SciML / SciML/JumpProcesses.jl
Automated depedency graph generation
Open
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 150
- Forks
- 41
- Avg merge
- 1d 9h
- Merged PRs (30d)
- 28
Description
We should hook into the new sparsity detection tools and/or extend them to generate jump dependency graphs from affect! functions. This would be great for users, and should allow the non-Direct SSAs to be used as broadly as Direct (for ConstantRateJumps at least).
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 by locating the sparsity detection tools and the handling of affect! functions, then trace how dependency information is represented for Direct and non-Direct SSAs. The work is done when jump dependency graphs are generated for the relevant ConstantRateJumps cases and non-Direct SSAs can use them as broadly as Direct.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- tooling
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100