Metadata-Version: 2.4
Name: uadapy
Version: 0.1.0
Summary: A software package for uncertainty-aware data analysis with Python
Author: David Hägele, Marina Evers, Patrick Paetzold, Ruben Bauer, Nikhil Bhavikatti
License: MIT License
        
        Copyright (c) 2024, UADAPy Dev Team
        Copyright (c) 2024, Visualization Research Center (VISUS), University of Stuttgart
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/UniStuttgart-VISUS/uadapy
Project-URL: Bug Tracker, https://github.com/UniStuttgart-VISUS/uadapy/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: scikit-learn
Requires-Dist: numba
Requires-Dist: glasbey
Requires-Dist: seaborn
Requires-Dist: cffi
Dynamic: license-file

# UADAPy - Uncertainty-aware Data Analysis with Python
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

![Teaser image](https://raw.githubusercontent.com/UniStuttgart-VISUS/uadapy/main/image.png)

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

## Installation
So far the library is very much work in progress, but you can already use it via pip:
```
pip install uadapy
```

## Documentation
You can find the documentation here: https://unistuttgart-visus.github.io/uadapy/

## Citation
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}}
```
