Plot: Voronoi labelsDelaunay edge coloringDelaunay sub-graphsd3-delaunay@6 robustly releasedClip LloydSemi-square voronoiTP3: Power Diagram and Semi-Discrete Optimal TransportSpatial interpolation: Voronoi & Blur (code)Paths Delaunay hoverSelf-Organizing Maps meet DelaunayVoronoiMap2DPolygon TriangulationHello, constrainautorThe Gray-Fuller spatial gridUnconnected Delaunay NeighborsLinde–Buzo–Gray stipplingLloyd’s relaxation on a graphManhattan Voronoi IIManhattan VoronoiGraph VoronoiUK TricontoursGeo Voronoi interpolationSpherical contoursPetri dish bubblingd3-geo-voronoi and gridded dataDelaunay.findTriangleIris Voronoi 3The Voronoi projectionSouth Africa’s medial axisDirection to shoreDistance to shoret-SNE VoronoiMurphey Butterfly ProjectionAlpha shapes 3Alpha shapes 2So many countries’ VoronoisKruskal MazeOffscreen VoronoiGeo Mesh & fake pointsDrawing Voronoi with two.jsAlpha shapesSpherical VoronoiPerturbed Geodesic RainbowWorld Airports UrquhartSpherical Lloyds RelaxationAntarctica’s VoronoiWorld Airports VoronoiThe Urquhart graphGeo Delaunay
World Cities Urquhart
Also listed in…
Graphs
delaunay = d3.geoDelaunay(points)
distances = delaunay.edges.map(([a, b]) => distance(points[a], points[b]))
distance = use_euclidian ? euclidian : d3.geoDistance
euclidian = (a, b) => Math.hypot(a[0] - b[0], a[1] - b[1])
urquhart = delaunay.urquhart(distances)
edges = delaunay.edges
urquhart_edges = edges.filter((_, i) => urquhart[i])
urquhart_mesh = ({
type: "MultiLineString",
coordinates: urquhart_edges.map(([i, j]) => [points[i], points[j]])
})
voronoi_mesh = ({
type: "MultiLineString",
coordinates: delaunay.mesh.map(([i, j]) => [
delaunay.centers[i],
delaunay.centers[j]
])
})
delaunay.mesh
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
