Bump dependencies.

Changelog.md

@@ -5,6 +5,54 @@ All notable Changes to the Julia package `Manopt.jl` will be documented in this
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.4.40] – 24/10/2023
+
+## Changes
+
+* Bump dependencies to `ManifoldsBase.jl` 0.15 and `Manifolds.jl` 0.9
+* move the ARC CG subsolver to the main package, since `TangentSpace` is now already
+  available from `ManifoldsBase`.
+
+## [0.4.39] – 02/09/2023
+
+## Changes
+* also use the pair of a retraction and the inverse retraction (see last update)
+  to perform the relaxation within the Douglas-Rachford algorithm.
+
+## [0.4.38] – 08/10/2023
+
+### Changes
+
+* Fix a lot of typos in the documentation
+* avoid allocations when calling `get_jacobian!` within the Levenberg-Marquard Algorithm.
+
+## [0.4.37] – 02/09/2023
+
+### Changes
+
+* add more of the Riemannian Levenberg-Marquard algorithms parameters as keywords, so they
+  can be changed on call
+* generalize the internal reflection of Douglas-Rachford, such that is also works with an
+  arbitrary pair of a reflection and an inverse reflection.
+
+## [0.4.36] – 20/09/2023
+
+
+## [0.4.35] – 14/09/2023
+
+### Added
+
+* The access to functions of the objective is now unified and encapsulated in proper `get_`
+  functions.
+
+## [0.4.34] – 02/09/2023
+
+### Added
+
+* an `ManifoldEuclideanGradientObjetive` to allow the cost, gradient, and Hessian and other
+  first or second derivative based elements to be Euclidean and converted when needed.
+* a keyword `objective_type=:Euclidean` for all solvers, that specifies that an Objective shall be created of the above type
+
 ## [0.4.33] - 24/08/2023
 
 ### Added

Project.toml

@@ -1,7 +1,7 @@
 name = "Manopt"
 uuid = "0fc0a36d-df90-57f3-8f93-d78a9fc72bb5"
 authors = ["Ronny Bergmann <[email protected]>"]
-version = "0.4.39"
+version = "0.4.40"
 
 [deps]
 ColorSchemes = "35d6a980-a343-548e-a6ea-1d62b119f2f4"
@@ -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 = "0.8.75"
-ManifoldsBase = "0.14.10"
+Manifolds = "0.9"
+ManifoldsBase = "0.15"
 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 = "0.8.75"
-ManifoldsBase = "0.13, 0.14"
+Manifolds = "0.8.81, 0.9"
+ManifoldsBase = "0.14.12, 0.15"

docs/src/tutorials/HowToDebug.md

@@ -74,7 +74,7 @@ There is two more advanced variants that can be used. The first is a tuple of a
 
 We can for example change the way the `:ϵ` is printed by adding a format string
 and use [`DebugCost`](@ref)`()` which is equivalent to using `:Cost`.
-Especially with the format change, the lines are more consistent in length.
+Especially with the format change, the lines are more coniststent in length.
 
 ``` julia
 p2 = exact_penalty_method(

ext/ManoptManifoldsExt/ManoptManifoldsExt.jl

@@ -30,5 +30,4 @@ include("nonmutating_manifolds_functions.jl")
 include("artificialDataFunctionsManifolds.jl")
 include("ChambollePockManifolds.jl")
 include("alternating_gradient.jl")
-include("ARC_CG.jl")
 end

src/Manopt.jl

@@ -69,8 +69,10 @@ using ManifoldsBase:
     NestedPowerRepresentation,
     ParallelTransport,
     PowerManifold,
+    ProductManifold,
     ProjectionTransport,
     QRRetraction,
+    TangentSpace,
     ^,
     _read,
     _write,
@@ -123,6 +125,7 @@ using ManifoldsBase:
     set_component!,
     shortest_geodesic,
     shortest_geodesic!,
+    submanifold_components,
     vector_transport_to,
     vector_transport_to!,
     zero_vector,

src/solvers/adaptive_regularization_with_cubics.jl

@@ -839,3 +839,49 @@ function show(io::IO, c::StopWhenAllLanczosVectorsUsed)
         "StopWhenAllLanczosVectorsUsed($(repr(c.maxLanczosVectors)))\n    $(status_summary(c))",
     )
 end
+#
+#
+function set_manopt_parameter!(M::TangentSpace, ::Val{:p}, v)
+    M.point .= v
+    return M
+end
+function (f::Manopt.AdaptiveRegularizationCubicCost)(M::TangentSpace, X)
+    ## (33) in Agarwal et al.
+    return get_cost(base_manifold(M), f.mho, M.point) +
+           inner(base_manifold(M), M.point, X, f.X) +
+           1 / 2 * inner(
+               base_manifold(M),
+               M.point,
+               X,
+               get_hessian(base_manifold(M), f.mho, M.point, X),
+           ) +
+           f.σ / 3 * norm(base_manifold(M), M.point, X)^3
+end
+function (grad_f::Manopt.AdaptiveRegularizationCubicGrad)(M::TangentSpace, X)
+    # (37) in Agarwal et
+    return grad_f.X +
+           get_hessian(base_manifold(M), grad_f.mho, M.point, X) +
+           grad_f.σ * norm(base_manifold(M), M.point, X) * X
+end
+function (grad_f::Manopt.AdaptiveRegularizationCubicGrad)(M::TangentSpace, Y, X)
+    get_hessian!(base_manifold(M), Y, grad_f.mho, M.point, X)
+    Y .= Y + grad_f.X + grad_f.σ * norm(base_manifold(M), M.point, X) * X
+    return Y
+end
+function (c::StopWhenFirstOrderProgress)(
+    dmp::AbstractManoptProblem{<:TangentSpace}, ams::AbstractManoptSolverState, i::Int
+)
+    if (i == 0)
+        c.reason = ""
+        return false
+    end
+    #Update Gradient
+    TpM = get_manifold(dmp)
+    nG = norm(base_manifold(TpM), TpM.point, get_gradient(dmp, ams.p))
+    nX = norm(base_manifold(TpM), TpM.point, ams.p)
+    if (i > 0) && (nG <= c.θ * nX^2)
+        c.reason = "The algorithm has reduced the model grad norm by $(c.θ).\n"
+        return true
+    end
+    return false
+end

test/solvers/test_adaptive_regularization_with_cubics.jl

@@ -16,7 +16,7 @@ include("../utils/example_tasks.jl")
     Hess_f(M, p, X) = -A * X + p * p' * A * X + X * p' * A * p
 
     p0 = Matrix{Float64}(I, n, n)[:, 1:k]
-    M2 = TangentSpaceAtPoint(M, p0)
+    M2 = TangentSpace(M, p0)
 
     mho = ManifoldHessianObjective(f, grad_f, Hess_f)
     g = AdaptiveRegularizationCubicCost(M2, mho)

tutorials/Project.toml

@@ -18,7 +18,7 @@ FiniteDifferences = "0.12"
 IJulia = "1"
 LRUCache = "1.4"
 ManifoldDiff = "0.3"
-Manifolds = "0.8.75"
-ManifoldsBase = "0.14.5"
+Manifolds = "0.8.81, 0.9"
+ManifoldsBase = "0.14.12, 0.15"
 Manopt = "0.4.22"
 Plots = "1.38"