Published
Edited
Nov 12, 2020
1 fork
10 stars
Hello, spectral.jsPseudo-blue noise shaderHow fast does walk-on-spheres converge?KDE estimationSpherical Perlin NoiseHull paddingDithered heatmapMean value coordinatesHeatmapPoisson potentialK-means binningImage FFTSquircle interpolatorDisc TransportAn approximate formula for the chord area inverse problemWalk on SpheresnoFrame contoursHue blurMoving average blurFitting a sigmoidGaussian SmoothingPlateau detectionHello, LOESSLinde–Buzo–Gray stipplinginterpolateBalanced?Hello, delatinHillshading & supersamplingBlurry contoursSpherical contours iteratorSpherical contours as a gradientGeo Voronoi interpolationModified Shepard’s method II (with geoContour)MapfillSpherical contoursModified Shepard’s methodShepard’s methodSpherical kernel interpolation with nearest neighborsSpherical HeatmapKrigingSpherical KDE Interpolation
Transport to a map
n = 4000 // don't be shy, try 30k!
transport = {
const dirs = 7,
strength = 1;
const w = 400,
h = (height * (w / width)) | 0;
let indices = [],
projection,
deltas;
const sample = Uint32Array.from(
d3.range(w * h).filter(k => bitmap((k % w) / w, Math.floor(k / w) / h))
);
const indicesq = Uint32Array.from(d3.range(sample.length));
const xs = Float32Array.from(indicesq, k => sample[k] % w);
const ys = Float32Array.from(indicesq, k => Math.floor(sample[k] / w));
const projectionq = new Float32Array(indicesq.length);
// batched
return points => {
const n = points.length / 2;
if (n !== indices.length) {
indices = Uint32Array.from(d3.range(n));
projection = new Float32Array(n);
deltas = new Float32Array(2 * n);
}
const a = 2 * Math.PI * Math.random();
deltas.fill(0);
for (let d = 0; d < dirs; d++) {
const ap = a + (Math.PI * d) / dirs,
sa = Math.sin(ap),
ca = Math.cos(ap);
for (let i = 0; i < n; i++)
projection[i] = ca * points[2 * i] + sa * points[2 * i + 1];
indices.sort((i, j) => projection[i] - projection[j]);
for (let i = 0; i < indicesq.length; i++)
projectionq[i] = (ca * xs[i] + sa * ys[i]) * (width / w);
indicesq.sort((i, j) => projectionq[i] - projectionq[j]);
let i, ideal, delta;
for (let k = 0; k < n; k++) {
i = indices[k];
ideal =
projectionq[
indicesq[Math.floor(((k + 1) / (n + 1)) * indicesq.length)]
];
delta = ideal - projection[i];
deltas[2 * i] += ca * delta;
deltas[2 * i + 1] += sa * delta;
}
}
for (let i = 0; i < points.length; i++)
points[i] += (deltas[i] / dirs) * strength;
};
}
points = {
const random = d3.randomNormal(0, 10);
return Float32Array.from(
{ length: 2 * n },
(_, i) => (i % 2 ? height : width) / 2 + random()
);
}
bitmap = {
const w = 400,
h = ((im.height / im.width) * w) | 0;
const context = DOM.context2d(w, h, 1);
context.drawImage(im, 0, 0, w, h);
const pixels = context
.getImageData(0, 0, w, h)
.data.filter((_, i) => i % 4 === 0);
return (x, y) =>
255 - pixels[Math.floor(x * w) + w * Math.floor(y * h)] > 127;
}
height = ((im1.height / im1.width) * width) | 0
im1 = FileAttachment("conformal-dymaxion.png").image()
im = {
if (image === "Earth") return im1;
const context = DOM.context2d(width, height, 1);
context.fillStyle = "white";
context.fillRect(0, 0, width, height);
const n = 3 + Math.random() * 8;
for (let i = 0; i < n; i++) {
context.beginPath();
context.arc(
Math.random() * width,
Math.random() * height,
30 + Math.random() * 60,
0,
tau
);
context.fillStyle = "black";
context.fill();
}
return context.canvas;
}
d3 = require("d3@6")
tau = 2 * Math.PI
import { checkbox, select } from "@jashkenas/inputs"
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