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
@INPROCEEDINGS{UADAPy,
author={Paetzold, Patrick and Hägele, David and Evers, Marina and Weiskopf, Daniel and Deussen, Oliver},
booktitle={2024 IEEE Workshop on Uncertainty Visualization: Applications, Techniques, Software, and Decision Frameworks},
title={UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox},
year={2024},
volume={},
number={},
pages={48-50},
keywords={Uncertainty;Data analysis;Software packages;Conferences;Software algorithms;Pipelines;Data visualization;Python;Uncertainty visualization;software toolbox},
doi={10.1109/UncertaintyVisualization63963.2024.00011}}