# squirrel-noise

> A typescript implementation of Squirrel Eiserloh's noise based RNG explained at GDC

Latest version **1.0.0** (published 2022-08-18) · SEE LICENSE IN LICENSE.md license · 0 weekly downloads

## Install

```sh
npm install squirrel-noise
pnpm add squirrel-noise
yarn add squirrel-noise
bun add squirrel-noise
```

## Health

**Score 15/100 (F)** — status: abandoned.

Positive: no vulnerabilities.

Warnings: low downloads; no types; no esm support.

Negative: abandoned; low maintenance score.

## Facts

| | |
|---|---|
| Version | 1.0.0 |
| Published | 2022-08-18 |
| First published | 2022-08-18 |
| Weekly downloads | 0 |
| License | SEE LICENSE IN LICENSE.md |
| TypeScript types | none |
| Module format | CommonJS |
| Dependencies | 0 |
| Unpacked size | 21.3 KB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 0 |
| Author | Barthélemy Paléologue |
| Maintainers | barthpaleologue |
| Keywords | random, noise, rng, pseudo-random, squirrel |

## Links

- npm: https://www.npmjs.com/package/squirrel-noise
- Repository: https://github.com/BarthPaleologue/squirrel-noise
- Homepage: https://github.com/BarthPaleologue/squirrel-noise#readme
- Issues: https://github.com/BarthPaleologue/squirrel-noise/issues
- npm.io page: https://npm.io/package/squirrel-noise

## Recent versions

- 1.0.0 (latest) — 2022-08-18

## README

# squirrel-noise

`squirrel-noise` is a typescript implementation of Squirrel Eiserloh's noise based RNG explained at GDC (<a href="https://www.youtube.com/watch?v=LWFzPP8ZbdU">Link</a>).

## Installation

Just use `npm i squirrel-noise` to install the package in your project

## Usage

To use squirrel noise, you can do the following :

```ts 
import { squirrelNoise, seededSquirrelNoise } from "squirrel-noise";

let randomValue = squirrelNoise(seed: number, step: number);

let rng = seededSquirrelNoise(seed: number);
let randomValue2 = rng(step: number);
```

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_Source: https://npm.io/package/squirrel-noise · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._