mirror of
https://github.com/bspeice/speice.io
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143 lines
3.4 KiB
TypeScript
143 lines
3.4 KiB
TypeScript
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import { randomInteger } from "./0-utility";
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type Variation = (x: number, y: number) => [number, number];
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const r = (x: number, y: number) => {
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return Math.sqrt(Math.pow(x, 2) + Math.pow(y, 2));
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};
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const theta = (x: number, y: number) => {
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return Math.atan2(x, y);
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};
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const linear: Variation = (x, y) => {
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return [x, y];
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};
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const swirl: Variation = (x, y) => {
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const r2 = Math.pow(r(x, y), 2);
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const sinR2 = Math.sin(r2);
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const cosR2 = Math.cos(r2);
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return [x * sinR2 - y * cosR2, x * cosR2 + y * sinR2];
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};
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const polar: Variation = (x, y) => {
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return [theta(x, y) / Math.PI, r(x, y) - 1];
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};
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const disc: Variation = (x, y) => {
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const thetaOverPi = theta(x, y) / Math.PI;
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const piR = Math.PI * r(x, y);
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return [thetaOverPi * Math.sin(piR), thetaOverPi * Math.cos(piR)];
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};
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const variations = [linear, swirl, polar, disc];
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class Coefs {
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constructor(
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public readonly a: number,
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public readonly b: number,
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public readonly c: number,
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public readonly d: number,
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public readonly e: number,
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public readonly f: number
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) {}
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}
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class Transform {
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constructor(
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public readonly weight: number,
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public readonly coefs: Coefs,
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// Assumes that we have a blend for each variation
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public readonly blend: number[]
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) {}
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apply(x: number, y: number) {
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const variationX = this.coefs.a * x + this.coefs.b * y + this.coefs.c;
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const variationY = this.coefs.d * x + this.coefs.e * y + this.coefs.f;
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var transformX = 0;
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var transformY = 0;
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this.blend.forEach((blend, i) => {
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const [perVarX, perVarY] = variations[i](variationX, variationY);
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transformX += blend * perVarX;
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transformY += blend * perVarY;
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});
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return [transformX, transformY];
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}
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}
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function plot(x: number, y: number, image: ImageData) {
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const pixelX = Math.floor(((x + 2) * image.width) / 4);
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const pixelY = Math.floor(((y + 2) * image.height) / 4);
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if (
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pixelX < 0 ||
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pixelX > image.width ||
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pixelY < 0 ||
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pixelY > image.height
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) {
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return;
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}
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const index = pixelY * (image.width * 4) + pixelX * 4;
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image.data[index + 0] = 0;
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image.data[index + 1] = 0;
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image.data[index + 2] = 0;
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image.data[index + 3] = 0xff;
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}
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function render(transforms: Transform[], image: ImageData) {
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const weightSum = transforms.reduce((val, xform) => val + xform.weight, 0);
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var x = Math.random() * 2 - 1;
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var y = Math.random() * 2 - 1;
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const iter = 100_000;
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for (var i = 0; i < iter; i++) {
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// Find the tranform we're operating on
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/*
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var f = Math.random() * weightSum;
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var transform = transforms[0];
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transforms.forEach((xform, j) => {
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if (f > 0 && f < xform.weight) {
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console.log(`xform=${j}`);
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transform = xform;
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f -= xform.weight;
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}
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});
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*/
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// HACK: Currently assuming weights are equal
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const transform = transforms[randomInteger(0, transforms.length)];
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// Play the chaos game
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[x, y] = transform.apply(x, y);
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if (i > 20) {
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plot(x, y, image);
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}
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}
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}
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export function renderBaseline(image: ImageData) {
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return render(
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[
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new Transform(
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0.5,
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new Coefs(0.982996, 0, -0.219512, 0, 0.982996, -0.1875),
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[1, 0, 0, -0.934]
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),
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new Transform(
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0.5,
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new Coefs(0.966511, -0.256624, 0.050305, 0.256624, 0.966511, -0.235518),
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[0, 0.156, 0.778, 0]
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),
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],
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image
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);
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}
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