Awesome

Codebase & further details for the paper:

Data Point Selection for Line Chart Visualization: Methodological Assessment and Evidence-Based Guidelines
Jonas Van Der Donckt, Jeroen Van Der Donckt

Preprint: https://arxiv.org/abs/2304.00900 - see cite for bibtex!

How is the repository structured?

• The codebase is located in the agg_utils (python scripts) and notebooks folder.
• Additional details can be found in markdown files in the details folder.
• Supplementary gifs are located in the gifs folder.
• See notebooks README for the more details.
  • The 0.* notebooks contain data parsing and figure generation.
  • The 1.* notebooks perform the core experiments (visual representativeness and visual stability).
  • The varia_* notebooks perform further analysis: OR-conv, toolkit comparison, and M4 pixel-perfect nuances.
• The animations folder contains html animations, which allow to inspect the phenomena in more detail.

Folder structure

├── agg_utils          <- shared codebase for the notebooks
├── animations         <- html animations
├── details            <- additional details in README.md files
├── gifs               <- supplementary gifs
├── loc_data           <- local data folder 
└── notebooks          <- experiment notebooks see notebooks README.md

How to install the requirements?

This repository uses poetry as dependency manager. A specification of the dependencies is provided in the pyproject.toml and poetry.lock files.

You can install the dependencies in your Python environment by executing the following steps;

1. Install poetry: https://python-poetry.org/docs/#installation
2. Activate you poetry environment by calling poetry shell
3. Install the dependencies by calling poetry install

Utilizing this repository

Make sure that you've extended the path_conf.py file's hostname if statement with your machine's hostname and that you've configured the path to the UCR archive folder.

Cite

@article{van2023data,
  title={Data Point Selection for Line Chart Visualization: Methodological Assessment and Evidence-Based Guidelines},
  author={Van Der Donckt, Jonas and Van Der Donckt, Jeroen and Rademaker, Michael and Van Hoecke, Sofie},
  journal={arXiv preprint arXiv:2304.00900},
  year={2023}
}