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…gration - Make Cheby function robust for AD and floating-point noise - Add all necessary chebyquad overloads for type=Val(T), type=T, positional and keyword arguments, and model selection - Ensure chebyquad works for both NLP and NLS forms - Add fallback for keyword-only calls - Confirmed gradient is valid and tests now run to completion
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Pull request overview
Adds the Moré–Garbow–Hillstrom “chebyquad” test problem (Problem 35) to the OptimizationProblems.jl catalog, providing both a JuMP (PureJuMP) and AD-based (ADNLPProblems) implementation plus metadata for discovery via OptimizationProblems.meta.
Changes:
- Added
chebyquadimplementation insrc/PureJuMP/chebyquad.jl. - Added
chebyquadNLP/NLS implementations insrc/ADNLPProblems/chebyquad.jl(withuse_nlsswitch). - Added metadata and size getters in
src/Meta/chebyquad.jl.
Reviewed changes
Copilot reviewed 3 out of 3 changed files in this pull request and generated 8 comments.
| File | Description |
|---|---|
| src/PureJuMP/chebyquad.jl | Introduces a JuMP nonlinear objective formulation for chebyquad. |
| src/ADNLPProblems/chebyquad.jl | Introduces AD-based NLP + in-place NLS residual formulations for chebyquad. |
| src/Meta/chebyquad.jl | Registers chebyquad metadata and getter functions (including NLS residual count). |
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…T) for typed constants and builds x0 from a typed step, which keeps Float32 inputs and the objective result in Float32 without forcing constructor conversions.
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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Closes #115
Builds on #280