blur = (d, i) =>
d3.median([i, ...triangulation.neighbors(i)], j => points[j][2])
points = d3.json(
"https://gist.githubusercontent.com/Fil/6bc12c535edc3602813a6ef2d1c73891/raw/3ae88bf307e740ddc020303ea95d7d2ecdec0d19/points.json"
)
triangulation = {
const c = d3.geoContour();
c.contour(points, 0); // compute a single contour to force the computation of the triangulation
return c._triangulation();
}
contour = d3
.geoContour()
.thresholds(100)
.value(!plain ? blur : d => d[2])
contours = ({
type: "FeatureCollection",
features: [{ type: "Sphere", value: -50 }, ...contour(points)]
})
color = d3.scaleSequential(d3.interpolateRdBu).domain([40, -20])
projection = d3
.geoArmadillo()
.fitExtent([[0, 0], [width, height]], { type: "Sphere" })
land = d3.json(
"https://unpkg.com/visionscarto-world-atlas/world/110m_land.geojson"
)
d3 = require("d3@7", "d3-geo-voronoi@2", "d3-geo-projection@3")
height = ((width * 2) / 3) | 0
import {checkbox} from "@jashkenas/inputs"
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.
