Metadata-Version: 2.1
Name: quasigraph
Version: 0.1.7
Summary: quasigraph: Chemical and Geometric Descriptor Toolkit for Machine Learning Models.
Project-URL: Homepage, https://github.com/leseixas/quasigraph
Author-email: Leandro Seixas <leandro.seixas@mackenzie.br>
License-File: LICENSE.txt
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.8
Requires-Dist: acat
Requires-Dist: ase
Requires-Dist: mendeleev
Requires-Dist: numpy
Requires-Dist: pandas
Description-Content-Type: text/markdown

<p align="center">
<img src="https://raw.githubusercontent.com/leseixas/quasigraph/master/logo.png" style="height: 120px"></p>

[![PyPI - License](https://img.shields.io/pypi/l/quasigraph?color=green&style=for-the-badge)](LICENSE.txt)    [![PyPI](https://img.shields.io/pypi/v/quasigraph?color=red&label=version&style=for-the-badge)](https://pypi.org/project/quasigraph/) 

**Quasigraph** is an open-source toolkit designed for generating chemical and geometric descriptors to be used in machine learning models.

## Installation

The easiest method to install quasigraph is by utilizing pip:
```bash
$ pip install quasigraph
```

## Getting started

```python
from ase.build import molecule
from quasigraph import QuasiGraph

# Initialize an Atoms object for water using ASE's molecule function
atoms = molecule('H2O')

# Instantiate a QuasiGraph object containing chemical and coordination numbers
qgr = QuasiGraph(atoms)

# Convert the QuasiGraph object into a pandas DataFrame
df = qgr.get_dataframe()

# Convert the QuasiGraph object into a vector
vector = qgr.get_vector()

```

## License

This is an open source code under [MIT License](LICENSE.txt).

