JuliaGraphs / JuliaGraphs/Graphs.jl
consider adding approximate algorithm for random_configuration_model
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 538
- Forks
- 128
- Avg merge
- 10h 25m
- Merged PRs (30d)
- 2
Description
Follow up to https://stackoverflow.com/questions/72732571/random-configuration-modeln-e-takes-to-long-on-lightgraphs-jl.
Currently random_configuration_model uses rejection sampling which is very slow for tight configurations. Probably allowing for approximate sampling with some edge rewiring strategy could be allowed (iGraph implements this).
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the random_configuration_model implementation and the linked Stack Overflow discussion to understand the rejection-sampling bottleneck for tight configurations. Compare the proposed approximate sampling and edge-rewiring approach with iGraph. Done means the function supports an approximate strategy for these configurations, with behavior and tradeoffs documented and validated by tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100