Segmentation Embeddings

Segmentation Embeddings can be used to embed multidimensional partitionings or segmentations to the 2D space. Shows the multidimensional visualization in a 2D space while preserving the topology and optimizing the relative area and boundary sizes of the segments.

More information can be found in the paper 2D Embeddings of Multi-dimensional Partitionings by Marina Evers and Lars Linsen.

If you use our approach, please cite our paper.

Evers, M. and Linsen, L. (2024), 2D Embeddings of Multi-dimensional Partitionings. IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/TVCG.2024.3456394

@article{evers20242d,
  title={2D Embeddings of Multi-dimensional Partitionings},
  author={Evers, Marina and Linsen, Lars},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  year={2024},
  publisher={IEEE}
}

Requirements

You can install the necessary dependencies using

pip install -r requirements.txt

You also need to install the Open Graph Drawing Framework (https://ogdf.uos.de/). You can get their code here: https://github.com/ogdf/ogdf Before building the project, add the file EmbedderBoundaryCycle.h to their project.

We plan to make the algorithm available as a ready-to-use package from PyPI in the future.

How to Run?

For running an example on the artificial dataset, just run

python src/run.py

If you have any questions, do not hesitate to reach out!