SciML / SciML/ComponentArrays.jl
Alias variables
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 375
- Forks
- 42
- Avg merge
- 7h 25m
- Merged PRs (30d)
- 17
Description
When there are physical conversions between components, we often have things like
x.comp1.out = fun(x.comp2.in)
However, when solving differential equations, we must have the same number of states as the number of equations, so we cannot actually introduce the new x.comp2.in variable without adding the trivial algebraic equation
du[i] = x.comp1.out - fun(x.comp2.in)
I wonder if we can add some kind of mechanism such that x.comp2.in directly returns fun(x.comp1.out).
Possible syntax:
x = ComponentArray(
comp1 = ComponentArray(out=1),
comp2 = ComponentArray(in=AliasVar(UpperLevel().comp1.out, fun)),
)
where UpperLevel signifies that comp2 array must keep a reference of the upper level ComponentArray x.
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
The issue names no files, tests, or entry points, so start by examining the existing ComponentArray construction and indexing behavior. Evaluate whether the proposed AliasVar and UpperLevel mechanism fits that design. Done means a defined interface and behavior for alias variables, including how references and conversions are handled.
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
- Mostly clear
- Newbie friendliness
- 25/100