Bump dependencies and add a exclude-tutorials option for the docs, …

…to be able to render documentation locally when not having quarot installed.

docs/Project.toml

@@ -22,6 +22,6 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 [compat]
 BenchmarkTools = "1.3"
 CondaPkg = "0.2"
-Documenter = "0.27"
+Documenter = "1"
 Manifolds = "0.8.81, 0.9"
 ManifoldsBase = "0.14.12, 0.15"

docs/make.jl

@@ -2,6 +2,28 @@
 #
 #
 
+if "--help" ∈ ARGS
+    println(
+        """
+docs/make.jl
+
+Render the `Manopt.jl` documenation with optinal arguments
+
+Arguments
+* `--exclude-docs` - exlcude the tutorials from the menu of Documenter,
+  this can be used if you do not have Quarto installed to still be able to render the docs
+  locally on this machine. This option should not be set on CI.
+* `--help`         - print this help and exit without rendering the documentation
+* `--quarto`       – run the Quarto notebooks from the `tutorials/` folder before generating the documentation
+  this has to be run locally at least once for the `tutorials/*.md` files to exist that are included in
+  the documentation (see `--exclude-tutorials`) for the alternative.
+  If they are generated ones they are cached accordingly.
+  Then you can spare time in the rendering by not passing this argument.
+""",
+    )
+    exit(0)
+end
+
 #
 # (a) if docs is not the current active environment, switch to it
 # (from https://github.com/JuliaIO/HDF5.jl/pull/1020/) 
@@ -29,6 +51,17 @@ if "--quarto" ∈ ARGS
     end
 end
 
+tutorials_in_menu = true
+if "--exclude-tutorials" ∈ ARGS
+    @warn """
+    You are excluding the tutorials from the Menu,
+    which might be done if you can not render them locally.
+
+    Remember that this should never be done on CI for the full documentation.
+    """
+    tutorials_in_menu = false
+end
+
 # (c) load necessary packages for the docs
 using Documenter
 using DocumenterCitations
@@ -54,10 +87,23 @@ open(joinpath(generated_path, "contributing.md"), "w") do io
     end
 end
 
+## Build titorials menu
+tutorials_menu =
+    "How to..." => [
+        "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",
+        "Print Debug Output" => "tutorials/HowToDebug.md",
+        "Record values" => "tutorials/HowToRecord.md",
+        "Implement a Solver" => "tutorials/ImplementASolver.md",
+        "Do Constrained Optimization" => "tutorials/ConstrainedOptimization.md",
+        "Do Geodesic Regression" => "tutorials/GeodesicRegression.md",
+    ]
 # (e) ...finally! make docs
 bib = CitationBibliography(joinpath(@__DIR__, "src", "references.bib"); style=:alpha)
-makedocs(
-    bib;
+makedocs(;
     format=Documenter.HTML(;
         mathengine=MathJax3(), prettyurls=get(ENV, "CI", nothing) == "true"
     ),
@@ -86,36 +132,10 @@ makedocs(
     ],
     authors="Ronny Bergmann and contributors.",
     sitename="Manopt.jl",
-    strict=[
-        :doctest,
-        :linkcheck,
-        :parse_error,
-        :example_block,
-        :autodocs_block,
-        :cross_references,
-        :docs_block,
-        :eval_block,
-        :example_block,
-        :footnote,
-        :meta_block,
-        :missing_docs,
-        :setup_block,
-    ],
     pages=[
         "Home" => "index.md",
         "About" => "about.md",
-        "How to..." => [
-            "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",
-            "Print Debug Output" => "tutorials/HowToDebug.md",
-            "Record values" => "tutorials/HowToRecord.md",
-            "Implement a Solver" => "tutorials/ImplementASolver.md",
-            "Do Constrained Optimization" => "tutorials/ConstrainedOptimization.md",
-            "Do Geodesic Regression" => "tutorials/GeodesicRegression.md",
-        ],
+        (tutorials_in_menu ? [tutorials_menu] : [])...,
         "Solvers" => [
             "Introduction" => "solvers/index.md",
             "Adaptive Regularization with Cubics" => "solvers/adaptive-regularization-with-cubics.md",
@@ -170,6 +190,7 @@ makedocs(
         "Notation" => "notation.md",
         "References" => "references.md",
     ],
+    plugins=[bib],
 )
 deploydocs(; repo="github.com/JuliaManifolds/Manopt.jl", push_preview=true)
 #back to main env

docs/src/solvers/ChambollePock.md

@@ -3,7 +3,7 @@
 The Riemannian Chambolle–Pock is a generalization of the Chambolle–Pock algorithm [ChambollePock:2011](@citet*)
 It is also known as primal-dual hybrid gradient (PDHG) or primal-dual proximal splitting (PDPS) algorithm.
 
-In order to minimize over $p∈\mathcal M§ the cost function consisting of
+In order to minimize over $p∈\mathcal M$ the cost function consisting of
 
 ```math
 F(p) + G(Λ(p)),

src/data/artificialDataFunctions.jl

@@ -98,7 +98,7 @@ end
 generate a real-valued signal having piecewise constant, linear and quadratic
 intervals with jumps in between. If the resulting manifold the data lives on,
 is the [`Circle`](hhttps://juliamanifolds.github.io/Manifolds.jl/latest/manifolds/circle.html)
-the data is also wrapped to $[-\pi,\pi)$. This is data for an example from  [Bergmann et. al., SIAM J Imag Sci, 2014](@cite BergmannLausSteidlWeinmann:2014:1).
+the data is also wrapped to ``[-\pi,\pi)``. This is data for an example from  [Bergmann et. al., SIAM J Imag Sci, 2014](@cite BergmannLausSteidlWeinmann:2014:1).
 
 # Optional
 * `pts` – (`500`) number of points to sample the function
@@ -110,7 +110,7 @@ function artificial_S1_signal(pts::Integer=500)
 end
 @doc raw"""
     artificial_S1_signal(x)
-evaluate the example signal $f(x), x ∈  [0,1]$,
+evaluate the example signal ``f(x), x ∈  [0,1]``,
 of phase-valued data introduces in Sec. 5.1 of  [Bergmann et. al., SIAM J Imag Sci, 2014](@cite BergmannLausSteidlWeinmann:2014:1)
 for values outside that interval, this Signal is `missing`.
 """
@@ -147,7 +147,7 @@ function artificial_S2_whirl_image end
 Generate an artificial image of data on the 2 sphere,
 
 # Arguments
-* `pts` – (`64`) size of the image in `pts`$\times$`pts` pixel.
+* `pts` – (`64`) size of the image in `pts`×`pts` pixel.
 
 This example dataset was used in the numerical example in Section 5.5 of [Laus et al., SIAM J Imag Sci., 2017](@cite LausNikolovaPerschSteidl:2017)
 
@@ -172,7 +172,7 @@ artificial_S2_rotation_image()
 @doc raw"""
     artificial_S2_whirl_patch([pts=5])
 
-create a whirl within the `pts`$\times$`pts` patch of
+create a whirl within the `pts`×`pts` patch of
 [Sphere](https://juliamanifolds.github.io/Manifolds.jl/stable/manifolds/sphere.html)(@ref)`(2)`-valued image data.
 
 These patches are used within [`artificial_S2_whirl_image`](@ref).
@@ -213,11 +213,11 @@ p_2 = \begin{bmatrix}-1&0&0\end{bmatrix}^{\mathrm{T}},
 p_3 = \begin{bmatrix}0&0&-1\end{bmatrix}^{\mathrm{T}},
 ````
 
-where each segment is a cubic Bézier curve, i.e. each point, except $p_3$ has a first point
-within the following segment $b_i^+$, $i=0,1,2$ and a last point within the previous
-segment, except for $p_0$, which are denoted by $b_i^-$, $i=1,2,3$.
-This curve is differentiable by the conditions $b_i^- = \gamma_{b_i^+,p_i}(2)$, $i=1,2$,
-where $\gamma_{a,b}$ is the [`shortest_geodesic`](https://juliamanifolds.github.io/ManifoldsBase.jl/stable/functions/#ManifoldsBase.shortest_geodesic-Tuple{AbstractManifold,%20Any,%20Any}) connecting $a$ and $b$.
+where each segment is a cubic Bézier curve, i.e. each point, except ``p_3`` has a first point
+within the following segment ``b_i^+``, ``i=0,1,2`` and a last point within the previous
+segment, except for ``p_0``, which are denoted by ``b_i^-``, ``i=1,2,3``.
+This curve is differentiable by the conditions ``b_i^- = \gamma_{b_i^+,p_i}(2)``, ``i=1,2``,
+where ``\gamma_{a,b}`` is the [`shortest_geodesic`](https://juliamanifolds.github.io/ManifoldsBase.jl/stable/functions/#ManifoldsBase.shortest_geodesic-Tuple{AbstractManifold,%20Any,%20Any}) connecting ``a`` and ``b``.
 The remaining points are defined as
 
 ````math
@@ -237,7 +237,7 @@ artificial_S2_composite_bezier_curve()
     artificial_SPD_image([pts=64, stepsize=1.5])
 
 create an artificial image of symmetric positive definite matrices of size
-`pts`$\times$`pts` pixel with a jump of size `stepsize`.
+`pts`×`pts` pixel with a jump of size `stepsize`.
 
 This dataset was used in the numerical example of Section 5.2 of [Bačák et al., SIAM J Sci Comput, 2016](@cite BacakBergmannSteidlWeinmann:2016).
 """
@@ -273,7 +273,7 @@ function artificial_SPD_image2 end
     artificial_SPD_image2([pts=64, fraction=.66])
 
 create an artificial image of symmetric positive definite matrices of size
-`pts`$\times$`pts` pixel with right hand side `fraction` is moved upwards.
+`pts`×`pts` pixel with right hand side `fraction` is moved upwards.
 
 This data set was introduced in the numerical examples of Section of [Bergmann, Presch, Steidl, SIAM J Imag Sci, 2016](@cite BergmannPerschSteidl:2016)
 """
@@ -282,7 +282,7 @@ artificial_SPD_image2(pts, fraction)
 @doc raw"""
     artificial_S2_lemniscate(p, t::Float64; a::Float64=π/2)
 
-Generate a point from the signal on the [`Sphere`](https://juliamanifolds.github.io/Manifolds.jl/stable/manifolds/sphere.html) $\mathbb S^2$ by
+Generate a point from the signal on the [`Sphere`](https://juliamanifolds.github.io/Manifolds.jl/stable/manifolds/sphere.html) ``\mathbb S^2`` by
 creating the [Lemniscate of Bernoulli](https://en.wikipedia.org/wiki/Lemniscate_of_Bernoulli)
 in the tangent space of `p` sampled at `t` and use exp` to obtain a point on
 the [`Sphere`](https://juliamanifolds.github.io/Manifolds.jl/stable/manifolds/sphere.html).
@@ -302,7 +302,7 @@ artificial_S2_lemniscate(p, t::Float64, a::Float64=π / 2.0)
 @doc raw"""
     artificial_S2_lemniscate(p [,pts=128,a=π/2,interval=[0,2π])
 
-Generate a Signal on the [`Sphere`](https://juliamanifolds.github.io/Manifolds.jl/stable/manifolds/sphere.html) $\mathbb S^2$ by creating the
+Generate a Signal on the [`Sphere`](https://juliamanifolds.github.io/Manifolds.jl/stable/manifolds/sphere.html) ``\mathbb S^2`` by creating the
 [Lemniscate of Bernoulli](https://en.wikipedia.org/wiki/Lemniscate_of_Bernoulli)
 in the tangent space of `p` sampled at `pts` points and use `exp` to get a
 signal on the [`Sphere`](https://juliamanifolds.github.io/Manifolds.jl/stable/manifolds/sphere.html).

tutorials/HowToRecord.qmd

@@ -198,7 +198,7 @@ mutable struct RecordCount <: RecordAction
 end
 function (r::RecordCount)(p::AbstractManoptProblem, ::AbstractManoptSolverState, i)
     if i > 0
-        push!(r.recorded_values, get_cost_function(get_objective(p)).count)
+        push!(r.recorded_values, Manopt.get_cost_function(get_objective(p)).count)
     elseif i < 0 # reset if negative
         r.recorded_values = Vector{Int}()
     end