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| /** | |
| * This code is an implementation of Alea algorithm; (C) 2010 Johannes Baagøe. | |
| * Alea is licensed according to the http://en.wikipedia.org/wiki/MIT_License. | |
| */ | |
| const FRAC = 2.3283064365386963e-10; /* 2^-32 */ | |
| class RNG { | |
| constructor() { | |
| this._seed = 0; | |
| this._s0 = 0; | |
| this._s1 = 0; | |
| this._s2 = 0; | |
| this._c = 0; | |
| } | |
| getSeed() { return this._seed; } | |
| /** | |
| * Seed the number generator | |
| */ | |
| setSeed(seed) { | |
| seed = (seed < 1 ? 1 / seed : seed); | |
| this._seed = seed; | |
| this._s0 = (seed >>> 0) * FRAC; | |
| seed = (seed * 69069 + 1) >>> 0; | |
| this._s1 = seed * FRAC; | |
| seed = (seed * 69069 + 1) >>> 0; | |
| this._s2 = seed * FRAC; | |
| this._c = 1; | |
| return this; | |
| } | |
| /** | |
| * @returns Pseudorandom value [0,1), uniformly distributed | |
| */ | |
| getUniform() { | |
| let t = 2091639 * this._s0 + this._c * FRAC; | |
| this._s0 = this._s1; | |
| this._s1 = this._s2; | |
| this._c = t | 0; | |
| this._s2 = t - this._c; | |
| return this._s2; | |
| } | |
| /** | |
| * @param lowerBound The lower end of the range to return a value from, inclusive | |
| * @param upperBound The upper end of the range to return a value from, inclusive | |
| * @returns Pseudorandom value [lowerBound, upperBound], using ROT.RNG.getUniform() to distribute the value | |
| */ | |
| getUniformInt(lowerBound, upperBound) { | |
| let max = Math.max(lowerBound, upperBound); | |
| let min = Math.min(lowerBound, upperBound); | |
| return Math.floor(this.getUniform() * (max - min + 1)) + min; | |
| } | |
| /** | |
| * @param mean Mean value | |
| * @param stddev Standard deviation. ~95% of the absolute values will be lower than 2*stddev. | |
| * @returns A normally distributed pseudorandom value | |
| */ | |
| getNormal(mean = 0, stddev = 1) { | |
| let u, v, r; | |
| do { | |
| u = 2 * this.getUniform() - 1; | |
| v = 2 * this.getUniform() - 1; | |
| r = u * u + v * v; | |
| } while (r > 1 || r == 0); | |
| let gauss = u * Math.sqrt(-2 * Math.log(r) / r); | |
| return mean + gauss * stddev; | |
| } | |
| /** | |
| * @returns Pseudorandom value [1,100] inclusive, uniformly distributed | |
| */ | |
| getPercentage() { | |
| return 1 + Math.floor(this.getUniform() * 100); | |
| } | |
| /** | |
| * @returns Randomly picked item, null when length=0 | |
| */ | |
| getItem(array) { | |
| if (!array.length) { | |
| return null; | |
| } | |
| return array[Math.floor(this.getUniform() * array.length)]; | |
| } | |
| /** | |
| * @returns New array with randomized items | |
| */ | |
| shuffle(array) { | |
| let result = []; | |
| let clone = array.slice(); | |
| while (clone.length) { | |
| let index = clone.indexOf(this.getItem(clone)); | |
| result.push(clone.splice(index, 1)[0]); | |
| } | |
| return result; | |
| } | |
| /** | |
| * @param data key=whatever, value=weight (relative probability) | |
| * @returns whatever | |
| */ | |
| getWeightedValue(data) { | |
| let total = 0; | |
| for (let id in data) { | |
| total += data[id]; | |
| } | |
| let random = this.getUniform() * total; | |
| let id, part = 0; | |
| for (id in data) { | |
| part += data[id]; | |
| if (random < part) { | |
| return id; | |
| } | |
| } | |
| // If by some floating-point annoyance we have | |
| // random >= total, just return the last id. | |
| return id; | |
| } | |
| /** | |
| * Get RNG state. Useful for storing the state and re-setting it via setState. | |
| * @returns Internal state | |
| */ | |
| getState() { return [this._s0, this._s1, this._s2, this._c]; } | |
| /** | |
| * Set a previously retrieved state. | |
| */ | |
| setState(state) { | |
| this._s0 = state[0]; | |
| this._s1 = state[1]; | |
| this._s2 = state[2]; | |
| this._c = state[3]; | |
| return this; | |
| } | |
| /** | |
| * Returns a cloned RNG | |
| */ | |
| clone() { | |
| let clone = new RNG(); | |
| return clone.setState(this.getState()); | |
| } | |
| } | |
| export default new RNG().setSeed(Date.now()); | |