pyMARS

pyMARS: automatically reducing chemical kinetic models in Python - Published in JOSS (2019)

https://github.com/niemeyer-research-group/pymars

Science Score: 100.0%

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 4 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • Committers with academic emails
    14 of 21 committers (66.7%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Scientific Fields

Engineering Computer Science - 40% confidence
Last synced: 6 months ago · JSON representation ·

Repository

Python-based (chemical kinetic) Model Automatic Reduction Software

Basic Info
Statistics
  • Stars: 63
  • Watchers: 9
  • Forks: 48
  • Open Issues: 20
  • Releases: 3
Created about 10 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation Authors

README.md

pyMARS

DOI JOSS DOI Build Status codecov License Code of Conduct Anaconda-Server Badge

Python-based (chemical kinetic) Model Automatic Reduction Software (pyMARS) implements multiple techniques for reducing the size and complexity of detailed chemical kinetic models.

An installation guide, usage examples, theory details, and API docs are provided in the online documentation: https://Niemeyer-Research-Group.github.io/pyMARS/

pyMARS currently consists of four methods for model reduction:

  1. Directed relation graph (DRG)
  2. Directed relation graph with error propagation (DRGEP)
  3. Path flux analysis (PFA)
  4. Sensitivity analysis (SA)

Sensitivity analysis may be run following one of the first three methods, or directly on the starting model; however, its computational expense is high, and applying this method alone is not recommended.

Installation

pyMARS supports Python 3.7, 3.8, and 3.9, and can be installed easily using conda:

conda install -c cantera cantera
conda install -c niemeyer-research-group pymars

Usage

For detailed usage examples, see the online documentation. Once installed, the list of options can be found with:

pymars --help

pyMARS requires models in the Cantera format. However, running pyMARS with a CHEMKIN file will convert it into a Cantera file. pyMARS also provides the --convert option to convert a given model to/from the CHEMKIN format.

Citation

Please refer to the CITATION file for information about citing pyMARS when used in a scholarly work.

If you use this package as part of a scholarly publication, please consider citing the appropriate theory/method papers in addition to the software itself.

License

pyMARS is released under the MIT license; see LICENSE for details.

Code of Conduct

To ensure an open and welcoming community, pyMARS adheres to a code of conduct adapted from the Contributor Covenant code of conduct.

Please adhere to this code of conduct in any interactions you have in the pyMARS community. It is strictly enforced on all official PyKED repositories, websites, and resources. If you encounter someone violating these terms, please let the project lead (@kyleniemeyer) know via email at kyle.niemeyer@gmail.com and we will address it as soon as possible.

Owner

  • Name: Niemeyer Research Group
  • Login: Niemeyer-Research-Group
  • Kind: organization
  • Email: kyle.niemeyer@oregonstate.edu
  • Location: Corvallis, OR

JOSS Publication

pyMARS: automatically reducing chemical kinetic models in Python
Published
September 08, 2019
Volume 4, Issue 41, Page 1543
Authors
Phillip O. Mestas ORCID
School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR USA 97331
Parker Clayton
School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR USA 97331
Kyle E. Niemeyer ORCID
School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR USA 97331
Editor
Kathryn Huff ORCID
Tags
chemical kinetics model reduction

Citation (CITATION.cff)

cff-version: 1.1.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Mestas
    given-names: Phillip O.
    orcid: https://orcid.org/0000-0003-4379-3592
  - family-names: Clayton
    given-names: Parker
  - family-names: Niemeyer
    given-names: Kyle E.
    orcid: https://orcid.org/0000-0003-4425-7097
title: "pyMARS"
version: 1.1.0
doi: 10.5281/zenodo.3401549
date-released: 2019-09-06

GitHub Events

Total
  • Issues event: 4
  • Watch event: 4
  • Issue comment event: 7
  • Pull request event: 1
  • Fork event: 3
Last Year
  • Issues event: 4
  • Watch event: 4
  • Issue comment event: 7
  • Pull request event: 1
  • Fork event: 3

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 836
  • Total Committers: 21
  • Avg Commits per committer: 39.81
  • Development Distribution Score (DDS): 0.315
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Parker Clayton p****n@c****t 573
Kyle Niemeyer k****r@g****m 164
xMestas p****1@g****m 29
xMestas m****p@f****u 16
xMestas m****p@f****u 10
xMestas m****p@r****u 7
jenzenho 4****o 5
Phillip MestasIII m****p@f****u 5
Shockablooey c****1@g****m 4
Phillip MestasIII m****p@k****u 4
Phillip MestasIII m****p@k****u 3
Phillip MestasIII m****p@o****u 3
Nick n****s@u****u 2
Phillip MestasIII m****p@k****u 2
Phillip MestasIII m****p@k****u 2
xMestas p****s@k****u 2
Phillip MestasIII m****p@r****u 1
Reese Benson b****e@f****u 1
Reese Benson b****e@f****u 1
Nick Curtis a****s 1
Katrin Leinweber k****i@p****e 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 44
  • Total pull requests: 45
  • Average time to close issues: 7 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 18
  • Total pull request authors: 15
  • Average comments per issue: 1.73
  • Average comments per pull request: 1.58
  • Merged pull requests: 29
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 1
  • Average comments per issue: 2.5
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • xMestas (18)
  • jcsutherland (6)
  • shenghuiqin (3)
  • kyleniemeyer (2)
  • skyreflectedinmirrors (2)
  • aeliasMFlab (1)
  • sandeepjella (1)
  • Zyr1ak (1)
  • disihan (1)
  • xyt0808 (1)
  • jerome-braun (1)
  • ajuluc (1)
  • jiweiqi (1)
  • Fraixxer (1)
  • wandadars (1)
Pull Request Authors
  • xMestas (19)
  • kyleniemeyer (9)
  • skyreflectedinmirrors (3)
  • jenzenho (3)
  • jiweiqi (2)
  • sandeepjella (2)
  • tsikes (1)
  • parkerclayton (1)
  • katrinleinweber (1)
  • cailinmoore (1)
  • ajuluc (1)
  • chasestubb (1)
  • anthony-walker (1)
  • kbronstein56 (1)
  • lkthang (1)
Top Labels
Issue Labels
bug (10) enhancement (8) good first issue (6) refactor (3) Documentation (1)
Pull Request Labels
bug (9) enhancement (5) refactor (3) Documentation (1)

Dependencies

setup.py pypi
  • cantera >=2.3.0
  • networkx *
  • numpy *
  • pyyaml >=4.2b1
  • tables *
.github/workflows/pythonpackage.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • codecov/codecov-action v2 composite
  • conda-incubator/setup-miniconda v2.1.1 composite
  • peaceiris/actions-gh-pages v3 composite