JuliaApproximation / JuliaApproximation/ApproxFunBase.jl
What would be the best way to implement support differentiation of a SubSpace
Open
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 13
- Forks
- 13
- Avg merge
- 10h 33m
- Merged PRs (30d)
- 16
Description
At this moment
julia> S = ApproxFunBase.SubSpace(Fourier(), 1:10);
julia> Derivative(S)
DerivativeWrapper : Fourier(【0.0,6.283185307179586❫)|1:10 → SinSpace(【0.0,6.283185307179586❫)⊕CosSpace(【0.0,6.283185307179586❫)
0.0 0.0 -1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 -2.0 0.0 0.0 0.0 0.0 0.0
0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 -3.0 0.0 0.0 0.0
0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -4.0 0.0
0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 4.0 0.0 0.0
while the first dimension could be finite.
Where would be the best place to interrupt the ApproxFunBase flow to create an Operator that is finite in both dimensions?
Contributor guide
No contributing guide indexed for this repository
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 reproducing the Derivative(S) example and tracing the ApproxFunBase flow into the resulting Operator. Identify where the finite first dimension is lost and determine the appropriate entry point for an operator finite in both dimensions. The work is done when differentiation of this SubSpace produces the intended finite operator.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- backend
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100