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uadapy

Uncertainty-aware Data Analysis with Python

https://github.com/unistuttgart-visus/uadapy

Science Score: 65.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in README
  • ○
    Academic publication links
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    Academic email domains
  • ✓
    Institutional organization owner
    Organization unistuttgart-visus has institutional domain (www.visus.uni-stuttgart.de)
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.2%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Uncertainty-aware Data Analysis with Python

Basic Info
Statistics
  • Stars: 5
  • Watchers: 3
  • Forks: 3
  • Open Issues: 6
  • Releases: 1
Created about 2 years ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

UADAPy - Uncertainty-aware Data Analysis with Python

License: MIT

Teaser image

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}}

Owner

  • Name: University of Stuttgart Visualization Research Center
  • Login: UniStuttgart-VISUS
  • Kind: organization
  • Location: Germany

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Paetzold"
  given-names: "Patrick"
  orcid: "https://orcid.org/0000-0002-1315-4602"
- family-names: "Hägele"
  given-names: "David"
  orcid: "https://orcid.org/0000-0002-2679-6882"
- family-names: "Evers"
  given-names: "Marina"
  orcid: "https://orcid.org/0000-0003-3904-5065"
- family-names: "Weiskopf"
  given-names: "Daniel"
  orcid: "https://orcid.org/0000-0003-1174-1026"
- family-names: "Deussen"
  given-names: "Oliver"
  orcid: "https://orcid.org/0000-0001-5803-2185"
title: "UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox"
repository-code: "https://github.com/UniStuttgart-VISUS/uadapy"
type: software
preferred-citation:
  type: conference-paper
  authors:
  - family-names: "Paetzold"
    given-names: "Patrick"
    orcid: "https://orcid.org/0000-0002-1315-4602"
  - family-names: "Hägele"
    given-names: "David"
    orcid: "https://orcid.org/0000-0002-2679-6882"
  - family-names: "Evers"
    given-names: "Marina"
    orcid: "https://orcid.org/0000-0003-3904-5065"
  - family-names: "Weiskopf"
    given-names: "Daniel"
    orcid: "https://orcid.org/0000-0003-1174-1026"
  - family-names: "Deussen"
    given-names: "Oliver"
    orcid: "https://orcid.org/0000-0001-5803-2185"
  title: "UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox"
  year: 2024
  url: "https://ieeexplore.ieee.org/document/10750138"
  doi: "10.1109/UncertaintyVisualization63963.2024.00011"
  start: 48
  end: 50
  booktitle: "2024 IEEE Workshop on Uncertainty Visualization: Applications, Techniques, Software, and Decision Frameworks"

GitHub Events

Total
  • Create event: 11
  • Issues event: 13
  • Watch event: 3
  • Delete event: 6
  • Issue comment event: 3
  • Push event: 64
  • Gollum event: 3
  • Pull request review event: 13
  • Pull request review comment event: 11
  • Pull request event: 17
  • Fork event: 1
Last Year
  • Create event: 11
  • Issues event: 13
  • Watch event: 3
  • Delete event: 6
  • Issue comment event: 3
  • Push event: 64
  • Gollum event: 3
  • Pull request review event: 13
  • Pull request review comment event: 11
  • Pull request event: 17
  • Fork event: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 18
  • Total pull requests: 20
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 14 days
  • Total issue authors: 2
  • Total pull request authors: 3
  • Average comments per issue: 0.11
  • Average comments per pull request: 0.5
  • Merged pull requests: 16
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 6
  • Pull requests: 13
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 14 days
  • Issue authors: 2
  • Pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.54
  • Merged pull requests: 10
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • marinaevers (14)
  • hageldave (4)
Pull Request Authors
  • nikhilbhavikatti (17)
  • marinaevers (2)
  • Tamir-K (1)
Top Labels
Issue Labels
bug (4) help wanted (4) feature (2) documentation (2) enhancement (1) good first issue (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 9 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 3
pypi.org: uadapy

A software package for uncertainty-aware data analysis with Python

  • Homepage: https://github.com/UniStuttgart-VISUS/uadapy
  • Documentation: https://uadapy.readthedocs.io/
  • 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.
  • Latest release: 0.0.2
    published over 1 year ago
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 9 Last month
Rankings
Dependent packages count: 10.7%
Average: 35.5%
Dependent repos count: 60.2%
Maintainers (3)
hageldave marinaevers PatrickPaetzold
Last synced: 7 months ago

Dependencies

pyproject.toml pypi
  • matplotlib *
  • numba *
  • numpy *
  • scikit-learn *
  • scipy *
requirements.txt pypi
  • matplotlib *
  • numpy *
  • scipy *