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ProgPy

ProgPy: Python Packages for Prognostics and Health Management of Engineering Systems - Published in JOSS (2023)

https://github.com/nasa/prog_models

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 1 DOI reference(s) in JOSS metadata
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    5 of 18 committers (27.8%) from academic institutions
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

modeling prognostic-models prognostics prognostics-health-management simulation
Last synced: 4 months ago · JSON representation

Repository

The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.

Basic Info
  • Host: GitHub
  • Owner: nasa
  • Default Branch: master
  • Homepage:
  • Size: 12.1 MB
Statistics
  • Stars: 126
  • Watchers: 6
  • Forks: 52
  • Open Issues: 75
  • Releases: 11
Topics
modeling prognostic-models prognostics prognostics-health-management simulation
Created almost 5 years ago · Last pushed about 2 years ago
Metadata Files
Readme

README.md

ProgPy Packages

The progmodels package has been combined with the progalgs package to create the new progpy python package, here: https://github.com/nasa/progpy.

Owner

  • Name: NASA
  • Login: nasa
  • Kind: organization
  • Email: nasa-data@lists.arc.nasa.gov
  • Location: United States of America

ReadOpen Data initiative here: https://www.nasa.gov/open/ & Instructions here: https://github.com/nasa/nasa.github.io/blob/master/docs/INSTRUCTIONS.md

JOSS Publication

ProgPy: Python Packages for Prognostics and Health Management of Engineering Systems
Published
July 06, 2023
DOI
Volume 8, Issue 87, Page 5099
Authors
Christopher Teubert ORCID
NASA Ames Research Center, United States
Katelyn Jarvis
NASA Ames Research Center, United States
Matteo Corbetta ORCID
KBR, Inc.
Chetan Kulkarni
KBR, Inc.
Matthew Daigle
KBR, Inc.
Editor
Kelly Rowland ORCID
Tags
Prognostics Health Management Degradation Simulation Diagnostics State Estimation Prediction CBM+ IVHM PHM
View PDF Review Thread Software Archive

GitHub Events

Total
  • Watch event: 4
  • Fork event: 2
Last Year
  • Watch event: 4
  • Fork event: 2

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 1,981
  • Total Committers: 18
  • Avg Commits per committer: 110.056
  • Development Distribution Score (DDS): 0.451
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Christopher Teubert c****t@n****v 1,088
Lawrence Hwang l****6@g****m 276
Aditya Tummala a****a@g****m 253
Katy k****s@u****u 142
Miryam S m****1@g****m 91
Wade Lamberson w****5@g****m 54
Henry Lembo l****y@g****m 29
matteocorbetta i****a@g****m 25
Matteo Corbetta m****a@n****v 6
Rishabh 5****7 4
Arjun Sharda 7****7 3
Arjun Sharda 7****a 2
Elizabeth Hale h****8@g****m 2
Matteo Corbetta m****1@m****v 2
Michael Snyder m****r@n****m 1
Sayyed Mohsen Vazirizade s****e@g****m 1
William Bradford Clark w****k@r****m 1
darrahts t****h@v****u 1
Committer Domains (Top 20 + Academic)
nasa.gov: 2 vanderbilt.edu: 1 redhat.com: 1 ngc.com: 1 matteocorbetta.ndc.nasa.gov: 1 ucdavis.edu: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 108
  • Total pull requests: 87
  • Average time to close issues: 9 months
  • Average time to close pull requests: 11 days
  • Total issue authors: 7
  • Total pull request authors: 8
  • Average comments per issue: 0.27
  • Average comments per pull request: 6.38
  • Merged pull requests: 65
  • 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
  • teubert (97)
  • kjjarvis (3)
  • wlamberson1 (3)
  • aqitya (2)
  • nkrusch (1)
  • tbsexton (1)
  • lawrence-hwang (1)
Pull Request Authors
  • teubert (40)
  • mstraut (14)
  • aqitya (11)
  • kjjarvis (8)
  • lizjhale (3)
  • hlembo (1)
  • lawrence-hwang (1)
  • kyleniemeyer (1)
Top Labels
Issue Labels
enhancement (54) CI/CD (16) component: models: data-driven (8) component: simulation (8) bug (7) component: models (6) documentation (5) component: surrogate (4) Priority: High (4) duplicate (1)
Pull Request Labels
enhancement (12) component: models (8) bug (4) component: models: data-driven (4) component: simulation (3) CI/CD (2) documentation (2) component: surrogate (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 85 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 1
  • Total versions: 28
  • Total maintainers: 2
pypi.org: prog-models

The NASA Prognostic Model Package is a python modeling framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.

  • Versions: 28
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 85 Last month
Rankings
Dependent packages count: 4.7%
Forks count: 5.7%
Stargazers count: 6.5%
Average: 13.1%
Dependent repos count: 21.7%
Downloads: 26.8%
Maintainers (2)
kjjarvis teubert
Last synced: 4 months ago