https://github.com/clugen/pyclugen

Multidimensional cluster generation in Python
https://github.com/clugen/pyclugen

multidimensional-clusters multidimensional-data python python-library python3-library synthetic-clusters synthetic-data-generator synthetic-dataset-generation

Last synced: 4 months ago
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Multidimensional cluster generation in Python

• Host: GitHub
• URL: https://github.com/clugen/pyclugen
• Owner: clugen
• License: mit
• Created: 2020-08-22T19:52:09.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2025-07-01T19:34:55.000Z (8 months ago)
• Last Synced: 2025-07-01T19:40:55.322Z (8 months ago)
• Topics: multidimensional-clusters, multidimensional-data, python, python-library, python3-library, synthetic-clusters, synthetic-data-generator, synthetic-dataset-generation
• Language: Python
• Homepage: https://clugen.github.io/pyclugen/
• Size: 21 MB
• Stars: 9
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt
  • Citation: CITATION.cff

Awesome Lists containing this project

• fucking-awesome-machine-learning - pyclugen - Multidimensional cluster generation in Python. (Python / General-Purpose Machine Learning)
• awesome-machine-learning - pyclugen - Multidimensional cluster generation in Python. (Python / General-Purpose Machine Learning)

README

          
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# pyclugen

**pyclugen** is a Python 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/pyclugen/) and

[examples](https://clugen.github.io/pyclugen/generated/gallery/) for more

details.

## Installation

Install from PyPI:

```sh

pip install --upgrade pip

pip install pyclugen

```

Or directly from GitHub:

```text

pip install --upgrade pip

pip install git+https://github.com/clugen/pyclugen.git#egg=pyclugen

```

## Quick start

```python

from pyclugen import clugen

import matplotlib.pyplot as plt

```

```python

out2 = clugen(2, 4, 400, [1, 0], 0.4, [50, 10], 20, 1, 2)

plt.scatter(out2.points[:, 0], out2.points[:, 1], c=out2.clusters)

plt.show()

```

![2D example.](https://github.com/clugen/.github/blob/main/images/example2d_python.png?raw=true)

```python

out3 = clugen(3, 5, 10000, [0.5, 0.5, 0.5], 0.2, [10, 10, 10], 10, 1, 2)

fig = plt.figure()

ax = fig.add_subplot(projection="3d")

ax.scatter(out3.points[:, 0], out3.points[:, 1], out3.points[:, 2], c=out3.clusters)

plt.show()

```

![3D example.](https://github.com/clugen/.github/blob/main/images/example3d_python.png?raw=true)

## See also

* [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.

* [MOCluGen](https://github.com/clugen/MOCluGen/), a MATLAB/Octave

  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.txt)