TrustRegionMethods

Trust region methods for nonlinear systems of equations in Julia.

https://github.com/tpapp/trustregionmethods.jl

Science Score: 31.0%

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
  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.3%) to scientific vocabulary

Keywords

julia julia-language nonlinear-equations optimization optimization-algorithms trust-region-methods

Keywords from Contributors

nlpmodels nonlinear-programming julialang mixed-model ipopt quantum-computing quantum-information abstract-algebra computer-algebra computer-algebra-system
Last synced: 6 months ago · JSON representation ·

Repository

Trust region methods for nonlinear systems of equations in Julia.

Basic Info
  • Host: GitHub
  • Owner: tpapp
  • License: other
  • Language: Julia
  • Default Branch: master
  • Size: 149 KB
Statistics
  • Stars: 15
  • Watchers: 3
  • Forks: 0
  • Open Issues: 4
  • Releases: 13
Topics
julia julia-language nonlinear-equations optimization optimization-algorithms trust-region-methods
Created about 6 years ago · Last pushed 7 months ago
Metadata Files
Readme Changelog License Citation

README.md

TrustRegionMethods.jl

lifecycle build codecov Aqua QA

A simple, and somewhat experimental Julia package for trust region methods, with an emphasis on

  1. Clean functional style: no preallocated buffers, resulting in less complicated code.

  2. A detailed tracer API:: trace the solver by printing or accumulating steps and/or various diagnostics.

  3. AD via DifferentiationInterface: harness the power of Julia's AD ecosystem in a simple way.

  4. Support for bailing out: some inputs just may not be possible or worthwhile to evaluate for very complicated functions (eg economic models). You can signal this by returning non-finite residuals (eg NaNs) early.

Example

```julia julia> using TrustRegionMethods

julia> const A = [1.0 2.0; 3.0 4.0] 2×2 Matrix{Float64}: 1.0 2.0 3.0 4.0

julia> f(x) = A * x .- exp.(x);

julia> F = trustregionproblem(f, zeros(2)) trust region problem residual dimension: 2 initial x: [0.0, 0.0] AD backend: ADTypes.AutoForwardDiff()

julia> result = trustregionsolver(F) Nonlinear solver using trust region method converged after 5 steps with ‖x‖₂ = 1.26e-15, Δ = 1.0 x = [-0.12, 0.503] r = [-8.88e-16, -8.88e-16]

julia> result.converged true

julia> result.x 2-element Vector{Float64}: -0.11979242665753244 0.5034484917613987 ```

Related packages

This package is very experimental — the interface will be evolving without prior warning or deprecation. You may want to consider the packages below instead.

  • NLsolve.jl is much more mature, but written with a lot of emphasis on using pre-allocated buffers.

  • TRS.jl solves trust region subproblems for large scale problems using the generalized eigenvalue solver of Adachi et al (2017). This solver is also implemented in this package, but not optimized for large-scale sparse problems.

References

See CITATIONS.bib.

Owner

  • Name: Tamas K. Papp
  • Login: tpapp
  • Kind: user
  • Company: Institute for Advanced Studies, Vienna

Citation (CITATIONS.bib)

@article{adachi2017solving,
  title={Solving the trust-region subproblem by a generalized eigenvalue problem},
  author={Adachi, Satoru and Iwata, Satoru and Nakatsukasa, Yuji and Takeda, Akiko},
  journal={SIAM Journal on Optimization},
  volume=27,
  number=1,
  pages={269--291},
  year=2017,
  publisher={SIAM}
}

@book{nocedal2006numerical,
  title={Numerical optimization 2nd},
  author={Nocedal, Jorge and Wright, Stephen J},
  year=2006,
  publisher={Springer}
}

GitHub Events

Total
  • Create event: 12
  • Commit comment event: 15
  • Issues event: 1
  • Release event: 4
  • Watch event: 3
  • Delete event: 5
  • Issue comment event: 5
  • Push event: 24
  • Pull request event: 16
Last Year
  • Create event: 12
  • Commit comment event: 15
  • Issues event: 1
  • Release event: 4
  • Watch event: 3
  • Delete event: 5
  • Issue comment event: 5
  • Push event: 24
  • Pull request event: 16

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 58
  • Total Committers: 4
  • Avg Commits per committer: 14.5
  • Development Distribution Score (DDS): 0.138
Top Committers
Name Email Commits
Tamas K. Papp t****p@g****m 50
github-actions[bot] 4****]@u****m 5
CompatHelper Julia c****y@j****g 2
Julia TagBot 5****t@u****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 10
  • Total pull requests: 41
  • Average time to close issues: 5 months
  • Average time to close pull requests: 11 days
  • Total issue authors: 2
  • Total pull request authors: 3
  • Average comments per issue: 1.6
  • Average comments per pull request: 0.27
  • Merged pull requests: 40
  • Bot issues: 0
  • Bot pull requests: 16
Past Year
  • Issues: 2
  • Pull requests: 14
  • Average time to close issues: N/A
  • Average time to close pull requests: 11 days
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 13
  • Bot issues: 0
  • Bot pull requests: 7
Top Authors
Issue Authors
  • tpapp (9)
  • JuliaTagBot (1)
Pull Request Authors
  • tpapp (28)
  • github-actions[bot] (18)
  • JuliaTagBot (1)
Top Labels
Issue Labels
enhancement (1) help wanted (1) good first issue (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • julia 1 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 16
juliahub.com: TrustRegionMethods

Trust region methods for nonlinear systems of equations in Julia.

  • Versions: 16
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 1 Total
Rankings
Dependent repos count: 9.9%
Stargazers count: 31.2%
Average: 33.4%
Dependent packages count: 38.9%
Forks count: 53.5%
Last synced: 6 months ago

Dependencies

.github/workflows/CI.yml actions
  • actions/cache v1 composite
  • actions/checkout v2 composite
  • codecov/codecov-action v1 composite
  • julia-actions/julia-buildpkg v1 composite
  • julia-actions/julia-processcoverage v1 composite
  • julia-actions/julia-runtest v1 composite
  • julia-actions/setup-julia v1 composite
.github/workflows/CompatHelper.yml actions
.github/workflows/TagBot.yml actions
  • JuliaRegistries/TagBot v1 composite