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}
}
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
After building, adapt the paths in the top of src/graphAlgorithms.py and in the end of src/embedGraph.cpp to your local paths.
The library was last tested with Python 3.11.
We plan to make the algorithm available as a ready-to-use package from PyPI in the future.
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!