https://github.com/saehm/DruidJS

A JavaScript Library for Dimensionality Reduction
https://github.com/saehm/DruidJS

clustering dimensionality-reduction fastmap isomap javascript-library lle ltsa matrix mds pca t-sne umap unsupervised-learning

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A JavaScript Library for Dimensionality Reduction

• Host: GitHub
• URL: https://github.com/saehm/DruidJS
• Owner: saehm
• Created: 2019-08-27T11:37:10.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-09-26T16:42:50.000Z (3 months ago)
• Last Synced: 2024-11-08T13:06:15.058Z (about 1 month ago)
• Topics: clustering, dimensionality-reduction, fastmap, isomap, javascript-library, lle, ltsa, matrix, mds, pca, t-sne, umap, unsupervised-learning
• Language: JavaScript
• Homepage:
• Size: 6.18 MB
• Stars: 112
• Watchers: 7
• Forks: 10
• Open Issues: 12
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-dataviz-education - DruidJS
• awesome-viz - DruidJS - DruidJS is a JavaScript library for dimensionality reduction. With dimesionality reduction you can project high-dimensional data to a lower dimensionality while keeping method-specific properties of the data. DruidJS makes it easy to project a dataset with the implemented dimensionality reduction methods. ([↑](#contents) Data Analytics)

README

        
## DruidJS — A JavaScript Library for Dimensionality Reduction.



DruidJS is a JavaScript library for dimensionality reduction. 

With dimesionality reduction you can project high-dimensional data to a lower dimensionality while keeping method-specific properties of the data.

DruidJS makes it easy to project a dataset with the implemented dimensionality reduction methods.




### Resources

```

@inproceedings{cutura2020druid,

  title={{DRUIDJS — A JavaScript Library for Dimensionality Reduction}},

  author={Cutura, Rene and Kralj, Christoph and Sedlmair, Michael},

  booktitle={2020 IEEE Visualization Conference (VIS)},

  pages={111--115},

  year={2020},

  organization={IEEE}

}

```

- [Documentation](https://saehm.github.io/DruidJS/index.html) 

- [Demo](https://renecutura.eu/druid_demo)

- [Conference Talk](https://youtu.be/bi6FfsWV_9k?t=2463) [IEEEVIS2020](http://ieeevis.org/year/2020/welcome)

### Installation

If you use npm, install with `npm install @saehrimnir/druidjs`, and use it with

```js

import * as druid from "@saehrimnir/druidjs";

```

Otherwise download the files [here](https://github.com/saehm/DruidJS/releases/latest), or use for instance [unpkg](https://unpkg.com/@saehrimnir/druidjs) this way:

```html

```

### Matrix

DruidJS uses internally the Matrix class for storing data. You can use it by creating a `druid.Matrix` object for instance with the function `from`, in example:

```js

    import * as druid from '@saehrimnir/druidjs';

    let data = [[...], [...], ...];

    let matrix = druid.Matrix.from(data);

```

You can create a `druid.Matrix` object programmatically by:

```js

    let fn = (row, col) => row == col ? 1 : 0;

    let matrix = new druid.Matrix(rows, columns, fn);

```

If `rows == columns`, then `matrix` would be a identity matrix.

A shortcut for a identity matrix is:

```js

    let matrix = new druid.Matrix(rows, columns, "I");

    // or

    let matrix = new druid.Matrix(rows, columnbs, "identity");

```

There are more shortcuts for creating matrices:

```js

    let matrix = new druid.Matrix(3, 3, "zeros"); // matrix would be a 3x3 matrix with zeroes

    let matrix = new druid.Matrix(3, 3, "center"); // matrix would be a 3x3 center matrix;

    let number = 12;

    let matrix = new druid.Matrix(3, 3, number); // matrix would b a 3x3 matrix filled with 'number'

```

If you want to use a `druid.Matrix` object, for instance, with [d3](https://d3js.org), you can use either the `to2dArray` property, the `iterate_rows` generator function, or just use the `druid.Matrix` object as an iterable (works with d3 since version 6).

```js

    let data = await d3.csv("data.csv");

    let matrix = druid.Matrix.from(data);

    d3.selectAll("datapoints").data(matrix.to2dArray)//...

    d3.selectAll("datapoints").data(matrix.iterate_rows())//...

    d3.selectAll("datapoints").data(matrix)//...

```

### DR methods

#### Transform

[Example](https://observablehq.com/@saehrimnir/hello-druidjs)

#### Generator

[Example](https://observablehq.com/@saehrimnir/hello-druidjs/2)

#### TopoMap Example

[Example](https://observablehq.com/@saehrimnir/topomap)

...