StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
https://doi.org/10.1109/TVCG.2020.3030352
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Angelos Chatzimparmpas
e069030893
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3 years ago | |
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| .. | ||
| bench | 3 years ago | |
| example | 3 years ago | |
| test | 3 years ago | |
| .npmignore | 3 years ago | |
| .travis.yml | 3 years ago | |
| LICENSE | 3 years ago | |
| README.md | 3 years ago | |
| delaunay3d.png | 3 years ago | |
| package.json | 3 years ago | |
| triangulate.js | 3 years ago | |
README.md
delaunay-triangulate
Triangulates a set of points into a Delaunay triangulation. This code works in arbitrary dimensions, and both in the server and in the browser.
Here are some in browser demos:
Example
var triangulate = require("delaunay-triangulate")
var points = [
[0, 1],
[1, 0],
[1, 1],
[0, 0],
[0.5, 0.5]
]
var triangles = triangulate(points)
console.log(triangles)
Install
npm install delaunay-triangulate
API
require("delaunay-triangulate")(points[,pointAtInfinity])
Constructs a Delaunay triangulation over points
pointsis a collection of points in Euclidean space.pointAtInfinityis a flag, which if set adds an extra point at infinity to give the spherical compactification of the triangulation. The index of the point at infinity is-1
Returns A list of cells representing the faces of the triangulation. These are triangles in 2D or tetrahedra in 3D.
Credits
(c) 2013-2014 Mikola Lysenko. MIT License