An open API service for producing an overview of a list of open source projects.

JOSS: https://github.com/nasa/prog_models

modeling prognostic-models prognostics prognostics-health-management simulation

Score: 15.823166582349234

Last synced: about 14 hours ago
JSON representation

Repository metadata:

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.


Owner metadata:


GitHub Events

Total
Last Year

Committers metadata

Last synced: 3 days ago

Total Commits: 1,981
Total Committers: 18
Avg Commits per committer: 110.056
Development Distribution Score (DDS): 0.451

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

Name Email Commits
Christopher Teubert c****t@n****v 1088
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

Issue and Pull Request metadata

Last synced: 9 days ago

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 request: 65
Bot issues: 0
Bot pull requests: 0

Past year issues: 0
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 0
Past year pull request authors: 0
Past year average comments per issue: 0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/nasa/prog_models

Top Issue Authors

  • teubert (97)
  • kjjarvis (3)
  • wlamberson1 (3)
  • aqitya (2)
  • nkrusch (1)
  • tbsexton (1)
  • lawrence-hwang (1)

Top Pull Request Authors

  • teubert (40)
  • mstraut (14)
  • aqitya (11)
  • kjjarvis (8)
  • lizjhale (3)
  • hlembo (1)
  • kyleniemeyer (1)
  • lawrence-hwang (1)

Top 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)

Top Pull Request Labels

  • enhancement (12)
  • component: models (8)
  • component: models: data-driven (4)
  • bug (4)
  • component: simulation (3)
  • CI/CD (2)
  • documentation (2)
  • component: surrogate (1)

Package metadata

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.

  • Homepage: https://nasa.github.io/progpy/prog_models_guide.html
  • Documentation: https://prog-models.readthedocs.io/
  • Licenses: NOSA
  • Latest release: 1.5.2 (published almost 3 years ago)
  • Last Synced: 2026-06-19T20:00:39.921Z (3 days ago)
  • Versions: 28
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 2,054 Last month
  • Rankings:
    • Dependent packages count: 4.733%
    • Forks count: 5.655%
    • Stargazers count: 6.498%
    • Average: 13.077%
    • Dependent repos count: 21.662%
    • Downloads: 26.838%
  • Maintainers (2)