INSEE ParquetWord Tour: 40k words and their friendsHello, SageMath cellPoisson disk sampling functionsSubresource Integrity Hash GeneratorChatterjee correlationTagged bordersHeatmapSankey link paths (#91)Search with AccentsHello, EDTF!Canvas axisTernary binningTable ExtractorjszipScintillating symbolsDiscrete distribution inputHello, talismanCanvas path blurPaths Delaunay hoverFill with strokeDruidJSAnimating a cardinal curve between control points
Spatial interpolation: Voronoi & Blur (code)
Also listed in…
Voronoi
scale = 0.2
isopleth = isoplethFactory(centers, width, height)
data = (replay,
Array.from(
Object.values(states),
d => somevalue || Math.floor(Math.random() * 256)
))
function isoplethFactory(centers, width, height, padding) {
if (!padding) padding = 0;
const scale = 0.2;
const w = Math.round((width + 2 * padding) * scale);
const h = Math.round((height + 2 * padding) * scale);
const x = scaleLinear([-padding, width + padding], [0, w]);
const y = x; // Use scaleLinear([0, height], [0, h]); to change the aspect ratio (usually we wouldn't want that)
const delaunay = Delaunay.from(centers.map(d => [x(d[0]), y(d[1])]));
const nn = nnmap(delaunay, w, h);
const bl = blur().width(w);
const ct = contours().size([w, h]);
function rescale(contour) {
for (const polygon of contour.coordinates) {
for (const ring of polygon) {
for (const pt of ring) {
pt[0] = x.invert(pt[0]);
pt[1] = y.invert(pt[1]);
}
}
}
return contour;
}
function nnmap(delaunay, width, height) {
const site = new Uint16Array(width * height),
distance = new Float32Array(width * height);
width |= 0;
height |= 0;
let n = 0;
for (let i = 0; i < width; i++) {
for (let j = 0; j < height; j++) {
site[i + width * j] = n = delaunay.find(i, j);
distance[i + width * j] = Math.hypot(
delaunay.points[2 * n] - i,
delaunay.points[2 * n + 1] - j
);
}
}
return { site, distance, width, height };
}
function datamap(data, nn, borderradius, defaultValue) {
return borderradius > 0
? Array.from(nn.site, (s, i) =>
nn.distance[i] < borderradius ? data[s] : defaultValue
)
: Array.from(nn.site, s => data[s]);
}
function computecontours(data, bandwidth, borderradius, defaultValue = 0) {
bl.radius(bandwidth * scale);
return ct(bl(datamap(data, nn, borderradius * scale, defaultValue))).map(
rescale
);
}
computecontours.thresholds = _ =>
_ ? (ct.thresholds(_), computecontours) : ct.thresholds();
return computecontours;
}
contours = d3.contours
scaleLinear = d3.scaleLinear
Delaunay = d3.Delaunay
blur = (await require("array-blur")).blur
d3 = require("d3@6", "array-blur@1")
color = d3.scaleSequential(d3["interpolate"+scheme]).domain([0, 255])
centers = Array.from(Object.values(states), d => [
(width * (2 + d.x)) / 15,
(height * (2 - d.y)) / 11
])
height = Math.round(width / Math.sqrt(3))
somevalue = (replay, samevalue && 100 + 150 * Math.random())
states = FileAttachment("tileCoords (1).json").json()
import { checkbox, select, slider } from "@jashkenas/inputs"
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.