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Working version of updated randomness

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This commit is contained in:
Aria 2025-08-15 22:57:59 -05:00
parent ed5bf3b3fc
commit 058d950121
1 changed files with 36 additions and 26 deletions
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62
packages/core/signal.mjs
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@ -188,36 +188,46 @@ export const mouseX = signal(() => _mouseX);
// random signals
const xorwise = (x) => {
const a = (x << 13) ^ x;
const b = (a >> 17) ^ a;
return (b << 5) ^ b;
};
// Produce "Avalanche effect" where flipping a single bit of x
// results in all output bits flipping with probability 0.5
// See e.g. https://github.com/aappleby/smhasher/blob/0ff96f7835817a27d0487325b6c16033e2992eb5/src/MurmurHash3.cpp#L68-L77
function _murmurHashFinalizer(x) {
x |= 0;
x ^= x >>> 16;
x = Math.imul(x, 0x85ebca6b);
x ^= x >>> 13;
x = Math.imul(x, 0xc2b2ae35);
x ^= x >>> 16;
return x >>> 0; // unsigned
}
// stretch 300 cycles over the range of [0,2**29 == 536870912) then apply the xorshift algorithm
const _frac = (x) => x - Math.trunc(x);
// Used to decorrelate nearby t and i prior to hashing
function _decorrelate(t, i = 0) {
// const T = Math.floor(t * 4096); // set 2^12 resolution
const T = Math.floor(t * 536870912); // set 2^29 resolution
const lowBits = (T >>> 0) >>> 0;
const highBits = Math.floor(T / 4294967296) >>> 0; // 2^32
let key = lowBits ^ Math.imul(highBits ^ 0x85ebca6b, 0xc2b2ae35);
key ^= Math.imul(i ^ 0x7f4a7c15, 0x9e3779b9);
return key >>> 0;
// return (T ^ Math.imul(i ^ 0x7f4a7c15, 0x9e3779b9)) >>> 0;
}
const timeToIntSeed = (x) => xorwise(Math.trunc(_frac(x / 300) * 536870912));
function randAt(t, i = 0) {
return _murmurHashFinalizer(_decorrelate(t, i)) / 4294967296; // 2^32
}
const intSeedToRand = (x) => (x % 536870912) / 536870912;
// N samples at time t
function timeToRands(t, n) {
const out = new Array(n);
for (let i = 0; i < n; i++) out[i] = randAt(t, i);
return out;
}
const timeToRand = (x) => Math.abs(intSeedToRand(timeToIntSeed(x)));
const timeToRandsPrime = (seed, n) => {
const result = [];
// eslint-disable-next-line
for (let i = 0; i < n; ++i) {
result.push(intSeedToRand(seed));
seed = xorwise(seed);
}
return result;
};
const timeToRands = (t, n) => timeToRandsPrime(timeToIntSeed(t), n);
/**
*
*/
// Single sample at time t
function timeToRand(t) {
return randAt(t, 0);
}
/**
* A discrete pattern of numbers from 0 to n-1