D-dimensional Delaunay triangulations in Rust, inspired by CGAL.
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.
- Copy-able data types associated with vertices and cells (integers, floats, chars, custom enums)
- d-dimensional Delaunay triangulations
- d-dimensional Convex hulls
- Geometry quality metrics for simplices: radius ratio and normalized volume (dimension-agnostic)
- Serialization/Deserialization of all data structures to/from JSON
- Tested for 2-, 3-, 4-, and 5-dimensional triangulations
See CHANGELOG.md for details.
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
We welcome contributions! Here's a 30-second quickstart:
# Clone and setup
git clone https://github.com/acgetchell/delaunay.git
cd delaunay
# Setup development environment (installs tools, builds project)
cargo install just
just setup # Installs all development tools and dependencies
# Development workflow
just dev # Quick development cycle: format, lint, test
just quality # Comprehensive quality checks before pushing
just commit-check # Verify your changes will pass CI
just --list # See all available commandsTry the examples:
just examples # Run all examples
# Or run specific examples:
cargo run --release --example triangulation_3d_100_points
cargo run --release --example convex_hull_3d_100_pointsThe examples/ directory contains several demonstrations:
triangulation_3d_100_points: Complete 3D Delaunay triangulation with 100 random pointsconvex_hull_3d_100_points: 3D convex hull extraction and analysis with performance benchmarksinto_from_conversions: Demonstrates Into/From trait conversions and utilitiespoint_comparison_and_hashing: Demonstrates point comparison and hashing behaviormemory_analysis: Memory usage analysis for triangulations across dimensions with allocation trackingzero_allocation_iterator_demo: Performance comparison between allocation and zero-allocation iterators
For detailed documentation, sample output, and usage instructions for each example, see examples/README.md.
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
For a comprehensive list of academic references and bibliographic citations used throughout the library, see REFERENCES.md.
Portions of this library were developed with the assistance of these AI tools:
All code was reviewed and/or edited by the author.