delaunay

D-dimensional Delaunay triangulations in Rust, inspired by CGAL.

📐 Introduction

This library implements d-dimensional Delaunay triangulations in Rust. It is inspired by CGAL, which is a C++ library for computational geometry, and Spade, a Rust library that implements 2D Delaunay triangulations, Constrained Delaunay triangulations, and Voronoi diagrams. The goal of this library is to provide a lightweight alternative to CGAL for the Rust ecosystem.

✨ Features

• Arbitrary data types associated with vertices and cells
• d-dimensional Delaunay triangulations
• d-dimensional Convex hulls
• Serialization/Deserialization of all data structures to/from JSON
• Tested for 2-, 3-, 4-, and 5-dimensional triangulations

See CHANGELOG.md for details.

🚧 Project History

This crate was originally maintained at https://github.com/oovm/shape-rs through version 0.1.0. The original implementation provided basic Delaunay triangulation functionality.

Starting with version 0.3.4, maintenance transferred to this repository, which hosts a completely rewritten d-dimensional implementation focused on computational geometry research applications.

• 📚 Docs for old versions (≤ 0.1.0): https://docs.rs/delaunay/0.1.0/delaunay/
• 📚 Docs for current version (≥ 0.3.4): https://docs.rs/delaunay

🤝 How to Contribute

We welcome contributions! Here's a 30-second quickstart:

# Clone and setup
git clone https://github.com/acgetchell/delaunay.git
cd delaunay

# Build and test
cargo build
cargo test

# Format and lint
cargo fmt --all
cargo clippy --all-targets --all-features

# Run examples
./scripts/run_all_examples.sh

# Run a specific example
cargo run --example triangulation_3d_50_points
cargo run --example convex_hull_3d_50_points
cargo run --example into_from_conversions
cargo run --example point_comparison_and_hashing

📋 Examples

The examples/ directory contains several demonstrations:

• triangulation_3d_50_points: Complete 3D Delaunay triangulation with 50 random points
• convex_hull_3d_50_points: 3D convex hull extraction and analysis with performance benchmarks
• into_from_conversions: Demonstrates Into/From trait conversions and utilities
• point_comparison_and_hashing: Demonstrates point comparison and hashing behavior

For comprehensive guidelines on development environment setup, testing, benchmarking, performance analysis, and development workflow, please see CONTRIBUTING.md.

This includes information about:

• Building and testing the library
• Running benchmarks and performance analysis
• Code style and standards
• Submitting changes and pull requests
• Project structure and development tools

📚 References

For a comprehensive list of academic references and bibliographic citations used throughout the library, see REFERENCES.md.