/** * A standalone, pure JavaScript implementation of the Mersenne Twister pseudo random number generator. * * @author Raphael Pigulla * @version 0.2.3 * @license * Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * 3. The names of its contributors may not be used to endorse or promote * products derived from this software without specific prior written * permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ export default class MersenneTwister { /** * Instantiates a new Mersenne Twister. * @param {number} [seed] The initial seed value, if not provided the current timestamp will be used. * @constructor */ constructor(seed) { // Initial values this.MAX_INT = 4294967296.0; this.N = 624; this.M = 397; this.UPPER_MASK = 0x80000000; this.LOWER_MASK = 0x7fffffff; this.MATRIX_A = 0x9908b0df; // Initialize sequences this.mt = new Array(this.N); this.mti = this.N + 1; this.SEED = this.seed(seed ?? new Date().getTime()); }; /** * Initializes the state vector by using one unsigned 32-bit integer "seed", which may be zero. * * @since 0.1.0 * @param {number} seed The seed value. */ seed(seed) { this.SEED = seed; let s; this.mt[0] = seed >>> 0; for (this.mti = 1; this.mti < this.N; this.mti++) { s = this.mt[this.mti - 1] ^ (this.mt[this.mti - 1] >>> 30); this.mt[this.mti] = (((((s & 0xffff0000) >>> 16) * 1812433253) << 16) + (s & 0x0000ffff) * 1812433253) + this.mti; this.mt[this.mti] >>>= 0; } return seed; }; /** * Initializes the state vector by using an array key[] of unsigned 32-bit integers of the specified length. If * length is smaller than 624, then each array of 32-bit integers gives distinct initial state vector. This is * useful if you want a larger seed space than 32-bit word. * * @since 0.1.0 * @param {array} vector The seed vector. */ seedArray(vector) { let i = 1, j = 0, k = this.N > vector.length ? this.N : vector.length, s; this.seed(19650218); for (; k > 0; k--) { s = this.mt[i - 1] ^ (this.mt[i - 1] >>> 30); this.mt[i] = (this.mt[i] ^ (((((s & 0xffff0000) >>> 16) * 1664525) << 16) + ((s & 0x0000ffff) * 1664525))) + vector[j] + j; this.mt[i] >>>= 0; i++; j++; if (i >= this.N) { this.mt[0] = this.mt[this.N-1]; i = 1; } if (j >= vector.length) { j = 0; } } for (k = this.N-1; k; k--) { s = this.mt[i - 1] ^ (this.mt[i - 1] >>> 30); this.mt[i] = (this.mt[i] ^ (((((s & 0xffff0000) >>> 16) * 1566083941) << 16) + (s & 0x0000ffff) * 1566083941)) - i; this.mt[i] >>>= 0; i++; if (i >= this.N) { this.mt[0] = this.mt[this.N - 1]; i = 1; } } this.mt[0] = 0x80000000; }; /** * Generates a random unsigned 32-bit integer. * * @since 0.1.0 * @returns {number} */ int() { let y, kk, mag01 = [0, this.MATRIX_A]; if (this.mti >= this.N) { if (this.mti === this.N+1) { this.seed(5489); } for (kk = 0; kk < this.N - this.M; kk++) { y = (this.mt[kk] & this.UPPER_MASK) | (this.mt[kk + 1] & this.LOWER_MASK); this.mt[kk] = this.mt[kk + this.M] ^ (y >>> 1) ^ mag01[y & 1]; } for (; kk < this.N - 1; kk++) { y = (this.mt[kk] & this.UPPER_MASK) | (this.mt[kk + 1] & this.LOWER_MASK); this.mt[kk] = this.mt[kk + (this.M - this.N)] ^ (y >>> 1) ^ mag01[y & 1]; } y = (this.mt[this.N - 1] & this.UPPER_MASK) | (this.mt[0] & this.LOWER_MASK); this.mt[this.N - 1] = this.mt[this.M - 1] ^ (y >>> 1) ^ mag01[y & 1]; this.mti = 0; } y = this.mt[this.mti++]; y ^= (y >>> 11); y ^= (y << 7) & 0x9d2c5680; y ^= (y << 15) & 0xefc60000; y ^= (y >>> 18); return y >>> 0; }; /** * Generates a random unsigned 31-bit integer. * * @since 0.1.0 * @returns {number} */ int31() { return this.int() >>> 1; }; /** * Generates a random real in the interval [0;1] with 32-bit resolution. * * @since 0.1.0 * @returns {number} */ real() { return this.int() * (1.0 / (this.MAX_INT - 1)); }; /** * Generates a random real in the interval ]0;1[ with 32-bit resolution. * * @since 0.1.0 * @returns {number} */ realx() { return (this.int() + 0.5) * (1.0 / this.MAX_INT); }; /** * Generates a random real in the interval [0;1[ with 32-bit resolution. * * @since 0.1.0 * @returns {number} */ rnd() { return this.int() * (1.0 / this.MAX_INT); }; /** * Generates a random real in the interval [0;1[ with 32-bit resolution. * * Same as .rnd() method - for consistency with Math.random() interface. * * @since 0.2.0 * @returns {number} */ random() { return this.rnd(); }; /** * Generates a random real in the interval [0;1[ with 53-bit resolution. * * @since 0.1.0 * @returns {number} */ rndHiRes() { const a = this.int() >>> 5; const b = this.int() >>> 6; return (a * 67108864.0 + b) * (1.0 / 9007199254740992.0); }; /** * A pseudo-normal distribution using the Box-Muller transform. * @param {number} mu The normal distribution mean * @param {number} sigma The normal distribution standard deviation * @returns {number} */ normal(mu, sigma) { let u = 0; while (u === 0) u = this.random(); // Converting [0,1) to (0,1) let v = 0; while (v === 0) v = this.random(); // Converting [0,1) to (0,1) let n = Math.sqrt( -2.0 * Math.log(u) ) * Math.cos(2.0 * Math.PI * v); return (n * sigma) + mu; } /** * A factory method for generating random uniform rolls * @returns {number} */ static random() { return twist.random(); } /** * A factory method for generating random normal rolls * @return {number} */ static normal(...args) { return twist.normal(...args); } } // Global singleton const twist = new MersenneTwister(Date.now());