ReaxKit Documentation

ReaxKit is a Python toolkit for parsing, analyzing, and visualizing ReaxFF simulation data.

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Getting started

• Architecture Overview - Overview of different codes, how ReaxKit works, and how it stores the results
• Installation - Install ReaxKit and dependencies
• Quickstart - First end-to-end CLI run
• Tutorials - Step-by-step workflows
• Examples - Runnable scripts and sample data

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Core concepts

As you will read more in detail in Architecture Overview, ReaxKit uses a layered model: - Engine I/O + generators for data/file handling - Analysis tasks for computations - Workflows for CLI orchestration and presentation

API entry points:

• Analysis API
• Engine API
• Utils API
• Workflows API

Example current commands:

1. reaxkit timeseries --field trajectory[1].z --xaxis time
2. reaxkit get_msd --atom-types O --xaxis time
3. reaxkit gen_eregime --type sin --iteration-step 500 ...
4. reaxkit gen-plot --type single --file table.csv --xaxis c1 --yaxis c2

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Reference material

One of the engines supported by ReaxKit is ReaxFF (i.e., ReaxFF standalone). This engine saves the data across multiple files, and needs specific input files. If you are not familiar with ReaxFF data structure and file semantics, it is recommended to read the following resources to understand the file semantics and context:

• ReaxFF Reference

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Developer resources

If you are interested in contributing to ReaxKit, or want to understand the codebase and design decisions, check out the following resources:

• File templates
• Contributing
• Rules and conventions

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If you are not sure where to begin, start from Architecture Overview.