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some typos and formatting
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src/solvers/interior_point_Newton.jl

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@@ -24,7 +24,7 @@ $(_doc_IPN_subsystem)
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see [`CondensedKKTVectorFieldJacobian`](@ref) and [`CondensedKKTVectorField`](@ref), respectively,
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for the reduced form, this is usually solved in.
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From the resulting `X` and `Z` in the reeuced form, the other two, ``Y``, ``W``, are then computed.
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From the resulting `X` and `Z` in the reduced form, the other two, ``Y``, ``W``, are then computed.
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From the gradient ``(X,Y,Z,W)`` at the current iterate ``(p, μ, λ, s)``,
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a line search is performed using the [`KKTVectorFieldNormSq`](@ref) norm of the KKT vector field (squared)
@@ -89,11 +89,11 @@ $(_var(:Keyword, :sub_problem; default = "[`DefaultManoptProblem`](@ref)`(M, sub
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$(_var(:Keyword, :sub_state; default = "[`ConjugateResidualState`](@ref)"))
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* `vector_space=`[`Rn`](@ref Manopt.Rn) a function that, given an integer, returns the manifold to be used for the vector space components ``ℝ^m,ℝ^n``
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* `X=`[`zero_vector`](@extref `ManifoldsBase.zero_vector-Tuple{AbstractManifold, Any}`)`(M,p)`:
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th initial gradient with respect to `p`.
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* `Y=zero(μ)`: the initial gradient with respect to `μ`
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* `Z=zero(λ)`: the initial gradient with respect to `λ`
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* `W=zero(s)`: the initial gradient with respect to `s`
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* `is_feasible_error=:error`: specify how to handle infeasible starting points, see [`is_feasible`](@ref) for options.
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the initial gradient with respect to `p`.
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* `Y=zero(μ)`: the initial gradient with respect to `μ`
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* `Z=zero(λ)`: the initial gradient with respect to `λ`
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* `W=zero(s)`: the initial gradient with respect to `s`
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* `is_feasible_error=:error`: specify how to handle infeasible starting points, see [`is_feasible`](@ref) for options.
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As well as internal keywords used to set up these given keywords like `_step_M`, `_step_p`, `_sub_M`, `_sub_p`, and `_sub_X`,
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that should not be changed.

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