delaunator
An incredibly fast JavaScript library for Delaunay triangulation of 2D points
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A Javascript implementation of Fortune's algorithm to compute Voronoi cells
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Quick Overview
Delaunator is a fast and lightweight JavaScript library for Delaunay triangulation of 2D points. It efficiently computes triangulations for large sets of points, making it suitable for various applications such as computational geometry, computer graphics, and geographic information systems.
Pros
- Extremely fast performance, especially for large datasets
- Lightweight with no dependencies
- Works in both Node.js and browser environments
- Well-documented API with clear usage instructions
Cons
- Limited to 2D point sets only
- Does not provide advanced features like constrained triangulation
- No built-in visualization tools
- Requires additional processing for certain applications (e.g., Voronoi diagrams)
Code Examples
Creating a Delaunay triangulation:
import Delaunator from 'delaunator';
const points = [[0, 0], [1, 0], [1, 1], [0, 1], [0.5, 0.5]];
const delaunay = new Delaunator(points.flat());
Iterating through triangles:
for (let i = 0; i < delaunay.triangles.length; i += 3) {
const triangle = [
delaunay.triangles[i],
delaunay.triangles[i + 1],
delaunay.triangles[i + 2]
];
console.log('Triangle:', triangle);
}
Finding adjacent triangles:
function getAdjacentTriangles(delaunay, triangleIndex) {
return [
delaunay.halfedges[triangleIndex * 3],
delaunay.halfedges[triangleIndex * 3 + 1],
delaunay.halfedges[triangleIndex * 3 + 2]
].map(h => Math.floor(h / 3));
}
const adjacentTriangles = getAdjacentTriangles(delaunay, 0);
console.log('Adjacent triangles:', adjacentTriangles);
Getting Started
To use Delaunator in your project, follow these steps:
-
Install the library:
npm install delaunator
-
Import and use in your JavaScript code:
import Delaunator from 'delaunator'; const points = [[0, 0], [1, 0], [1, 1], [0, 1], [0.5, 0.5]]; const delaunay = new Delaunator(points.flat()); console.log('Triangles:', delaunay.triangles); console.log('Halfedges:', delaunay.halfedges);
This will create a Delaunay triangulation for the given points and output the resulting triangles and halfedges.
Competitor Comparisons
A Javascript implementation of Fortune's algorithm to compute Voronoi cells
Pros of Javascript-Voronoi
- Implements full Voronoi diagram computation, not just Delaunay triangulation
- Provides more advanced features like edge clipping and relaxation
- Has been around longer, potentially more stable and well-tested
Cons of Javascript-Voronoi
- Less actively maintained (last update in 2013)
- Slower performance for large datasets compared to Delaunator
- More complex API, potentially harder to integrate into projects
Code Comparison
Javascript-Voronoi:
var voronoi = new Voronoi();
var bbox = {xl: 0, xr: 800, yt: 0, yb: 600};
var sites = [{x: 200, y: 200}, {x: 50, y: 250}, {x: 400, y: 100}];
var diagram = voronoi.compute(sites, bbox);
Delaunator:
const points = [[200, 200], [50, 250], [400, 100]];
const delaunay = Delaunator.from(points);
const triangles = delaunay.triangles;
The code snippets demonstrate the basic usage of both libraries. Javascript-Voronoi requires more setup but provides a complete Voronoi diagram, while Delaunator offers a simpler API focused on Delaunay triangulation. Delaunator's approach is more performant but less feature-rich compared to Javascript-Voronoi.
The fastest and smallest JavaScript polygon triangulation library for your WebGL apps
Pros of Earcut
- Specialized for polygon triangulation, optimized for this specific use case
- Supports holes in polygons, making it versatile for complex shapes
- Extremely fast performance for polygon triangulation tasks
Cons of Earcut
- Limited to 2D polygon triangulation only
- May produce less optimal triangulations for certain complex shapes
- Requires pre-processing of input data for non-trivial polygons
Code Comparison
Earcut:
const triangles = earcut([10,0, 0,50, 60,60, 70,10]);
Delaunator:
const points = [[10,0], [0,50], [60,60], [70,10]];
const delaunay = Delaunator.from(points);
Key Differences
- Earcut is specifically designed for polygon triangulation, while Delaunator is a more general-purpose Delaunay triangulation library
- Delaunator works with point sets in any dimension, whereas Earcut is limited to 2D polygons
- Earcut directly outputs triangle indices, while Delaunator provides a Delaunay triangulation structure with additional features
Use Cases
- Choose Earcut for efficient 2D polygon triangulation, especially with holes
- Opt for Delaunator for point set triangulation, Voronoi diagram generation, or when working in higher dimensions
Both libraries are maintained by Mapbox and offer high-performance triangulation solutions, but they cater to different specific needs within the realm of computational geometry.
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Delaunator

An incredibly fast and robust JavaScript library for Delaunay triangulation of 2D points.

Projects based on Delaunator
- d3-delaunay for Voronoi diagrams, search, traversal and rendering (a part of D3).
- d3-geo-voronoi for Delaunay triangulations and Voronoi diagrams on a sphere (e.g. for geographic locations).
Example
const coords = [377,479, 453,434, 326,387, 444,359, 511,389,
586,429, 470,315, 622,493, 627,367, 570,314];
const delaunay = new Delaunator(coords);
console.log(delaunay.triangles);
// [4,3,1, 4,6,3, 1,5,4, 4,9,6, 2,0,1, 1,7,5,
// 5,9,4, 6,2,3, 3,2,1, 5,8,9, 0,7,1, 5,7,8]

Install
Install with NPM (npm install delaunator
) or Yarn (yarn add delaunator
), then import as an ES module:
import Delaunator from 'delaunator';
To use as a module in a browser:
<script type="module">
import Delaunator from 'https://cdn.skypack.dev/delaunator@5.0.0';
</script>
Or use a browser UMD build that exposes a Delaunator
global variable:
<script src="https://unpkg.com/delaunator@5.0.0/delaunator.min.js"></script>
API Reference
new Delaunator(coords)
Constructs a delaunay triangulation object given an array of point coordinates of the form:
[x0, y0, x1, y1, ...]
(use a typed array for best performance).
Delaunator.from(points[, getX, getY])
Constructs a delaunay triangulation object given an array of points ([x, y]
by default).
getX
and getY
are optional functions of the form (point) => value
for custom point formats.
Duplicate points are skipped.
delaunay.triangles
A Uint32Array
array of triangle vertex indices (each group of three numbers forms a triangle).
All triangles are directed counterclockwise.
To get the coordinates of all triangles when using Delaunator.from(points)
, use:
for (let i = 0; i < triangles.length; i += 3) {
coordinates.push([
points[triangles[i]],
points[triangles[i + 1]],
points[triangles[i + 2]]
]);
}
To get the coordinates of all triangles when using new Delaunator(coords)
, use:
for (let i = 0; i < triangles.length; i += 3) {
coordinates.push([
[coords[2 * triangles[i]], coords[2 * triangles[i] + 1]],
[coords[2 * triangles[i + 1]], coords[2 * triangles[i + 1] + 1]],
[coords[2 * triangles[i + 2]], coords[2 * triangles[i + 2] + 1]]
]);
}
delaunay.halfedges
A Int32Array
array of triangle half-edge indices that allows you to traverse the triangulation.
i
-th half-edge in the array corresponds to vertex triangles[i]
the half-edge is coming from.
halfedges[i]
is the index of a twin half-edge in an adjacent triangle
(or -1
for outer half-edges on the convex hull).
The flat array-based data structures might be counterintuitive, but they're one of the key reasons this library is fast.
delaunay.hull
A Uint32Array
array of indices that reference points on the convex hull of the input data, counter-clockwise.
delaunay.coords
An array of input coordinates in the form [x0, y0, x1, y1, ....]
,
of the type provided in the constructor (or Float64Array
if you used Delaunator.from
).
delaunay.update()
Updates the triangulation if you modified delaunay.coords
values in place, avoiding expensive memory allocations.
Useful for iterative relaxation algorithms such as Lloyd's.
Performance
Benchmark results against other Delaunay JS libraries
(npm run bench
on Macbook Pro Retina 15" 2017, Node v10.10.0):
uniform 100k | gauss 100k | grid 100k | degen 100k | uniform 1 million | gauss 1 million | grid 1 million | degen 1 million | |
---|---|---|---|---|---|---|---|---|
delaunator | 82ms | 61ms | 66ms | 25ms | 1.07s | 950ms | 830ms | 278ms |
faster‑delaunay | 473ms | 411ms | 272ms | 68ms | 4.27s | 4.62s | 4.3s | 810ms |
incremental‑delaunay | 547ms | 505ms | 172ms | 528ms | 5.9s | 6.08s | 2.11s | 6.09s |
d3‑voronoi | 972ms | 909ms | 358ms | 720ms | 15.04s | 13.86s | 5.55s | 11.13s |
delaunay‑fast | 3.8s | 4s | 12.57s | timeout | 132s | 138s | 399s | timeout |
delaunay | 4.85s | 5.73s | 15.05s | timeout | 156s | 178s | 326s | timeout |
delaunay‑triangulate | 2.24s | 2.04s | OOM | 1.51s | OOM | OOM | OOM | OOM |
cdt2d | 45s | 51s | 118s | 17s | timeout | timeout | timeout | timeout |
Papers
The algorithm is based on ideas from the following papers:
- A simple sweep-line Delaunay triangulation algorithm, 2013, Liu Yonghe, Feng Jinming and Shao Yuehong
- S-hull: a fast radial sweep-hull routine for Delaunay triangulation, 2010, David Sinclair
- A faster circle-sweep Delaunay triangulation algorithm, 2011, Ahmad Biniaz and Gholamhossein Dastghaibyfard
Robustness
Delaunator should produce valid output even on highly degenerate input. It does so by depending on robust-predicates, a modern port of Jonathan Shewchuk's robust geometric predicates, an industry standard in computational geometry.
Ports to other languages
- delaunator-rs (Rust)
- fogleman/delaunay (Go)
- delaunator-cpp (C++)
- delaunator-sharp (C#)
- delaunator-ruby (Ruby)
- Delaunator-Python (Python)
- torch-delaunay (Python/Torch)
- ricardomatias/delaunator (Kotlin)
- delaunator-java (Java)
- delaunay-Stata (Stata/Mata)
- Delaunator.jl (Julia)
Top Related Projects
A Javascript implementation of Fortune's algorithm to compute Voronoi cells
The fastest and smallest JavaScript polygon triangulation library for your WebGL apps
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designs to code with AI
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