# ml-affine-transform

> Get and apply affine transform to 2D points.

Latest version **1.0.3** (published 2023-06-15) · MIT license · 0 weekly downloads

## Install

```sh
npm install ml-affine-transform
pnpm add ml-affine-transform
yarn add ml-affine-transform
bun add ml-affine-transform
```

## Health

**Score 30/100 (F)** — status: abandoned.

Positive: has types; esm support; no vulnerabilities; high quality score.

Warnings: low downloads.

Negative: abandoned; low maintenance score.

## Facts

| | |
|---|---|
| Version | 1.0.3 |
| Published | 2023-06-15 |
| First published | 2023-06-08 |
| Weekly downloads | 0 |
| License | MIT |
| TypeScript types | bundled |
| Module format | ESM + CommonJS |
| Dependencies | 1 |
| Unpacked size | 37.4 KB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| Author | Océane Patiny |
| Maintainers | mljs-bot |
| Keywords | affine transformation, image registration, 2D transform |

## Links

- npm: https://www.npmjs.com/package/ml-affine-transform
- Repository: https://github.com/mljs/affine-transform
- Homepage: https://github.com/mljs/affine-transform#readme
- Issues: https://github.com/mljs/affine-transform/issues
- npm.io page: https://npm.io/package/ml-affine-transform

## Dependencies (1)

- [ml-matrix](https://npm.io/package/ml-matrix.md) ^6.10.4

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## Recent versions

- 1.0.3 (latest) — 2023-06-15
- 1.0.2 — 2023-06-08
- 1.0.1 — 2023-06-08
- 1.0.0 — 2023-06-08

## README

# affine-transform

[![NPM version][npm-image]][npm-url]
[![build status][ci-image]][ci-url]
[![Test coverage][codecov-image]][codecov-url]
[![npm download][download-image]][download-url]

Get and apply affine transform to 2D points.

## Installation

`$ npm i ml-affine-transform`

## Main steps of the algorithm to get the affine transform

Based on the tutorial: https://nghiaho.com/?page_id=671

1. Find centroids of the two point sets and deduce the translation from one to the other
2. Find rotation using SVD

When the transform is applied to a function, the operations are made in the following order:

1. Rotate
2. Scale
3. Translate

## API

The inputs of the functions are 3xN matrices consisting of the source and the destination points. The third dimension for Z must be padded with ones. The output is an object containing the x and y translations as well as the anti-clockwise angle in degrees.

```ts
export interface AffineTransformParameters {
  rotation: number;
  translation: { x: number; y: number };
  scale: number;
}

export function getAffineTransform(
  source: Matrix,
  destination: Matrix,
): AffineTransformParameters;
```

## Coordinates system

In this project, standard x and y axes are used, as in mathematics (y pointing up and x to the right). The angles are expressed in degrees and positive angles are in the anti-clockwise direction.

## Example

```js
import Matrix from 'ml-matrix';
import { getAffineTransform } from '../getAffineTransform';

const sourceMatrix = new Matrix([
  [1, 1, -3], // x
  [2, -1, -1], // y
  [1, 1, 1], // z
]);
const destinationMatrix = new Matrix([
  [4, -2, -2],
  [-2, -2, 6],
  [1, 1, 1],
]);

const result = getAffineTransform(sourceMatrix, destinationMatrix);

// result = {
//   translation: { x: 0, y: 0 },
//   scale: 2,
//   rotation: -90,
// }
```

## License

[MIT](./LICENSE)

[npm-image]: https://img.shields.io/npm/v/ml-affine-transform.svg
[npm-url]: https://www.npmjs.com/package/ml-affine-transform
[ci-image]: https://github.com/mljs/affine-transform/workflows/Node.js%20CI/badge.svg?branch=main
[ci-url]: https://github.com/mljs/affine-transform/actions?query=workflow%3A%22Node.js+CI%22
[codecov-image]: https://img.shields.io/codecov/c/github/mljs/affine-transform.svg
[codecov-url]: https://codecov.io/gh/mljs/affine-transform
[download-image]: https://img.shields.io/npm/dm/ml-affine-transform.svg
[download-url]: https://www.npmjs.com/package/ml-affine-transform

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