This dataset contains the data and code for the publication: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples.

Code Repository A dynamic version of the code repository can be found at https://github.com/rbnbr/VoroParaSense. The version presented in this dataset corresponds to the version used in the corresponding paper (referenced as v1.0.0) and does not contain post-publication changes to the repository.

Figures

Some of the figures contained in the Jupyter Notebooks were used to generate the CC BY 4.0 licensed figures in https://doi.org/10.1111/cgf.70122. The figures here are the raw .png figures. The published figures are mostly vector graphics and were slightly modified compared to the figures rendered in the Jupyter notebooks.

Author: Ruben Bauer 
Source: https://doi.org/10.1111/cgf.70122 
License: CC BY 4.0

The figures of the main paper are:

examples\notebooks\plot_examples\two_d_clipping_and_distribution.ipynb used to generate Figure 2 examples\notebooks\plot_examples\three_dimensional_case.ipynb used to generate Figure 3 examples\notebooks\plot_examples\two_d_clipping_and_distribution.ipynb used to generate Figure 4 examples\notebooks\plot_examples\two_d_major_transition_directions.ipynb used to generate Figure 5 examples\notebooks\single_dataset_convenience_plots\iris_conv_plot.ipynb used to generate Figure 6, 7, 8, 9, 10, 12 examples\notebooks\plot_examples\space_dividing_line.ipynb used to generate Figure 11 examples\notebooks\single_dataset_convenience_plots\semiconductor_conv_plot.ipynb used to generate Figure 14 examples\notebooks\single_dataset_convenience_plots\droplet_impact_conv_plot.ipynb used to generate Figure 15, 16

For the supplemental material:

examples\notebooks\plot_examples\normal_vectors_angle_vis.ipynb used to generate Figure 1 examples\notebooks\plot_examples\plane_plane_distance.ipynb used to generate Figure 2 examples\notebooks\plot_examples\runtime_experiments_2.ipynb used to generate Figure 3, 4 examples\notebooks\plot_examples\bandwidth_experiments.ipynb used to generate Figure 5 - 15

Install

Tested with Python 3.12.3.

Setup virtual environment with Python: python -m venv .venv Activate the environment, then install the requirements via: pip install -r requirements.txt Run python ./main.py to run the main example.

Use persistent identifiers from Software Heritage (

) to cite individual files or even lines of the source code.