UADAPy is a Python library to support an easy analysis of uncertain data.
The library provides:
- uncertainty-aware algorithms for different visualization algorithms, including UAMDS
- easy-to-use visualizations for uncertain data
So far the library is very much work in progress, but you can already use it via pip:
pip install uadapy
You can find the documentation here: https://unistuttgart-visus.github.io/uadapy/
If you use this software in your work, please cite it using the following metadata
@misc{UADAPy,
title={UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox},
author={Patrick Paetzold and David Hägele and Marina Evers and Daniel Weiskopf and Oliver Deussen},
year={2024},
eprint={2409.10217},
archivePrefix={arXiv},
primaryClass={cs.HC},
url={https://arxiv.org/abs/2409.10217},
}