SimpleDiffEq

Simple differential equation solvers in native Julia for scientific machine learning (SciML)

https://github.com/sciml/simplediffeq.jl

Science Score: 54.0%

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
  • Academic publication links
  • Committers with academic emails
    1 of 15 committers (6.7%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (7.5%) to scientific vocabulary

Keywords

differential-equations scientific-machine-learning sciml

Keywords from Contributors

matrix-exponential pde sde ode dae neural-ode partial-differential-equations numerics differentialequations data-structures
Last synced: 7 months ago · JSON representation ·

Repository

Simple differential equation solvers in native Julia for scientific machine learning (SciML)

Basic Info
  • Host: GitHub
  • Owner: SciML
  • License: other
  • Language: Julia
  • Default Branch: master
  • Homepage:
  • Size: 251 KB
Statistics
  • Stars: 24
  • Watchers: 6
  • Forks: 11
  • Open Issues: 5
  • Releases: 26
Topics
differential-equations scientific-machine-learning sciml
Created about 8 years ago · Last pushed 8 months ago
Metadata Files
Readme License Citation

README.md

SimpleDiffEq.jl

Build Status Coverage Status codecov.io

SimpleDiffEq.jl is a library of basic differential equation solvers. They are the "no-cruft" versions of the solvers which don't and won't ever support any fancy features like events. They are self-contained. This library exists for a few purposes. For one, it can be a nice way to teach "how to write a solver for X" in Julia by having a simple yet optimized version. Secondly, since it's hooked onto the common interface, these algorithms can serve as benchmarks to test the overhead of the full integrators on the simplest case. Lastly, these can be used to test correctness of the more complicated implementations.

Owner

  • Name: SciML Open Source Scientific Machine Learning
  • Login: SciML
  • Kind: organization
  • Email: contact@chrisrackauckas.com

Open source software for scientific machine learning

Citation (CITATION.bib)

@article{DifferentialEquations.jl-2017,
 author = {Rackauckas, Christopher and Nie, Qing},
 doi = {10.5334/jors.151},
 journal = {The Journal of Open Research Software},
 keywords = {Applied Mathematics},
 note = {Exported from https://app.dimensions.ai on 2019/05/05},
 number = {1},
 pages = {},
 title = {DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia},
 url = {https://app.dimensions.ai/details/publication/pub.1085583166 and http://openresearchsoftware.metajnl.com/articles/10.5334/jors.151/galley/245/download/},
 volume = {5},
 year = {2017}
}

GitHub Events

Total
  • Issues event: 3
  • Watch event: 2
  • Delete event: 6
  • Issue comment event: 2
  • Push event: 11
  • Pull request event: 8
  • Create event: 6
Last Year
  • Issues event: 3
  • Watch event: 2
  • Delete event: 6
  • Issue comment event: 2
  • Push event: 11
  • Pull request event: 8
  • Create event: 6

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 186
  • Total Committers: 15
  • Avg Commits per committer: 12.4
  • Development Distribution Score (DDS): 0.516
Past Year
  • Commits: 4
  • Committers: 2
  • Avg Commits per committer: 2.0
  • Development Distribution Score (DDS): 0.25
Top Committers
Name Email Commits
Chris Rackauckas a****s@c****m 90
George Datseris d****e@g****m 47
Utkarsh r****0@g****m 15
github-actions[bot] 4****] 7
dependabot[bot] 4****] 7
Anant Thazhemadam a****m@g****m 5
kanav99 k****0@g****m 4
ErikQQY 2****3@q****m 3
Chris de Graaf me@c****v 2
Ronan Arraes Jardim Chagas r****r@g****m 1
Julia TagBot 5****t 1
Hendrik Ranocha m****l@r****e 1
David Widmann d****n 1
Anshul Singhvi a****7@s****u 1
CompatHelper Julia c****y@j****g 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 18
  • Total pull requests: 64
  • Average time to close issues: 3 months
  • Average time to close pull requests: 4 days
  • Total issue authors: 8
  • Total pull request authors: 16
  • Average comments per issue: 4.28
  • Average comments per pull request: 0.84
  • Merged pull requests: 54
  • Bot issues: 0
  • Bot pull requests: 15
Past Year
  • Issues: 1
  • Pull requests: 2
  • Average time to close issues: 12 days
  • Average time to close pull requests: 25 minutes
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • ChrisRackauckas (6)
  • Datseris (6)
  • utkarsh530 (1)
  • Vilin97 (1)
  • Volker-Weissmann (1)
  • julianmuehlenhoff (1)
  • bradcarman (1)
  • sdwfrost (1)
  • thazhemadam (1)
  • JuliaTagBot (1)
Pull Request Authors
  • ChrisRackauckas (18)
  • Datseris (12)
  • dependabot[bot] (9)
  • github-actions[bot] (8)
  • utkarsh530 (7)
  • ranocha (3)
  • thazhemadam (3)
  • kanav99 (2)
  • christopher-dG (2)
  • ronisbr (1)
  • devmotion (1)
  • asinghvi17 (1)
  • rusandris (1)
  • YingboMa (1)
  • ErikQQY (1)
Top Labels
Issue Labels
bug (1)
Pull Request Labels
dependencies (9)

Packages

  • Total packages: 1
  • Total downloads:
    • julia 117 total
  • Total dependent packages: 3
  • Total dependent repositories: 0
  • Total versions: 26
juliahub.com: SimpleDiffEq

Simple differential equation solvers in native Julia for scientific machine learning (SciML)

  • Versions: 26
  • Dependent Packages: 3
  • Dependent Repositories: 0
  • Downloads: 117 Total
Rankings
Dependent repos count: 9.9%
Forks count: 12.5%
Dependent packages count: 13.2%
Average: 14.9%
Stargazers count: 24.1%
Last synced: 7 months ago