Use seedrandom to back PseudoRandom.ts (#1828)

## Description:

The previous implementation had a bug that biased numbers away from 0,
so random.chance(1500+) would always return false. This caused trains to
not spawn at all when their spawn rate was sufficiently low. We should
be using a library instead of implementing it from scratch anyways.

## Please complete the following:

- [x] I have added screenshots for all UI updates
- [x] I process any text displayed to the user through translateText()
and I've added it to the en.json file
- [x] I have added relevant tests to the test directory
- [x] I confirm I have thoroughly tested these changes and take full
responsibility for any bugs introduced

## Please put your Discord username so you can be contacted if a bug or
regression is found:

evan
This commit is contained in:
evanpelle
2025-08-16 18:03:25 -07:00
committed by GitHub
parent bce2b80486
commit 77fd82b4b4
3 changed files with 38 additions and 103 deletions
+21 -103
View File
@@ -1,123 +1,45 @@
export class PseudoRandom {
// Internal state (two 32-bit integers)
private state0: number;
private state1: number;
import seedrandom from "seedrandom";
// Keep these variables to maintain the exact same interface
private m: number = 0x80000000; // 2**31
private a: number = 1103515245;
private c: number = 12345;
private state: number;
export class PseudoRandom {
private rng: seedrandom.PRNG;
private static readonly POW36_8 = Math.pow(36, 8); // Pre-compute 36^8
private static readonly INV_2_32 = 1 / 4294967296; // 1 / 2^32 for float conversion
constructor(seed: number) {
// Initialize the XorShift state with seed
this.state0 = seed | 0; // Force to 32-bit integer with bitwise OR
this.state1 = 0x6e2d786c; // Fixed value as second seed (arbitrary prime)
// Ensure non-zero state
if (this.state0 === 0) this.state0 = 1;
// Also set the LCG state variable to maintain interface
this.state = seed % this.m;
if (this.state < 0) this.state += this.m;
// Warm up the generator to improve initial distribution
for (let i = 0; i < 20; i++) {
this._nextIntInternal();
}
this.rng = seedrandom(String(seed));
}
/**
* Internal function that implements XorShift algorithm
* @returns A 32-bit integer
*/
private _nextIntInternal(): number {
// Get current state
let s1 = this.state0;
const s0 = this.state1;
// Update state using XorShift algorithm (all operations are bitwise)
this.state0 = s0;
s1 ^= s1 << 23;
s1 ^= s1 >>> 17;
s1 ^= s0;
s1 ^= s0 >>> 26;
this.state1 = s1;
// Generate output (force 32-bit integer)
return (this.state0 + this.state1) | 0;
}
/**
* Optimized version that directly returns unsigned 32-bit integer
*/
private _nextUInt32(): number {
return this._nextIntInternal() >>> 0;
}
/**
* Generates the next pseudorandom number.
* @returns A number between 0 (inclusive) and 1 (exclusive).
*/
// Generates the next pseudorandom number between 0 and 1.
next(): number {
// Get a 32-bit integer and convert to [0,1) range
// Using >>> 0 to get unsigned interpretation (positive number)
const int = this._nextUInt32();
// Update the state variable to maintain compatibility with original interface
this.state = int % this.m;
// Convert to [0,1) range - using division for same interface
return this.state / this.m;
return this.rng();
}
/**
* Optimized version for internal use - directly converts to [0,1) without state update
*/
private _nextFloat(): number {
return this._nextUInt32() * PseudoRandom.INV_2_32;
}
/**
* Generates a random integer between min (inclusive) and max (exclusive).
*/
// Generates a random integer between min (inclusive) and max (exclusive).
nextInt(min: number, max: number): number {
// keep max exclusive, min inclusive round down to get an int
return Math.floor(this._nextFloat() * (max - min)) + min;
return Math.floor(this.rng() * (max - min)) + min;
}
/**
* Generates a random float between min (inclusive) and max (exclusive).
*/
// Generates a random float between min (inclusive) and max (exclusive).
nextFloat(min: number, max: number): number {
return this._nextFloat() * (max - min) + min;
return this.rng() * (max - min) + min;
}
/**
* Generates a random ID (8 characters, alphanumeric).
*/
// Generates a random ID (8 characters, alphanumeric).
nextID(): string {
return Math.floor(this._nextFloat() * PseudoRandom.POW36_8) // 36^8 possibilities
.toString(36) // Convert to base36 (0-9 and a-z)
.padStart(8, "0"); // Ensure 8 chars by padding with zeros
return Math.floor(this.rng() * PseudoRandom.POW36_8)
.toString(36)
.padStart(8, "0");
}
/**
* Selects a random element from an array.
*/
// Selects a random element from an array.
randElement<T>(arr: T[]): T {
if (arr.length === 0) {
throw new Error("array must not be empty");
}
return arr[Math.floor(this._nextFloat() * arr.length)];
return arr[Math.floor(this.rng() * arr.length)];
}
/**
* Selects a random element from a set.
*/
// Selects a random element from a set.
randFromSet<T>(set: Set<T>): T {
const size = set.size;
if (size === 0) {
@@ -137,20 +59,16 @@ export class PseudoRandom {
throw new Error("Unexpected error selecting element from set");
}
/**
* Returns true with probability 1/odds.
*/
// Returns true with probability 1/odds.
chance(odds: number): boolean {
return Math.floor(this._nextFloat() * odds) === 0;
return Math.floor(this.rng() * odds) === 0;
}
/**
* Returns a shuffled copy of the array using Fisher-Yates algorithm.
*/
// Returns a shuffled copy of the array using Fisher-Yates algorithm.
shuffleArray<T>(array: T[]): T[] {
const result = [...array];
for (let i = result.length - 1; i >= 0; i--) {
const j = Math.floor(this._nextFloat() * (i + 1));
const j = Math.floor(this.rng() * (i + 1));
[result[i], result[j]] = [result[j], result[i]];
}
return result;