi-packages huggingface dataset:
ions 0.5.1
A python library for studying ionic conductors
License: MIT
Keywords: Li-ion, barrier, migration, percolation, ion, ions, crystal, bvse, bvel, NEB

![ions_logo](https://raw.githubusercontent.com/dembart/ions/main/ions_logo.png)



## Contents
- [About](#about)
- [Installation](#installation)
- [Minimal usage example](#minimal-usage-example)
- [Notebooks](#notebooks)
- [How to cite](#how-to-cite)


### About

ions is a python library made for studying crystalline ionic conductors

### Installation

```bash
pip install ions
```

or 

```bash
git clone https://github.com/dembart/ions
cd ions
pip install .
```

### Minimal usage examples:


> Note: The last library update was not systematically tested. Errors are expected. Be careful.


#### Inequivalent ionic jumps (edges) forming a percolating network


```python
from ase.io import read
from ions import Percolator

file = '/Users/artemdembitskiy/Downloads/LiFePO4.cif'
atoms = read(file)  

pl = Percolator(atoms, mobile_specie='Li', upper_bound=5.0)

bottleneck_radius = 0.5 
mincut, maxdim = pl.mincut_maxdim(bottleneck_radius)
print(f'Maximum percolation dimensionality: {maxdim}')
print(f'Jump distance cutoff: {mincut} angstrom', '\n')

edges = pl.unique_edges(mincut, bottleneck_radius, method = 'naive')
print(f'Inequivalent edges forming {maxdim}D percolating network:')
print(edges)
```
    Maximum percolation dimensionality: 2
    Jump distance cutoff: 4.755859375 angstrom 
    
    Inequivalent edges forming 2D percolating network:
    [[ 0  3  0 -1  0]
     [ 0  0 -1  0  0]]

#### Notebooks

- [Percolations barriers from nudged elastic band (NEB) calculations using universal machine learning interatomic potentials (UMLIPS)](notebooks/neb_umlip.ipynb)
- [Available data](notebooks/available_data.ipynb)

#### How to cite

If you use the library consider citing the [following paper](https://www.nature.com/articles/s41524-025-01571-z#code-availability):

```
@article{dembitskiy2025benchmarking,
  title={Benchmarking machine learning models for predicting lithium ion migration},
  author={Dembitskiy, Artem D and Humonen, Innokentiy S and Eremin, Roman A and Aksyonov, Dmitry A and Fedotov, Stanislav S and Budennyy, Semen A},
  journal={npj Computational Materials},
  volume={11},
  number={1},
  pages={131},
  year={2025},
  publisher={Nature Publishing Group UK London}
}
```
twc-cli 2.15.1
Timeweb Cloud Command Line Interface.
License: MIT
Requires Python: <4.0.0,>=3.8.19

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  <img alt="TWC CLI" src="https://ec650031-twc-cli.s3.timeweb.cloud/light.png">
</picture>

Timeweb Cloud Command Line Interface and simple SDK 💫

* [Руководство пользователя](https://github.com/timeweb-cloud/twc/blob/master/docs/ru/README.md) 🇷🇺
* [Command Line Interface (CLI) Reference](https://github.com/timeweb-cloud/twc/blob/master/docs/ru/CLI_REFERENCE.md)

# Installation

From PyPI registry via pip:

```
pip install twc-cli
```

Using [pipx](https://pipx.pypa.io/stable/):

```
pipx install twc-cli
```

Or install [zippap](https://docs.python.org/3/library/zipapp.html) in your PATH.
Look for prebuilt `.pyz` archives on [releases page](https://github.com/timeweb-cloud/twc/releases/latest).

# Getting started

Get Timeweb Cloud [access token](https://timeweb.cloud/my/api-keys) and
configure **twc** with command:

```
twc config
```

Enter your access token and hit `Enter`.

Configuration done! Let's use:

```
twc --help
```

# Shell completion

To install completion script run:

```
twc --install-completion
```

**twc** automatically detect your shell. Supported: Bash, Zsh, Fish, PowerShell.