JuliaApproximation / JuliaApproximation/ApproxFun.jl
Are we able to solve this simple sturm liouville problem taken from chebfun examples?
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- Dominant language
- Julia
- Stars
- 559
- Forks
- 71
- PR merge metrics
- No merged PRs in 30d
Description
Here is the simple example in the documentation. How would you achieve the same with Approxfun?
L = chebop(@(u) -diff(u, 2), dom);
L.bc = 'periodic';
k = 5; % number of eigenvalues we want
[V, D] = eigs(L, k);
figure, plot(V, LW, 2)
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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 provides a Chebfun documentation snippet for a periodic Sturm–Liouville eigenvalue problem. Start by reading the corresponding ApproxFun documentation and locating its operator and eigenvalue entry points. Done means the issue has a documented, working equivalent or a clearly scoped limitation.
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
- 20/100