Introduce mutating functions for Problem member functions #53
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…nguish modifying and non-modifying memberfunctions.
kellertuer
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@@ Coverage Diff @@
## master #53 +/- ##
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+ Coverage 99.28% 99.66% +0.37%
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Files 41 45 +4
Lines 1968 2360 +392
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+ Hits 1954 2352 +398
+ Misses 14 8 -6
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# Conflicts: # Project.toml # src/plans/gradient_plan.jl # src/plans/hessian_plan.jl # src/plans/stepsize.jl # src/solvers/gradient_descent.jl # test/solvers/test_trust_regions.jl
…opt.jl into mutating-evalutations
* use grad instead of ∇ to denote the gradient
* use gradient within options (instead of ∇) to denote the current gradient
* use gradient!! within probems (instead of ∇) to denote the gradient function gradF
* use ˚\operatorname{grad}` within math formular (instead of ∇) to denote the gradient
* use `grad_` (instead of `∇`) to prefix gradient functions
* introduce a notation page in the documentation.
* adapt Newton (still with allocation always) to new scheme).
# Conflicts: # src/solvers/quasi_Newton.jl
…, finish documentation overhaul.
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This PR is finished, we just need JuliaManifolds/Manifolds.jl#334 to be merged. |
kellertuer
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This is a major rework of the inner structure of
Manopt.jlto support mutating problem functions, most prominentlygradient!(X,x).gradient!!function and encapsulate all of this inget_gradient/get_gradient!Circle/PositiveNumberssince thengradient!!never mutates.get_gradient!should be introducedhessiantohessian!!ApproximateHessianto act as a normal hessian (mutating or allocating) functionsubgradienttosubgradient!!proxestoproximal_maps!!∇tostochastic_gradient!!PrimalDualProbemto!!.Mas their first parameter.This then solves #52.
The problem parameter might even later be used to indicate whether the gradient/hessian is Riemannian or Euclidean, though their conversions have to first be more established.
Maybe a small benchmark of the two new methods (providing either a allocation or a mutating gradient) would be nice, too.