PoUnce

PoUnce: A framework for automatized uncertainty quantification simulations on high-performance clusters - Published in JOSS (2023)

https://github.com/jakobbd/pounce

Science Score: 95.0%

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

○
CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
✓
DOI references
Found 3 DOI reference(s) in README and JOSS metadata
○
Academic publication links
✓
Committers with academic emails
5 of 7 committers (71.4%) from academic institutions
○
Institutional organization owner
✓
JOSS paper metadata
Published in Journal of Open Source Software

Scientific Fields

Mathematics Computer Science - 69% confidence

Physics Physical Sciences - 40% confidence

Last synced: 6 months ago · JSON representation

Repository

Basic Info

Host: GitHub
Owner: JakobBD
License: gpl-3.0
Language: Python
Default Branch: master
Size: 1.42 MB

Statistics

Stars: 2
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 1

Created almost 4 years ago · Last pushed about 3 years ago

Metadata Files

Readme Contributing License Codemeta

PoUnce

PoUnce (Propagation Of UNCErtainties) is a framework fully automatized runs of non-intrusive forward UQ simulations. It is designed for efficiency on HPC clusters.

Extending the code and adding an API for your own baseline solver and cluster/scheduler is comparatively simple due to the light-weight nature and modular design of PoUnce. PoUnce therefore hopes to head-start for your own UQ implementation.

Requirements

Required Python packages are given in src/requirements.txt.

Quick start / basic run

Runs are configured using a YAML input file. Example input files are located in the ini folder.

For a test run, go to ini/internal_local and run

python3 ../../src/pounce.py parameter_mlmc.yml

Run progress and results should be printed to stdout, ending with a QoI table and the sentence "PoUnce Finished". Further, results should be written to the file output_double.csv.

Contributors

The authors of PoUnce are:

Jakob Dürrwächter\ Thomas Kuhn\ Fabian Meyer\ Andrea Beck\ Claus-Dieter Munz

License

FLEXI is Copyright (C) 2022, Jakob Dürrwächter, Prof. Dr. Andrea Beck, and Prof. Dr. Claus-Dieter Munz and is released under the terms of the GNU General Public License v3.0. For the full license terms see the included license file license.

Reference / Please cite

References will be added shortly. In the meantime, please cite

A. Beck, J. Dürrwächter, T. Kuhn, F. Meyer, C.-D. Munz, C. Rohde.\ “hp-multilevel Monte Carlo methods for uncertainty quantification of compressible Navier–Stokes equations”. \ SIAM J. Sci. Comput. (Aug. 2020). \ DOI: https://doi.org/10.1137/18M1210575 \

Documentation

Further documentation can be found in the doc folder. The guide can be compiled using pandoc by running

make

Owner

Name: Jakob Duerrwaechter
Login: JakobBD
Kind: user

Repositories: 2
Profile: https://github.com/JakobBD

JOSS Publication

PoUnce: A framework for automatized uncertainty quantification simulations on high-performance clusters

Published

February 15, 2023

DOI

10.21105/joss.04683

Volume 8, Issue 82, Page 4683

Authors

Jakob Duerrwaechter

Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, Germany

Thomas Kuhn
Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, Germany

Fabian Meyer
Institute of Applied Analysis and Numerical Simulation, University of Stuttgart, Germany

Andrea Beck
Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, Germany, The Laboratory of Fluid Dynamics and Technical Flows, Otto von Guericke University Magdeburg, Germany

Claus-Dieter Munz
Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, Germany

Editor

Nikoleta Glynatsi

CodeMeta (codemeta.json)

{
  "@context": "https://raw.githubusercontent.com/codemeta/codemeta/master/codemeta.jsonld",
  "@type": "Code",
  "author": [
    {
      "@id": "0000-0001-8961-5340",
      "@type": "Person",
      "email": "jakob.duerrwaechter@iag.uni-stuttgart.de",
      "name": "Jakob Duerrwaechter",
      "affiliation": "University of Stuttgart"
    },
    {
      "@id": "",
      "@type": "Person",
      "email": "thomas.kuhn@iag.uni-stuttgart.de",
      "name": "Thomas Kuhn",
      "affiliation": "University of Stuttgart"
    },
    {
      "@id": "",
      "@type": "Person",
      "email": "fabian.meyer@mathematik.uni-stuttgart.de",
      "name": "Fabian Meyer",
      "affiliation": "University of Stuttgart"
    },
    {
      "@id": "",
      "@type": "Person",
      "email": "beck@iag.uni-stuttgart.de",
      "name": "Andrea Beck",
      "affiliation": "University of Stuttgart"
    },
    {
      "@id": "",
      "@type": "Person",
      "email": "munz@iag.uni-stuttgart.de",
      "name": "Claus-Dieter Munz",
      "affiliation": "University of Stuttgart"
    }
  ],
  "identifier": "",
  "codeRepository": "https://github.com/JakobBD/pounce",
  "datePublished": "2022-07-29",
  "dateModified": "2022-07-29",
  "dateCreated": "2022-07-29",
  "description": "A Python framework for fully automatized runs of non-intrusive forward uncertainty quantification (UQ) simulations on high performance computers",
  "keywords": "uncertainty quantification, high performance computing, Python",
  "license": "GPL v3.0",
  "title": "PoUnce",
  "version": ""
}

GitHub Events

Total

Last Year

Committers

Last synced: 7 months ago

All Time

Total Commits: 291
Total Committers: 7
Avg Commits per committer: 41.571
Development Distribution Score (DDS): 0.261

Past Year

Commits: 0
Committers: 0
Avg Commits per committer: 0.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Jakob Duerrwaechter	i**r@i**e	215
Your Name	y**u@e**m	45
thomas	i**n@i**e	19
Fabian Meyer	f**r@m**e	8
Daniel S. Katz	d**z@i**g	2
Albert Krewinkel	a**t@z**e	1
Jakob Duerrwaechter	i**r@s**t	1

Committer Domains (Top 20 + Academic)

iagpc151.iag.uni-stuttgart.de: 2 siegfried.iag.uni-stuttgart: 1 zeitkraut.de: 1 ieee.org: 1 mathematik.uni-stuttgart.de: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 0
Total pull requests: 2
Average time to close issues: N/A
Average time to close pull requests: about 1 hour
Total issue authors: 0
Total pull request authors: 2
Average comments per issue: 0
Average comments per pull request: 0.0
Merged pull requests: 2
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

Pull Request Authors

tarleb (1)
danielskatz (1)

Top Labels

Issue Labels

Pull Request Labels

Dependencies

externals/demonstrators/requirements.txt pypi

h5py *
mpi4py *
numpy *

src/requirements.txt pypi

PyYAML *
chaospy *
h5py *
inflection *
matplotlib *
numpy *
parse *
prettytable *
scipy *

.github/workflows/draft-pdf.yml actions

actions/checkout v2 composite
actions/upload-artifact v1 composite
openjournals/openjournals-draft-action master composite

.github/workflows/python-app.yml actions

actions/checkout v3 composite
actions/setup-python v3 composite
mpi4py/setup-mpi v1 composite

PoUnce

Science Score: 95.0%

Scientific Fields

Repository

Basic Info

Statistics

Metadata Files

README.md

PoUnce

Requirements

Quick start / basic run

Contributors

License

Reference / Please cite

Documentation

Owner

JOSS Publication

PoUnce: A framework for automatized uncertainty quantification simulations on high-performance clusters

Authors

Editor

Tags

CodeMeta (codemeta.json)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Dependencies