Merge branch 'kellertuer/adding-aqua' of github.com:JuliaManifolds/Ma…

…nopt.jl into kellertuer/adding-aqua

src/plans/solver_state.jl

@@ -421,21 +421,16 @@ end
     X_init=zero_vector(M, p_init),
     once=true,
 )
-    if store_points isa Vector{Symbol}
-        TPS_tuple = tuple(store_points...)
-    else
-        TPS_tuple = Tuple(store_points.parameters)
-    end
-    if store_vectors isa Vector{Symbol}
-        TTS_tuple = tuple(store_vectors...)
-    else
-        TTS_tuple = Tuple(store_vectors.parameters)
-    end
+    TPS_tuple = _store_to_tuple(store_points)
+    TTS_tuple = _store_to_tuple(store_vectors)
     point_values = NamedTuple{TPS_tuple}(map(_ -> p_init, TPS_tuple))
     vector_values = NamedTuple{TTS_tuple}(map(_ -> X_init, TTS_tuple))
     return StoreStateAction(store_fields, point_values, vector_values, once; M=M)
 end
 
+_store_to_tuple(store::Type{<:Tuple}) = Tuple(store.parameters)
+_store_to_tuple(store::Vector{Symbol}) = tuple(store...)
+
 @generated function extract_type_from_namedtuple(::Type{nt}, ::Val{key}) where {nt,key}
     for i in 1:length(nt.parameters[1])
         if nt.parameters[1][i] === key

src/solvers/particle_swarm.jl

@@ -216,7 +216,7 @@ Instead of a cost function `f` you can also provide an [`AbstractManifoldCostObj
 * `social_weight`:             (`1.4`) a social weight factor
 * `stopping_criterion`:        ([`StopAfterIteration`](@ref)`(500) | `[`StopWhenChangeLess`](@ref)`(1e-4)`)
   a functor inheriting from [`StoppingCriterion`](@ref) indicating when to stop.
-* `vector_transport_mthod`:    (`default_vector_transport_method(M, eltype(swarm))`) a vector transport method to use.
+* `vector_transport_method`:   (`default_vector_transport_method(M, eltype(swarm))`) a vector transport method to use.
 * `velocity`:                  a set of tangent vectors (of type `AbstractVector{T}`) representing the velocities of the particles, per default a random tangent vector per initial position
 
 All other keyword arguments are passed to [`decorate_state!`](@ref) for decorators or
@@ -269,8 +269,8 @@ function particle_swarm(
 end
 
 @doc raw"""
-    patricle_swarm!(M, f, swarm; kwargs...)
-    patricle_swarm!(M, mco::AbstractManifoldCostObjective, swarm; kwargs..)
+    particle_swarm!(M, f, swarm; kwargs...)
+    particle_swarm!(M, mco::AbstractManifoldCostObjective, swarm; kwargs..)
 
 perform the particle swarm optimization algorithm (PSO), starting with the initial `swarm` which is then modified in place.