## Delaunay.jl

Find the Delaunay triangulation for a set of points
Author eschnett
Popularity
4 Stars
Updated Last
1 Year Ago
Started In
July 2020

# Delaunay / də lɔˈnɛ /: Find the Delaunay triangulation for a set of points

This package finds the Delaunay triangulation for a set of points in arbitrary dimensions. It uses the Python package `scipy.spatial.Delaunay` to perform the actual calculation.

This package is inspired by QHull.jl, which uses the same Python library.

## Example in 2D

```using Delaunay
points = rand(10, 2)
mesh = delaunay(points)

mesh.points                      # the points
mesh.simplices                   # the simplices (triangles in 2d)
mesh.neighbors                   # neighbouring simplices of a simplex
mesh.vertex_to_simplex           # find a simplex for a point
mesh.convex_hull                 # convex hull of the domain
mesh.vertex_neighbor_vertices    # neighbouring vertices of a vertex

using Makie
color = rand(size(mesh.points, 1))
scene = Makie.mesh(mesh.points, mesh.simplices, color=color, shading=false, scale_plot=false)
xlims!(scene, 0, 1)
ylims!(scene, 0, 1)
wireframe!(scene[end], color=(:black, 0.6), linewidth=5)```

## Example in 3D

```using Delaunay
points = rand(6, 3)
mesh = delaunay(points)

using Makie
scene = Makie.mesh(mesh.points, mesh.simplices, visible=false)
xlims!(scene, 0, 1)
ylims!(scene, 0, 1)
zlims!(scene, 0, 1)
wireframe!(scene[end], color=(:black, 0.6), linewidth=5)```

The test cases contain also examples in higher dimensions.

### Used By Packages

No packages found.