https://github.com/clugen/MOCluGen

Multidimensional cluster generation in MATLAB/Octave
https://github.com/clugen/MOCluGen

gnu-octave gnu-octave-toolbox matlab matlab-toolbox multidimensional-clusters multidimensional-data octave octave-toolbox synthetic-clusters synthetic-data-generator synthetic-dataset-generation

Last synced: 18 days ago
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Multidimensional cluster generation in MATLAB/Octave

• Host: GitHub
• URL: https://github.com/clugen/MOCluGen
• Owner: clugen
• License: mit
• Created: 2020-08-20T15:16:42.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2024-08-05T19:08:09.000Z (over 1 year ago)
• Last Synced: 2025-09-05T06:43:38.491Z (3 months ago)
• Topics: gnu-octave, gnu-octave-toolbox, matlab, matlab-toolbox, multidimensional-clusters, multidimensional-data, octave, octave-toolbox, synthetic-clusters, synthetic-data-generator, synthetic-dataset-generation
• Language: MATLAB
• Homepage: https://clugen.github.io/MOCluGen/
• Size: 11.3 MB
• Stars: 5
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: CITATION.cff

Awesome Lists containing this project

• awesome-MATLAB - MOCluGen - Multidimensional cluster generation in MATLAB/Octave. (Miscellaneous Free Toolboxes)

README

          
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# MOCluGen

## Summary

**MOCluGen** is a MATLAB/Octave implementation of the *clugen* algorithm for

generating multidimensional clusters with arbitrary distributions. Each cluster

is supported by a line segment, the position, orientation and length of which

guide where the respective points are placed.

See the [documentation](https://clugen.github.io/MOCluGen/) and

[examples](https://clugen.github.io/MOCluGen/examples/) for more details.

## Install and use

Download the most recent version from the

[releases](https://github.com/clugen/MOCluGen/releases/latest) page or clone the

development version with following command:

```text

$ git clone https://github.com/clugen/MOCluGen.git

```

Open MATLAB or GNU Octave and `cd` into the project's folder, and run the

`startup.m` script:

```matlab

>> startup

```

**MOCluGen** can now be used, e.g:

```matlab

>> o = clugen(2, 4, 400, [1 0], pi / 8, [50, 10], 20, 1, 2, 'seed', 123);

>> scatter(o.points(:, 1), o.points(:, 2), 36, o.clusters, 'filled', 'MarkerEdgeColor', 'k');

```

![Example 2D](https://github.com/clugen/.github/blob/main/images/example2d_moc.png?raw=true)

```matlab

>> o = clugen(3, 4, 1000, [1 0 0], pi / 8, [20 15 25], 16, 4, 3.5, 'seed', 123);

>> scatter3(o.points(:, 1), o.points(:, 2), o.points(:, 3), 36, o.clusters, 'filled', 'MarkerEdgeColor', 'k');

```

![Example 3D](https://github.com/clugen/.github/blob/main/images/example3d_moc.png?raw=true)

## See also

* [pyclugen](https://github.com/clugen/pyclugen/), a Python implementation of

  the *clugen* algorithm.

* [CluGen.jl](https://github.com/clugen/CluGen.jl/), a Julia implementation of

  the *clugen* algorithm.

* [clugenr](https://github.com/clugen/clugenr/), an R implementation

  of the *clugen* algorithm.

## Reference

If you use this software, please cite the following reference:

* Fachada, N. & de Andrade, D. (2023). Generating multidimensional clusters

  with support lines. *Knowledge-Based Systems*, 277, 110836.

  

  ([arXiv preprint](https://doi.org/10.48550/arXiv.2301.10327))

## License

[MIT License](LICENSE)