reaxkit 2.0.0

A toolkit for parsing, analyzing, and visualizing ReaxFF simulation data.

ReaxKit

ReaxKit is a modular, extensible Python toolkit for pre‑processing, post‑processing, and analysis of ReaxFF molecular dynamics simulations. It provides a clean separation between file parsing, analysis routines, and reproducible workflows, with Python APIs, a CLI interface, and a Dash-based GUI.

ReaxKit is designed for researchers who want a transparent, scriptable bridge between raw ReaxFF data and quantitative, publication‑ready results.

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Key Capabilities

Engine

• Shared engine abstractions for consistent parsing and generating input/output files across 3 different ReaxFF simulation engines, namely ams, lammps, reaxff
• Example IO and generator modules under the reaxff engine:
  • ReaxFF input and output files such as xmolout, fort.7, fort.13, molfra, and more
  • Input generators for control, geo, eregime, tregime, and related files

Analysis

• Engine-agnostic analyzers built on ReaxKit's domain data models
• Analyzer tasks organized around separated request, result, and task objects
• Analysis components separated from engine IO so the same computations can be reused across scripts, workflows, web UI, and presentation modules

Workflows

• Reproducible workflows organized by data handling, file tools, meta orchestration, presentation, and study design
• Automation paths for common ReaxFF pre-processing, analysis, post-processing, and presentation tasks

Web UI

• Dash-based interface components for interactive ReaxFF data inspection
• Backend, UI, and presentation layers for browser-driven workflows

Presentation

• Publication-ready plotting utilities:
  • 2D plots, dual-axis plots, tornado plots, 3D scatter, and heatmaps
• Video generators

Utilities

• Shared data, media, and numerical utilities
• Common infrastructure used by analysis, workflows, web UI, and presentation modules

See the full documentation (API reference, tutorials, examples) on ReaxKit Site.

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Project Layout

src/reaxkit/
├── analysis/        # Engine-agnostic analysis tasks
├── cli/             # Command-line entry points
├── core/            # Registries and shared core infrastructure
├── data/            # Packaged reference data and resources
├── domain/          # Central data models, requests, and results
├── engine/          # IO handlers and input generators
├── help/            # Introspection and help system
├── presentation/    # Plotting, active-site views, and media presentation
├── utils/           # Shared data, media, and numerical utilities
├── webui/           # Dash/web interface backend, UI, and presentation layers
└── workflows/       # Workflow orchestration and automation

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Testing

Run unit tests with:

pytest -s tests/

to test the package and get the timing for their execution.

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Citation

If you use ReaxKit in your work, please cite:

Dinani, A. M., van Duin, A., Shin, Y. K., & Sepehrinezhad, A. (2025).
ReaxKit: A modular Python toolkit for ReaxFF simulation analysis.
Zenodo. https://doi.org/10.5281/zenodo.18485384

Source code: https://github.com/ali-m-dinani/reaxkit

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Future Directions

• Implement machine learning-based surrogate models for rapid property prediction and active-site identification.
• Develop a plugin system for user-contributed analysis routines and visualization components.
• Integrate with Jupyter notebooks for interactive analysis and visualization.

If you have any feature request, you can submit it through the ReaxKit's GitHub page, or directly sending an email to [e-mail].

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Additional resources:

• AUTHORS.md — Full credits and acknowledgments.
• LICENSE — Full license terms under the MIT License