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 VoronoiWorld Cities UrquhartUK TricontoursGeo Voronoi interpolationPetri 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
Spherical contours
points = d3.json(
"https://gist.githubusercontent.com/Fil/6bc12c535edc3602813a6ef2d1c73891/raw/3ae88bf307e740ddc020303ea95d7d2ecdec0d19/points.json"
)
contour = d3.geoContour().thresholds(500)
contours = ({
type: "FeatureCollection",
features: [{ type: "Sphere", value: -50 }, ...contour(points)]
})
color = d3.scaleSequential(d3.interpolateRdBu).domain([40, -20])
projection = d3
.geoBertin1953()
.fitExtent([[0, 0], [width, height]], { type: "Sphere" })
import { land } from "@visionscarto/geo"
d3 = require("d3@7", "d3-geo-voronoi@2", "d3-geo-projection@4")
height = ((width * 2) / 3) | 0
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.
