Seeded random number generators for TypeScript.
npm install ts-seedrandom
Each generator includes the following methods:
quick - Default method used. Provides 32 bits of randomness in a float. Can either be called by calling generator instance directly (ex.generator()) or by name (ex.generator.quick()).double - Provides 56 bits of randomness.int32 - Providers a 32 bit (signed) integer.state - Provides internal generator state. Used for saving and restoring states.
import{prngAlea}from'ts-seedrandom';constaleaGenerator=prngAlea('seed');constfirstValue=aleaGenerator();constsecondValue=aleaGenerator();You also have the option of saving and restoring state of your generator.
import{prngAlea}from'ts-seedrandom';constaleaGenerator=prngAlea('seed');constfirstValue=aleaGenerator();// Return internal generator state, which you can use in other generator instancesconststate=aleaGenerator.state();// This generator starts from the same state as first generator, but runs independentlyconstsecondAleaGenerator=prngAlea('seed',state);The following PRNG algorithms are available:
prngAlea: Alea algorithmprngArc4: ARC4 algorithmprngTychei: Tyche-i algorithmprngXor128: XorShift128 algorithmprngXor4096: XorShift4096 algorithmprngXorshift7: XorShift7 algorithmprngXorwow: Xorwow algorithmprngMulberry32: Mulberry 32 algorithmprngXoshiro128Plus: Xoshiro128+ algorithm (simple, fast)prngXoshiro128PlusPlus: Xoshiro128++ algorithm (higher statistical quality)prngSplitMix64: SplitMix64 algorithmprngPcg32: PCG32 algorithm
You can import and use any of these algorithms in the same way as demonstrated in the usage examples above.
| Name | State Size | Speed 🏎️ | Quality 📊 | Period | Notes |
|---|
prngAlea | ~96 bits | 🟢 Fast | 🔸 OK | ~2³² | Simple and widely used in JS |
prngArc4 | 2048 bits | 🟡 Medium | 🔸 OK | ~2¹⁷⁰⁰ | Legacy cipher, good entropy, slowish |
prngTychei | 128 bits | 🟢 Fast | 🟡 Medium | ~2⁶⁴ | Inspired by Marsaglia, fast and small |
prngXor128 | 128 bits | 🟢 Fast | 🔸 OK | ~2¹²⁸−1 | Basic Xorshift, outdated |
prngXor4096 | 4096 bits | 🔴 Slow | 🟡 Medium | ~2⁴⁰⁹⁶−1 | Very large state |
prngXorshift7 | 224 bits | 🟡 Medium | 🟡 Medium | ~2²²⁴ | Passes more tests than basic Xorshift |
prngXorwow | 160 bits | 🟢 Fast | 🟡 Medium | ~2¹⁹² | Used in older CUDA RNGs |
prngMulberry32 | 32 bits | 🟢 Very fast | 🔸 OK | ~2³² | Very small, ultra fast |
prngXoshiro128Plus | 128 bits | 🟢 Fast | 🟡 Good | ~2¹²⁸−1 | Simple, good for games |
prngXoshiro128PlusPlus | 128 bits | 🟢 Fast | 🟢 Better | ~2¹²⁸−1 | Improved output function |
prngSplitMix64 | 64 bits | 🟢 Very fast | 🟢 High | ~2⁶⁴ | Great for seeding other PRNGs |
prngPcg32 | 64 bits | 🟢 Fast | 🟢 High | ~2⁶⁴ | Compact, modern, good for simulation use |
Speed:
- 🟢 Fast: Suitable for games, animation, UI
- 🟡 Medium: Acceptable overhead
- 🔴 Slow: Use only when large state is essential
Quality:
- 🔸 OK: May fail strict tests (e.g., PractRand)
- 🟡 Medium: Passes basic uniformity/randomness
- 🟢 High: Strong statistical quality