Visualization toolmaker. Founder @observablehq. Creator @d3. Former @nytgraphics. Pronounced BOSS-tock.
Guided Tour of an Infinite Sphere GridCreating a Canvas Noise Map for Generative Art012 Truchet tiles014 Joy Division016 Some TrianglesConnections 2Stacking Polygons In A CircleSplitting LinesBulge IllusionVoronoi Spirals IITruchet Tiles variant: Intertwined quarter circlesGetting Artsy With LloydUlam SpiralOil painting brushstrokesRotating VoronoiBridget Riley 3SphoiseTriangles And CirclesYvaral IITwo GridsRandomized Flood FillOrientedTrefoilsMeandering VoronoiVoronoi StipplingEyesSubstrateIncremental Drift (Rose Equation)Circles, Spirals and SunflowersVoronoi Stained Glass PortraitsYvaralMy first Observable Notebook - Art of πQuadtree ArtFitzHugh–Nagumo MazeBridget RileyStructure de QuadrilatèresFractal TreePencil TraceAltered World
Perlin Noise Contours
chart = {
const context = DOM.context2d(width, height);
const path = d3.geoPath(projection, context);
for (const value of samples(color.domain(), 200)) {
context.beginPath();
path(contours.contour(grid, value));
context.strokeStyle = color(value);
context.stroke();
yield context.canvas;
}
}
color = d3.scaleSequential(d3.extent(grid), d3.interpolateGreys)
q = 3 // The level of detail, e.g., sample every 4 pixels in x and y.
period = 0.005
n = Math.ceil(width / q) + 1
m = Math.ceil(height / q) + 1
projection = d3.geoIdentity().translate([-q / 2, -q / 2]).scale(q)
contours = d3.contours().size([n, m])
grid = {
const grid = new Float64Array(n * m);
for (let j = 0; j < m; ++j) {
for (let i = 0; i < n; ++i) {
grid[j * n + i] = noise.noise(i * period, j * period);
}
}
return grid;
}
noise = new Noise(3)
class Noise {
static lerp(t, a, b) {
return a + t * (b - a);
}
static grad2d(i, x, y) {
const v = (i & 1) === 0 ? x : y;
return (i & 2) === 0 ? -v : v;
}
constructor(octaves = 1) {
this.p = new Uint8Array(512);
this.octaves = octaves;
this.init();
}
init() {
for (let i = 0; i < 512; ++i) {
this.p[i] = Math.random() * 256;
}
}
noise2d(x2d, y2d) {
const X = Math.floor(x2d) & 255;
const Y = Math.floor(y2d) & 255;
const x = x2d - Math.floor(x2d);
const y = y2d - Math.floor(y2d);
const fx = (3 - 2 * x) * x * x;
const fy = (3 - 2 * y) * y * y;
const p0 = this.p[X] + Y;
const p1 = this.p[X + 1] + Y;
return Noise.lerp(
fy,
Noise.lerp(
fx,
Noise.grad2d(this.p[p0], x, y),
Noise.grad2d(this.p[p1], x - 1, y)
),
Noise.lerp(
fx,
Noise.grad2d(this.p[p0 + 1], x, y - 1),
Noise.grad2d(this.p[p1 + 1], x - 1, y - 1)
)
);
}
noise(x, y) {
let e = 1,
k = 1,
s = 0;
for (let i = 0; i < this.octaves; ++i) {
e *= 0.5;
s += e * (1 + this.noise2d(k * x, k * y)) / 2;
k *= 2;
}
return s;
}
}
height = 600
d3 = require("d3@5")
import {samples} from "@mbostock/1d-poisson-disk-sampling"
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