71 lines
2.2 KiB
JavaScript
71 lines
2.2 KiB
JavaScript
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/* ============================================================
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rng.js — deterministic seeding & sampling
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Every stochastic decision in the generator draws from a
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salted sub-stream so that changing one parameter does not
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reshuffle unrelated parts of the scene.
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============================================================ */
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/* cyrb53 — fast 53-bit string hash. Stable across runs/machines. */
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export function cyrb53(str, seed = 0) {
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let h1 = 0xdeadbeef ^ seed, h2 = 0x41c6ce57 ^ seed;
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for (let i = 0; i < str.length; i++) {
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const ch = str.charCodeAt(i);
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h1 = Math.imul(h1 ^ ch, 2654435761);
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h2 = Math.imul(h2 ^ ch, 1597334677);
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}
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h1 = Math.imul(h1 ^ (h1 >>> 16), 2246822507) ^ Math.imul(h2 ^ (h2 >>> 13), 3266489909);
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h2 = Math.imul(h2 ^ (h2 >>> 16), 2246822507) ^ Math.imul(h1 ^ (h1 >>> 13), 3266489909);
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return (4294967296 * (2097151 & h2) + (h1 >>> 0)).toString(16).padStart(13, '0');
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}
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/* mulberry32 — tiny fast PRNG, returns [0,1). */
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export function mulberry32(seed) {
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let a = seed >>> 0;
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return function () {
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a = (a + 0x6D2B79F5) >>> 0;
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let t = a;
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t = Math.imul(t ^ (t >>> 15), t | 1);
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t ^= t + Math.imul(t ^ (t >>> 7), t | 61);
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return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
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};
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}
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/* makeRng — seed string + salt → independent PRNG stream. */
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export function makeRng(seedStr, salt = '') {
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const h = cyrb53(seedStr + '::' + salt);
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return mulberry32(parseInt(h.slice(0, 8), 16));
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}
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/* ---------- Distributions ---------- */
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/* Standard normal via Box-Muller. */
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export function gauss(rng) {
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const u = 1 - rng(), v = rng();
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return Math.sqrt(-2 * Math.log(u)) * Math.cos(2 * Math.PI * v);
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}
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/* Log-normal — heavy-tailed positive sample. */
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export function logNormal(rng, mu, sigma) {
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return Math.exp(mu + sigma * gauss(rng));
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}
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/* Uniform in [lo, hi). */
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export function range(rng, lo, hi) {
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return lo + (hi - lo) * rng();
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}
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/* Random int in [lo, hi]. */
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export function randInt(rng, lo, hi) {
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return lo + Math.floor(rng() * (hi - lo + 1));
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}
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/* Pick one element. */
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export function pick(rng, arr) {
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return arr[Math.floor(rng() * arr.length)];
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}
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/* Bernoulli. */
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export function chance(rng, p) {
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return rng() < p;
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}
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