Introduce an EmbeddedObjective

Project.toml

@@ -40,8 +40,8 @@ Colors = "0.11.2, 0.12"
 DataStructures = "0.17, 0.18"
 LRUCache = "1.4"
 ManifoldDiff = "0.2, 0.3.3"
-Manifolds = "0.8.69"
-ManifoldsBase = "0.14.4"
+Manifolds = "0.8.75"
+ManifoldsBase = "0.14.10"
 PolynomialRoots = "1"
 Requires = "0.5, 1"
 julia = "1.6"

docs/Project.toml

@@ -23,5 +23,5 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 BenchmarkTools = "1.3"
 CondaPkg = "0.2"
 Documenter = "0.27"
-Manifolds = "0.8.27"
+Manifolds = "0.8.75"
 ManifoldsBase = "0.13, 0.14"

docs/make.jl

@@ -61,7 +61,29 @@ makedocs(
     format=Documenter.HTML(;
         mathengine=MathJax3(), prettyurls=get(ENV, "CI", nothing) == "true"
     ),
-    modules=[Manopt],
+    modules=[
+        Manopt,
+        if isdefined(Base, :get_extension)
+            Base.get_extension(Manopt, :ManoptLineSearchesExt)
+        else
+            Manopt.ManoptLineSearchesExt
+        end,
+        if isdefined(Base, :get_extension)
+            Base.get_extension(Manopt, :ManoptLRUCacheExt)
+        else
+            Manopt.ManoptLRUCacheExt
+        end,
+        if isdefined(Base, :get_extension)
+            Base.get_extension(Manopt, :ManoptManifoldsExt)
+        else
+            Manopt.ManoptManifoldsExt
+        end,
+        if isdefined(Base, :get_extension)
+            Base.get_extension(Manopt, :ManoptPlotsExt)
+        else
+            Manopt.ManoptPlotsExt
+        end,
+    ],
     authors="Ronny Bergmann and contributors.",
     sitename="Manopt.jl",
     strict=[
@@ -86,8 +108,9 @@ makedocs(
             "Get started: Optimize!" => "tutorials/Optimize!.md",
             "Speedup using Inplace computations" => "tutorials/InplaceGradient.md",
             "Use Automatic Differentiation" => "tutorials/AutomaticDifferentiation.md",
+            "Define Objectives in the Embedding" => "tutorials/EmbeddingObjectives.md",
             "Count and use a Cache" => "tutorials/CountAndCache.md",
-            "Perform Debug Output" => "tutorials/HowToDebug.md",
+            "Print Debug Output" => "tutorials/HowToDebug.md",
             "Record values" => "tutorials/HowToRecord.md",
             "Implement a Solver" => "tutorials/ImplementASolver.md",
             "Do Contrained Optimization" => "tutorials/ConstrainedOptimization.md",

docs/src/extensions.md

@@ -45,6 +45,11 @@ x_opt = quasi_Newton(
 )
 ```
 
+### Manifolds.jl
+
 ```@docs
 Manopt.LineSearchesStepsize
+mid_point
+Manopt.max_stepsize(::TangentBundle, ::Any)
+Manopt.max_stepsize(::FixedRankMatrices, ::Any)
 ```

docs/src/plans/objective.md

@@ -20,23 +20,83 @@ InplaceEvaluation
 evaluation_type
 ```
 
-It sometimes might be nice to set certain parameters within
 
-## Cost Objective
+## Decorators for Objectives
+
+An objective can be decorated using the following trait and function to initialize
+
+```@docs
+dispatch_objective_decorator
+is_objective_decorator
+decorate_objective!
+```
+
+### [Embedded Objectives](@id ManifoldEmbeddedObjective)
+
+```@docs
+EmbeddedManifoldObjective
+```
+
+### [Cache Objective](@id CacheSection)
+
+Since single function calls, e.g. to the cost or the gradient, might be expensive,
+a simple cache objective exists as a decorator, that caches one cost value or gradient.
+
+It can be activated/used with the `cache=` keyword argument available for every solver.
+
+```@docs
+Manopt.reset_counters!
+Manopt.objective_cache_factory
+```
+
+#### A simple cache
+
+A first generic cache is always available, but it only caches one gradient and one cost function evaluation (for the same point).
+
+```@docs
+SimpleManifoldCachedObjective
+```
+
+#### A Generic Cache
+
+For the more advanced cache, you need to implement some type of cache yourself, that provides a `get!`
+and implement [`init_caches`](@ref).
+This is for example provided if you load [`LRUCache.jl`](https://github.com/JuliaCollections/LRUCache.jl). Then you obtain
+
+```@docs
+ManifoldCachedObjective
+init_caches
+```
+
+### [Count Objective](@id ManifoldCountObjective)
+
+```@docs
+ManifoldCountObjective
+```
+
+### Internal Decorators
+
+```@docs
+ReturnManifoldObjective
+```
+
+## Specific Objective typed and their access functions
+
+### Cost Objective
 
 ```@docs
 AbstractManifoldCostObjective
 ManifoldCostObjective
 ```
 
-### Access functions
+#### Access functions
 
 ```@docs
 get_cost
 get_cost_function
 ```
 
-## Gradient Objectives
+### Gradient Objectives
 
 ```@docs
 AbstractManifoldGradientObjective
@@ -52,61 +112,61 @@ There is also a second variant, if just one function is responsible for computin
 ManifoldCostGradientObjective
 ```
 
-### Access functions
+#### Access functions
 
 ```@docs
 get_gradient
 get_gradients
 get_gradient_function
 ```
 
-## Subgradient Objective
+### Subgradient Objective
 
 ```@docs
 ManifoldSubgradientObjective
 ```
 
-### Access Functions
+#### Access Functions
 
 ```@docs
 get_subgradient
 ```
 
-## Proximal Map Objective
+### Proximal Map Objective
 
 ```@docs
 ManifoldProximalMapObjective
 ```
 
-### Access Functions
+#### Access Functions
 
 ```@docs
 get_proximal_map
 ```
 
 
-## Hessian Objective
+### Hessian Objective
 
 ```@docs
 ManifoldHessianObjective
 ```
 
-### Access functions
+#### Access functions
 
 ```@docs
 get_hessian
 get_preconditioner
 ```
 
-## Primal-Dual based Objetives
+### Primal-Dual based Objectives
 
 ```@docs
 AbstractPrimalDualManifoldObjective
 PrimalDualManifoldObjective
 PrimalDualManifoldSemismoothNewtonObjective
 ```
 
-### Access functions
+#### Access functions
 
 ```@docs
 adjoint_linearized_operator
@@ -118,7 +178,7 @@ get_primal_prox
 linearized_forward_operator
 ```
 
-## Constrained Objective
+### Constrained Objective
 
 Besides the [`AbstractEvaluationType`](@ref) there is one further property to
 distinguish among constraint functions, especially the gradients of the constraints.
@@ -135,7 +195,7 @@ The [`ConstraintType`](@ref) is a parameter of the corresponding Objective.
 ConstrainedManifoldObjective
 ```
 
-### Access functions
+#### Access functions
 
 ```@docs
 get_constraints
@@ -152,50 +212,3 @@ get_grad_inequality_constraint!
 get_grad_inequality_constraints
 get_grad_inequality_constraints!
 ```
-
-## Decorators for AbstractManoptSolverState
-
-An objective can be decorated using the following trait and function to initialize
-
-```@docs
-dispatch_objective_decorator
-is_objective_decorator
-decorate_objective!
-```
-
-### [Cache Objective](@id CacheSection)
-
-Since single function calls, e.g. to the cost or the gradient, might be expensive,
-a simple cache objective exists as a decorator, that caches one cost value or gradient.
-
-It can be activated/used with the `cache=` keyword argument available for every solver.
-
-```@docs
-Manopt.reset_counters!
-Manopt.objective_cache_factory
-```
-
-#### A simple cache
-
-A first generic cache is always available, but it only caches one gradient and one cost function evaluation (for the same point).
-
-```@docs
-SimpleManifoldCachedObjective
-```
-
-#### A Generic Cache
-
-For the more advanced cache, you need to implement some type of cache yourself, that provides a `get!`
-and implement [`init_caches`](@ref).
-This is for example provided if you load [`LRUCache.jl`](https://github.com/JuliaCollections/LRUCache.jl). Then you obtain
-
-```@docs
-ManifoldCachedObjective
-init_caches
-```
-
-### [Count Objective](@id ManifoldCountObjective)
-
-```@docs
-ManifoldCountObjective
-```

docs/src/plans/state.md

@@ -25,7 +25,7 @@ This might be useful to continue investigation at the current iterate, or to set
 ```@docs
 get_iterate
 set_iterate!
-get_gradient(::AbstractManifoldGradientObjective)
+get_gradient(s::AbstractManoptSolverState)
 set_gradient!
 ```
 

docs/src/references.bib

@@ -501,6 +501,20 @@ @article{LiuStorey:1991
 % --- N
 %
 %
+@article{Nguyen:2023,
+    DOI        = {10.1007/s10957-023-02242-z},
+    EPRINT     = {2009.10159},
+    EPRINTTYPE = {arXiv},
+    YEAR       = {2023},
+    MONTH      = jun,
+    PUBLISHER  = {Springer Science and Business Media {LLC}},
+    VOLUME     = {198},
+    NUMBER     = {1},
+    PAGES      = {135--164},
+    AUTHOR     = {Du Nguyen},
+    TITLE      = {Operator-Valued Formulas for Riemannian Gradient and Hessian and Families of Tractable Metrics in Riemannian Optimization},
+    JOURNAL    = {Journal of Optimization Theory and Applications}
+}
 @book{NocedalWright:2006,
     ADDRESS   = {New York},
     AUTHOR    = {Nocedal, Jorge and Wright, Steven J.},

src/Manopt.jl

@@ -7,8 +7,10 @@
 * 🎯 Issues: [github.com/JuliaManifolds/Manopt.jl/issues](https://github.com/JuliaManifolds/Manopt.jl/issues)
 """
 module Manopt
+
 import Base: &, copy, getindex, identity, setindex!, show, |
 import LinearAlgebra: reflect!
+import ManifoldsBase: embed!
 
 using ColorSchemes
 using ColorTypes
@@ -45,7 +47,11 @@ using ManifoldDiff:
     differential_shortest_geodesic_startpoint,
     differential_shortest_geodesic_startpoint!,
     jacobi_field,
-    jacobi_field!
+    jacobi_field!,
+    riemannian_gradient,
+    riemannian_gradient!,
+    riemannian_Hessian,
+    riemannian_Hessian!
 using ManifoldsBase:
     AbstractBasis,
     AbstractDecoratorManifold,
@@ -78,6 +84,7 @@ using ManifoldsBase:
     default_retraction_method,
     default_vector_transport_method,
     distance,
+    embed,
     embed_project,
     embed_project!,
     exp,
@@ -87,6 +94,7 @@ using ManifoldsBase:
     get_component,
     get_coordinates,
     get_coordinates!,
+    get_embedding,
     get_iterator,
     get_vector,
     get_vector!,
@@ -206,6 +214,7 @@ export AbstractDecoratedManifoldObjective,
     AbstractManifoldObjective,
     AbstractPrimalDualManifoldObjective,
     ConstrainedManifoldObjective,
+    EmbeddedManifoldObjective,
     ManifoldCountObjective,
     NonlinearLeastSquaresObjective,
     ManifoldAlternatingGradientObjective,

src/plans/constrained_plan.jl

@@ -515,9 +515,9 @@ eevaluate all gradients of the equality constraints ``\operatorname{grad} h(x)``
 of the [`ConstrainedManifoldObjective`](@ref) `P` at `p`.
 
 !!! note
-   for the [`InplaceEvaluation`](@ref) and [`FunctionConstraint`](@ref) variant of the problem,
-   this function currently also calls [`get_equality_constraints`](@ref),
-   since this is the only way to determine the number of cconstraints.
+    For the [`InplaceEvaluation`](@ref) and [`FunctionConstraint`](@ref) variant of the problem,
+    this function currently also calls [`get_equality_constraints`](@ref),
+    since this is the only way to determine the number of cconstraints.
 """
 get_grad_equality_constraints(M::AbstractManifold, co::ConstrainedManifoldObjective, p)
 function get_grad_equality_constraints(