Merge branch 'master' into mbaran/safer-step-qn

# Conflicts:
#	Changelog.md

.gitignore

@@ -23,3 +23,4 @@ docs/src/tutorials/*.html
 docs/src/changelog.md
 docs/styles/Google
 tutorials/LocalPreferences.toml
+temp

Changelog.md

@@ -5,11 +5,18 @@ 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).
 
-## [0.4.55] unreleased
+## [0.4.55] March 3, 2024
 
 ### Added
 
-* Option `nondescent_direction_behavior` for quasi-Newton solvers. By default it checks for non-descent direction which may not be handled well by some stepsize selection algorithms.
+* Option `nondescent_direction_behavior` for quasi-Newton solvers.
+  By default it checks for non-descent direction which may not be handled well by
+  some stepsize selection algorithms.
+
+### Fixed
+
+* unified documentation, especially function signatures further.
+* fixed a few typos related to math formulae in the doc strings.
 
 ## [0.4.54] February 28, 2024
 

Project.toml

@@ -10,7 +10,6 @@ Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-LinearOperators = "5c8ed15e-5a4c-59e4-a42b-c7e8811fb125"
 ManifoldDiff = "af67fdf4-a580-4b9f-bbec-742ef357defd"
 ManifoldsBase = "3362f125-f0bb-47a3-aa74-596ffd7ef2fb"
 Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
@@ -49,7 +48,6 @@ Dates = "1.6"
 JuMP = "1.15"
 LRUCache = "1.4"
 LinearAlgebra = "1.6"
-LinearOperators = "~2.6"
 ManifoldDiff = "0.3.8"
 Manifolds = "0.9.11"
 ManifoldsBase = "0.15"
@@ -61,7 +59,7 @@ Printf = "1.6"
 QuadraticModels = "0.9"
 Random = "1.6"
 Requires = "0.5, 1"
-RipQP = "0.6"
+RipQP = "0.6.4"
 SparseArrays = "1.6"
 Statistics = "1.6"
 Test = "1.6"

src/solvers/NelderMead.jl

@@ -169,8 +169,10 @@ function set_iterate!(O::NelderMeadState, ::AbstractManifold, p)
 end
 
 @doc raw"""
-    NelderMead(M::AbstractManifold, f [, population::NelderMeadSimplex])
-    NelderMead(M::AbstractManifold, mco::AbstractManifoldCostObjective [, population::NelderMeadSimplex])
+    NelderMead(M::AbstractManifold, f)
+    NelderMead(M::AbstractManifold, f, population::NelderMeadSimplex)
+    NelderMead(M::AbstractManifold, mco::AbstractManifoldCostObjective)
+    NelderMead(M::AbstractManifold, mco::AbstractManifoldCostObjective, population::NelderMeadSimplex)
 
 Solve a Nelder-Mead minimization problem for the cost function ``f:  \mathcal M`` on the
 manifold `M`. If the initial population `p` is not given, a random set of

src/solvers/particle_swarm.jl

@@ -158,19 +158,19 @@ The aim of PSO is to find the particle position ``p`` on the `Manifold M` that s
 \min_{p ∈\mathcal{M}} F(p).
 ```
 
-To this end, a swarm ``S = \{s_1,\ldots_s_n\}`` of particles is moved around the manifold `M` in the following manner.
+To this end, a swarm ``S = \{s_1, \ldots, s_n\}`` of particles is moved around the manifold `M` in the following manner.
 For every particle ``s_k^{(i)}`` the new particle velocities ``X_k^{(i)}`` are computed in every step ``i`` of the algorithm by
 
 ```math
-begin{aligned*}
-  X_k^{(i)} &= ω \, \operatorname{T}_{s_k^{(i)}\gets s_k^{(i-1)}}X_k^{(i-1)} + c r_1  \operatorname{retr}_{s_k^{(i)}}^{-1}(p_k^{(i)}) + s r_2 \operatorname{retr}_{s_k^{(i)}}^{-1}(p),
+  X_k^{(i)} = ω \, \operatorname{T}_{s_k^{(i)}\gets s_k^{(i-1)}}X_k^{(i-1)} + c r_1  \operatorname{retr}_{s_k^{(i)}}^{-1}(p_k^{(i)}) + s r_2 \operatorname{retr}_{s_k^{(i)}}^{-1}(p),
 ```
 
-where ``s_k^{(i)}`` is the current particle position, ``ω`` denotes the inertia,
-``c`` and ``s`` are a cognitive and a social weight, respectively,
-``r_j``, ``j=1,2`` are random factors which are computed new for each particle and step,
-``\operatorname{retr}^{-1}`` denotes an inverse retraction on the `Manifold` `M`, and
-``\operatorname{T}`` is a vector transport.
+where
+* ``s_k^{(i)}`` is the current particle position,
+* ``ω`` denotes the inertia,
+* ``c`` and ``s`` are a cognitive and a social weight, respectively,
+* ``r_j``, ``j=1,2`` are random factors which are computed new for each particle and step
+* ``T`` denotes the vector transport and ``\operatorname{retr}^{-1}`` the inverse retraction used
 
 Then the position of the particle is updated as
 

test/solvers/test_convex_bundle_method.jl

@@ -146,7 +146,7 @@ using Manopt: sectional_curvature, ζ_1, ζ_2, close_point
         )
         @test -10eps() ≤ cbms3.ϱ ≤ 10eps()
     end
-    @testset "A simple median rum" begin
+    @testset "A simple median run" begin
         M = Sphere(2)
         p1 = [1.0, 0.0, 0.0]
         p2 = 1 / sqrt(2) .* [1.0, 1.0, 0.0]