graphatoms 1.1.3

The Chemical Core Class for Graph Theory Analysis.

graphatoms

The Chemical Core Class for Graph Theory Analysis & Graph Neural Network.

Overview

The graphatoms is a Python library designed for chemical graph theory analysis and graph neural network applications. It provides core classes for representing chemical systems and reactions with graph-based data structures.

Features

• Graph-based Chemical System Representation: Represent chemical systems, clusters, and gas molecules using graph theory
• Reaction Modeling: Support for reaction classes, KMC (Kinetic Monte Carlo) events, and MC (Monte Carlo) moves
• Geometry Operations: Bond lists, distance calculations, neighbor lists, rotations, and sampling
• Data Storage: Support for HDF5 and SQLite databases for efficient data persistence
• Dataclasses: Pydantic-based data models for type-safe data handling

Module Structure

src/graphatoms/
├── dataclasses/     # Pydantic-based data models
├── geometry/        # Geometric operations
├── reaction/        # Reaction classes and KMC events
├── system/          # Core system classes (System, Cluster, Gas)
└── utils/           # Utility functions

Requirements

• Python >= 3.10
• ase
• pymatgen > 2023.6
• rdkit >= 2025
• scikit-learn >= 1.5
• pyarrow
• igraph >= 0.11
• h5py >= 3.16
• hydra-core
• numpydantic
• pydantic >= 2.11

Installation

pip install graphatoms

Development

For development setup with pixi:

pixi install
pixi run test

License

GPL-3.0-or-later

Authors

• LiuGaoyong ([e-mail])

Links

• Homepage: https://github.com/LiuGaoyong/GraphAtoms
• Repository: https://github.com/LiuGaoyong/GraphAtoms
• Issues: https://github.com/LiuGaoyong/GraphAtoms/issues/