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unified-ai-platform/node_modules/pure-rand/CHANGELOG.md
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# CHANGELOG 6.X
|
||||
|
||||
## 6.1.0
|
||||
|
||||
### Features
|
||||
|
||||
- [c60c828](https://github.com/dubzzz/pure-rand/commit/c60c828) ✨ Clone from state on `xorshift128plus` (#697)
|
||||
- [6a16bfe](https://github.com/dubzzz/pure-rand/commit/6a16bfe) ✨ Clone from state on `mersenne` (#698)
|
||||
- [fb78e2d](https://github.com/dubzzz/pure-rand/commit/fb78e2d) ✨ Clone from state on `xoroshiro128plus` (#699)
|
||||
- [a7dd56c](https://github.com/dubzzz/pure-rand/commit/a7dd56c) ✨ Clone from state on congruential32 (#696)
|
||||
- [1f6c3a5](https://github.com/dubzzz/pure-rand/commit/1f6c3a5) 🏷️ Expose internal state of generators (#694)
|
||||
|
||||
### Fixes
|
||||
|
||||
- [30d439a](https://github.com/dubzzz/pure-rand/commit/30d439a) 💚 Fix broken lock file (#695)
|
||||
- [9f935ae](https://github.com/dubzzz/pure-rand/commit/9f935ae) 👷 Speed-up CI with better cache (#677)
|
||||
|
||||
## 6.0.4
|
||||
|
||||
### Fixes
|
||||
|
||||
- [716e073](https://github.com/dubzzz/pure-rand/commit/716e073) 🐛 Fix typings for node native esm (#649)
|
||||
|
||||
## 6.0.3
|
||||
|
||||
### Fixes
|
||||
|
||||
- [9aca792](https://github.com/dubzzz/pure-rand/commit/9aca792) 🏷️ Better declare ESM's types (#634)
|
||||
|
||||
## 6.0.2
|
||||
|
||||
### Fixes
|
||||
|
||||
- [6d05e8f](https://github.com/dubzzz/pure-rand/commit/6d05e8f) 🔐 Sign published packages (#591)
|
||||
- [8b4e165](https://github.com/dubzzz/pure-rand/commit/8b4e165) 👷 Switch default to Node 18 in CI (#578)
|
||||
|
||||
## 6.0.1
|
||||
|
||||
### Fixes
|
||||
|
||||
- [05421f2](https://github.com/dubzzz/pure-rand/commit/05421f2) 🚨 Reformat README.md (#563)
|
||||
- [ffacfbd](https://github.com/dubzzz/pure-rand/commit/ffacfbd) 📝 Give simple seed computation example (#562)
|
||||
- [e432d59](https://github.com/dubzzz/pure-rand/commit/e432d59) 📝 Add extra keywords (#561)
|
||||
- [f5b18d4](https://github.com/dubzzz/pure-rand/commit/f5b18d4) 🐛 Declare types first for package (#560)
|
||||
- [a5b30db](https://github.com/dubzzz/pure-rand/commit/a5b30db) 📝 Final clean-up of the README (#559)
|
||||
- [5254ee0](https://github.com/dubzzz/pure-rand/commit/5254ee0) 📝 Fix simple examples not fully working (#558)
|
||||
- [8daf460](https://github.com/dubzzz/pure-rand/commit/8daf460) 📝 Clarify the README (#556)
|
||||
- [a915b6a](https://github.com/dubzzz/pure-rand/commit/a915b6a) 📝 Fix url error in README for logo (#554)
|
||||
- [f94885c](https://github.com/dubzzz/pure-rand/commit/f94885c) 📝 Rework README header with logo (#553)
|
||||
- [5f7645e](https://github.com/dubzzz/pure-rand/commit/5f7645e) 📝 Typo in link to comparison SVG (#551)
|
||||
- [61726af](https://github.com/dubzzz/pure-rand/commit/61726af) 📝 Better keywords for NPM (#550)
|
||||
- [6001e5a](https://github.com/dubzzz/pure-rand/commit/6001e5a) 📝 Update performance section with recent stats (#549)
|
||||
- [556ec33](https://github.com/dubzzz/pure-rand/commit/556ec33) ⚗️ Rewrite not uniform of pure-rand (#547)
|
||||
- [b3dfea5](https://github.com/dubzzz/pure-rand/commit/b3dfea5) ⚗️ Add more libraries to the experiment (#546)
|
||||
- [ac8b85d](https://github.com/dubzzz/pure-rand/commit/ac8b85d) ⚗️ Add some more non-uniform versions (#543)
|
||||
- [44af2ad](https://github.com/dubzzz/pure-rand/commit/44af2ad) ⚗️ Add some more self comparisons (#542)
|
||||
- [6d3342d](https://github.com/dubzzz/pure-rand/commit/6d3342d) 📝 Add some more details on the algorithms in compare (#541)
|
||||
- [359e214](https://github.com/dubzzz/pure-rand/commit/359e214) 📝 Fix some typos in README (#540)
|
||||
- [28a7bfe](https://github.com/dubzzz/pure-rand/commit/28a7bfe) 📝 Document some performance stats (#539)
|
||||
- [81860b7](https://github.com/dubzzz/pure-rand/commit/81860b7) ⚗️ Measure performance against other libraries (#538)
|
||||
- [114c2c7](https://github.com/dubzzz/pure-rand/commit/114c2c7) 📝 Publish changelogs from 3.X to 6.X (#537)
|
||||
|
||||
## 6.0.0
|
||||
|
||||
### Breaking Changes
|
||||
|
||||
- [c45912f](https://github.com/dubzzz/pure-rand/commit/c45912f) 💥 Require generators uniform in int32 (#513)
|
||||
- [0bde03e](https://github.com/dubzzz/pure-rand/commit/0bde03e) 💥 Drop congruencial generator (#511)
|
||||
|
||||
### Features
|
||||
|
||||
- [7587984](https://github.com/dubzzz/pure-rand/commit/7587984) ⚡️ Faster uniform distribution on bigint (#517)
|
||||
- [464960a](https://github.com/dubzzz/pure-rand/commit/464960a) ⚡️ Faster uniform distribution on small ranges (#516)
|
||||
- [b4852a8](https://github.com/dubzzz/pure-rand/commit/b4852a8) ⚡️ Faster Congruencial 32bits (#512)
|
||||
- [fdb6ec8](https://github.com/dubzzz/pure-rand/commit/fdb6ec8) ⚡️ Faster Mersenne-Twister (#510)
|
||||
- [bb69be5](https://github.com/dubzzz/pure-rand/commit/bb69be5) ⚡️ Drop infinite loop for explicit loop (#507)
|
||||
|
||||
### Fixes
|
||||
|
||||
- [00fc62b](https://github.com/dubzzz/pure-rand/commit/00fc62b) 🔨 Add missing benchType to the script (#522)
|
||||
- [db4a0a6](https://github.com/dubzzz/pure-rand/commit/db4a0a6) 🔨 Add more options to benchmark (#521)
|
||||
- [5c1ca0e](https://github.com/dubzzz/pure-rand/commit/5c1ca0e) 🔨 Fix typo in benchmark code (#520)
|
||||
- [36c965f](https://github.com/dubzzz/pure-rand/commit/36c965f) 👷 Define a benchmark workflow (#519)
|
||||
- [0281cfd](https://github.com/dubzzz/pure-rand/commit/0281cfd) 🔨 More customizable benchmark (#518)
|
||||
- [a7e19a8](https://github.com/dubzzz/pure-rand/commit/a7e19a8) 🔥 Clean internals of uniform distribution (#515)
|
||||
- [520cca7](https://github.com/dubzzz/pure-rand/commit/520cca7) 🔨 Add some more benchmarks (#514)
|
||||
- [c2d6ee6](https://github.com/dubzzz/pure-rand/commit/c2d6ee6) 🔨 Fix typo in bench for large reference (#509)
|
||||
- [2dd7280](https://github.com/dubzzz/pure-rand/commit/2dd7280) 🔥 Clean useless variable (#506)
|
||||
- [dd621c9](https://github.com/dubzzz/pure-rand/commit/dd621c9) 🔨 Adapt benchmarks to make them reliable (#505)
|
||||
- [122f968](https://github.com/dubzzz/pure-rand/commit/122f968) 👷 Drop dependabot
|
||||
- [f11d2e8](https://github.com/dubzzz/pure-rand/commit/f11d2e8) 💸 Add GitHub sponsors in repository's configuration
|
||||
- [6a23e48](https://github.com/dubzzz/pure-rand/commit/6a23e48) 👷 Stop running tests against node 12 (#486)
|
||||
- [cbefd3e](https://github.com/dubzzz/pure-rand/commit/cbefd3e) 🔧 Better configuration of prettier (#474)
|
||||
- [c6712d3](https://github.com/dubzzz/pure-rand/commit/c6712d3) 🔧 Configure Renovate (#470)
|
||||
21
unified-ai-platform/node_modules/pure-rand/LICENSE
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unified-ai-platform/node_modules/pure-rand/LICENSE
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MIT License
|
||||
|
||||
Copyright (c) 2018 Nicolas DUBIEN
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
208
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<h1>
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||||
<img src="https://raw.githubusercontent.com/dubzzz/pure-rand/main/assets/logo.svg" alt="pure-rand logo" />
|
||||
</h1>
|
||||
|
||||
Fast Pseudorandom number generators (aka PRNG) with purity in mind!
|
||||
|
||||
[](https://github.com/dubzzz/pure-rand/actions)
|
||||
[](https://badge.fury.io/js/pure-rand)
|
||||
[](https://www.npmjs.com/package/pure-rand)
|
||||
|
||||
[](https://codecov.io/gh/dubzzz/pure-rand)
|
||||
[](https://packagequality.com/#?package=pure-rand)
|
||||
[](https://snyk.io/advisor/npm-package/pure-rand)
|
||||
|
||||
[](https://github.com/dubzzz/pure-rand/labels/good%20first%20issue)
|
||||
[](https://github.com/dubzzz/pure-rand/blob/main/LICENSE)
|
||||
[](https://twitter.com/intent/tweet?text=Check%20out%20pure-rand%20by%20%40ndubien%20https%3A%2F%2Fgithub.com%2Fdubzzz%2Fpure-rand%20%F0%9F%91%8D)
|
||||
|
||||
## Getting started
|
||||
|
||||
**Install it in node via:**
|
||||
|
||||
`npm install pure-rand` or `yarn add pure-rand`
|
||||
|
||||
**Use it in browser by doing:**
|
||||
|
||||
`import * as prand from 'https://unpkg.com/pure-rand/lib/esm/pure-rand.js';`
|
||||
|
||||
## Usage
|
||||
|
||||
**Simple usage**
|
||||
|
||||
```javascript
|
||||
import prand from 'pure-rand';
|
||||
|
||||
const seed = 42;
|
||||
const rng = prand.xoroshiro128plus(seed);
|
||||
const firstDiceValue = prand.unsafeUniformIntDistribution(1, 6, rng); // value in {1..6}, here: 2
|
||||
const secondDiceValue = prand.unsafeUniformIntDistribution(1, 6, rng); // value in {1..6}, here: 4
|
||||
const thirdDiceValue = prand.unsafeUniformIntDistribution(1, 6, rng); // value in {1..6}, here: 6
|
||||
```
|
||||
|
||||
**Pure usage**
|
||||
|
||||
Pure means that the instance `rng` will never be altered in-place. It can be called again and again and it will always return the same value. But it will also return the next `rng`. Here is an example showing how the code above can be translated into its pure version:
|
||||
|
||||
```javascript
|
||||
import prand from 'pure-rand';
|
||||
|
||||
const seed = 42;
|
||||
const rng1 = prand.xoroshiro128plus(seed);
|
||||
const [firstDiceValue, rng2] = prand.uniformIntDistribution(1, 6, rng1); // value in {1..6}, here: 2
|
||||
const [secondDiceValue, rng3] = prand.uniformIntDistribution(1, 6, rng2); // value in {1..6}, here: 4
|
||||
const [thirdDiceValue, rng4] = prand.uniformIntDistribution(1, 6, rng3); // value in {1..6}, here: 6
|
||||
|
||||
// You can call: prand.uniformIntDistribution(1, 6, rng1);
|
||||
// over and over it will always give you back the same value along with a new rng (always producing the same values too).
|
||||
```
|
||||
|
||||
**Independent simulations**
|
||||
|
||||
In order to produce independent simulations it can be tempting to instanciate several PRNG based on totally different seeds. While it would produce distinct set of values, the best way to ensure fully unrelated sequences is rather to use jumps. Jump just consists into moving far away from the current position in the generator (eg.: jumping in Xoroshiro 128+ will move you 2<sup>64</sup> generations away from the current one on a generator having a sequence of 2<sup>128</sup> elements).
|
||||
|
||||
```javascript
|
||||
import prand from 'pure-rand';
|
||||
|
||||
const seed = 42;
|
||||
const rngSimulation1 = prand.xoroshiro128plus(seed);
|
||||
const rngSimulation2 = rngSimulation1.jump(); // not in-place, creates a new instance
|
||||
const rngSimulation3 = rngSimulation2.jump(); // not in-place, creates a new instance
|
||||
|
||||
const diceSim1Value = prand.unsafeUniformIntDistribution(1, 6, rngSimulation1); // value in {1..6}, here: 2
|
||||
const diceSim2Value = prand.unsafeUniformIntDistribution(1, 6, rngSimulation2); // value in {1..6}, here: 5
|
||||
const diceSim3Value = prand.unsafeUniformIntDistribution(1, 6, rngSimulation3); // value in {1..6}, here: 6
|
||||
```
|
||||
|
||||
**Non-uniform usage**
|
||||
|
||||
While not recommended as non-uniform distribution implies that one or several values from the range will be more likely than others, it might be tempting for people wanting to maximize the throughput.
|
||||
|
||||
```javascript
|
||||
import prand from 'pure-rand';
|
||||
|
||||
const seed = 42;
|
||||
const rng = prand.xoroshiro128plus(seed);
|
||||
const rand = (min, max) => {
|
||||
const out = (rng.unsafeNext() >>> 0) / 0x100000000;
|
||||
return min + Math.floor(out * (max - min + 1));
|
||||
};
|
||||
const firstDiceValue = rand(1, 6); // value in {1..6}, here: 6
|
||||
```
|
||||
|
||||
**Select your seed**
|
||||
|
||||
While not perfect, here is a rather simple way to generate a seed for your PNRG.
|
||||
|
||||
```javascript
|
||||
const seed = Date.now() ^ (Math.random() * 0x100000000);
|
||||
```
|
||||
|
||||
## Documentation
|
||||
|
||||
### Pseudorandom number generators
|
||||
|
||||
In computer science most random number generators<sup>(1)</sup> are [pseudorandom number generators](https://en.wikipedia.org/wiki/Pseudorandom_number_generator) (abbreviated: PRNG). In other words, they are fully deterministic and given the original seed one can rebuild the whole sequence.
|
||||
|
||||
Each PRNG algorithm has to deal with tradeoffs in terms of randomness quality, speed, length of the sequence<sup>(2)</sup>... In other words, it's important to compare relative speed of libraries with that in mind. Indeed, a Mersenne Twister PRNG will not have the same strenghts and weaknesses as a Xoroshiro PRNG, so depending on what you need exactly you might prefer one PRNG over another even if it will be slower.
|
||||
|
||||
4 PRNGs come with pure-rand:
|
||||
|
||||
- `congruential32`: Linear Congruential generator — \[[more](https://en.wikipedia.org/wiki/Linear_congruential_generator)\]
|
||||
- `mersenne`: Mersenne Twister generator — \[[more](https://en.wikipedia.org/wiki/Mersenne_Twister)\]
|
||||
- `xorshift128plus`: Xorshift 128+ generator — \[[more](https://en.wikipedia.org/wiki/Xorshift)\]
|
||||
- `xoroshiro128plus`: Xoroshiro 128+ generator — \[[more](https://en.wikipedia.org/wiki/Xorshift)\]
|
||||
|
||||
Our recommendation is `xoroshiro128plus`. But if you want to use another one, you can replace it by any other PRNG provided by pure-rand in the examples above.
|
||||
|
||||
### Distributions
|
||||
|
||||
Once you are able to generate random values, next step is to scale them into the range you want. Indeed, you probably don't want a floating point value between 0 (included) and 1 (excluded) but rather an integer value between 1 and 6 if you emulate a dice or any other range based on your needs.
|
||||
|
||||
At this point, simple way would be to do `min + floor(random() * (max - min + 1))` but actually it will not generate the values with equal probabilities even if you use the best PRNG in the world to back `random()`. In order to have equal probabilities you need to rely on uniform distributions<sup>(3)</sup> which comes built-in in some PNRG libraries.
|
||||
|
||||
pure-rand provides 3 built-in functions for uniform distributions of values:
|
||||
|
||||
- `uniformIntDistribution(min, max, rng)`
|
||||
- `uniformBigIntDistribution(min, max, rng)` - with `min` and `max` being `bigint`
|
||||
- `uniformArrayIntDistribution(min, max, rng)` - with `min` and `max` being instances of `ArrayInt = {sign, data}` ie. sign either 1 or -1 and data an array of numbers between 0 (included) and 0xffffffff (included)
|
||||
|
||||
And their unsafe equivalents to change the PRNG in-place.
|
||||
|
||||
### Extra helpers
|
||||
|
||||
Some helpers are also provided in order to ease the use of `RandomGenerator` instances:
|
||||
|
||||
- `prand.generateN(rng: RandomGenerator, num: number): [number[], RandomGenerator]`: generates `num` random values using `rng` and return the next `RandomGenerator`
|
||||
- `prand.skipN(rng: RandomGenerator, num: number): RandomGenerator`: skips `num` random values and return the next `RandomGenerator`
|
||||
|
||||
## Comparison
|
||||
|
||||
### Summary
|
||||
|
||||
The chart has been split into three sections:
|
||||
|
||||
- section 1: native `Math.random()`
|
||||
- section 2: without uniform distribution of values
|
||||
- section 3: with uniform distribution of values (not supported by all libraries)
|
||||
|
||||
<img src="https://raw.githubusercontent.com/dubzzz/pure-rand/main/perf/comparison.svg" alt="Comparison against other libraries" />
|
||||
|
||||
### Process
|
||||
|
||||
In order to compare the performance of the libraries, we aked them to shuffle an array containing 1,000,000 items (see [code](https://github.com/dubzzz/pure-rand/blob/556ec331c68091c5d56e9da1266112e8ea222b2e/perf/compare.cjs)).
|
||||
|
||||
We then split the measurements into two sections:
|
||||
|
||||
- one for non-uniform distributions — _known to be slower as it implies re-asking for other values to the PRNG until the produced value fall into the acceptable range of values_
|
||||
- one for uniform distributions
|
||||
|
||||
The recommended setup for pure-rand is to rely on our Xoroshiro128+. It provides a long enough sequence of random values, has built-in support for jump, is really efficient while providing a very good quality of randomness.
|
||||
|
||||
### Performance
|
||||
|
||||
**Non-Uniform**
|
||||
|
||||
| Library | Algorithm | Mean time (ms) | Compared to pure-rand |
|
||||
| ------------------------ | ----------------- | -------------- | --------------------- |
|
||||
| native \(node 16.19.1\) | Xorshift128+ | 33.3 | 1.4x slower |
|
||||
| **pure-rand _@6.0.0_** | **Xoroshiro128+** | **24.5** | **reference** |
|
||||
| pure-rand _@6.0.0_ | Xorshift128+ | 25.0 | similar |
|
||||
| pure-rand _@6.0.0_ | Mersenne Twister | 30.8 | 1.3x slower |
|
||||
| pure-rand _@6.0.0_ | Congruential | 22.6 | 1.1x faster |
|
||||
| seedrandom _@3.0.5_ | Alea | 28.1 | 1.1x slower |
|
||||
| seedrandom _@3.0.5_ | Xorshift128 | 28.8 | 1.2x slower |
|
||||
| seedrandom _@3.0.5_ | Tyche-i | 28.6 | 1.2x slower |
|
||||
| seedrandom _@3.0.5_ | Xorwow | 32.0 | 1.3x slower |
|
||||
| seedrandom _@3.0.5_ | Xor4096 | 32.2 | 1.3x slower |
|
||||
| seedrandom _@3.0.5_ | Xorshift7 | 33.5 | 1.4x slower |
|
||||
| @faker-js/faker _@7.6.0_ | Mersenne Twister | 109.1 | 4.5x slower |
|
||||
| chance _@1.1.10_ | Mersenne Twister | 142.9 | 5.8x slower |
|
||||
|
||||
**Uniform**
|
||||
|
||||
| Library | Algorithm | Mean time (ms) | Compared to pure-rand |
|
||||
| ---------------------- | ----------------- | -------------- | --------------------- |
|
||||
| **pure-rand _@6.0.0_** | **Xoroshiro128+** | **53.5** | **reference** |
|
||||
| pure-rand _@6.0.0_ | Xorshift128+ | 52.2 | similar |
|
||||
| pure-rand _@6.0.0_ | Mersenne Twister | 61.6 | 1.2x slower |
|
||||
| pure-rand _@6.0.0_ | Congruential | 57.6 | 1.1x slower |
|
||||
| random-js @2.1.0 | Mersenne Twister | 119.6 | 2.2x slower |
|
||||
|
||||
> System details:
|
||||
>
|
||||
> - OS: Linux 5.15 Ubuntu 22.04.2 LTS 22.04.2 LTS (Jammy Jellyfish)
|
||||
> - CPU: (2) x64 Intel(R) Xeon(R) Platinum 8272CL CPU @ 2.60GHz
|
||||
> - Memory: 5.88 GB / 6.78 GB
|
||||
> - Container: Yes
|
||||
> - Node: 16.19.1 - /opt/hostedtoolcache/node/16.19.1/x64/bin/node
|
||||
>
|
||||
> _Executed on default runners provided by GitHub Actions_
|
||||
|
||||
---
|
||||
|
||||
(1) — Not all as there are also [hardware-based random number generator](https://en.wikipedia.org/wiki/Hardware_random_number_generator).
|
||||
|
||||
(2) — How long it takes to reapeat itself?
|
||||
|
||||
(3) — While most users don't really think of it, uniform distribution is key! Without it entries might be biased towards some values and make some others less probable. The naive `rand() % numValues` is a good example of biased version as if `rand()` is uniform in `0, 1, 2` and `numValues` is `2`, the probabilities are: `P(0) = 67%`, `P(1) = 33%` causing `1` to be less probable than `0`
|
||||
Reference in New Issue
Block a user