Pretty printing

src/abstract_types.jl

@@ -105,6 +105,10 @@ Abstract Type for all Line Search Algorithms used in NonlinearSolve.jl.
 """
 abstract type AbstractNonlinearSolveLineSearchAlgorithm end
 
+function Base.show(io::IO, alg::AbstractNonlinearSolveLineSearchAlgorithm)
+    print(io, "$(nameof(typeof(alg)))()")
+end
+
 abstract type AbstractNonlinearSolveLineSearchCache end
 
 """
@@ -179,8 +183,25 @@ end
 
 abstract type AbstractJacobianInitialization end
 
+function Base.show(io::IO, alg::AbstractJacobianInitialization)
+    modifiers = String[]
+    hasfield(typeof(alg), :structure) &&
+        push!(modifiers, "structure = $(nameof(typeof(alg.structure)))()")
+    print(io, "$(nameof(typeof(alg)))($(join(modifiers, ", ")))")
+    return nothing
+end
+
 abstract type AbstractApproximateJacobianUpdateRule{INV} end
 
+function Base.show(io::IO, alg::AbstractApproximateJacobianUpdateRule{INV}) where {INV}
+    if INV
+        print(io, "$(nameof(typeof(alg)))(stores_inverse = true)")
+    else
+        print(io, "$(nameof(typeof(alg)))()")
+    end
+    return nothing
+end
+
 store_inverse_jacobian(::AbstractApproximateJacobianUpdateRule{INV}) where {INV} = INV
 
 abstract type AbstractApproximateJacobianUpdateRuleCache{INV} end
@@ -189,6 +210,11 @@ store_inverse_jacobian(::AbstractApproximateJacobianUpdateRuleCache{INV}) where
 
 abstract type AbstractResetCondition end
 
+function Base.show(io::IO, alg::AbstractResetCondition)
+    print(io, "$(nameof(typeof(alg)))()")
+    return nothing
+end
+
 abstract type AbstractTrustRegionMethod end
 
 abstract type AbstractTrustRegionMethodCache end

src/core/approximate_jacobian.jl

@@ -9,6 +9,19 @@
     initialization
 end
 
+function Base.show(io::IO,
+        alg::ApproximateJacobianSolveAlgorithm{concrete_jac, name}) where {concrete_jac, name}
+    modifiers = String[]
+    __is_present(alg.linesearch) && push!(modifiers, "linesearch = $(alg.linesearch)")
+    __is_present(alg.trustregion) && push!(modifiers, "trustregion = $(alg.trustregion)")
+    push!(modifiers, "descent = $(alg.descent)")
+    push!(modifiers, "update_rule = $(alg.update_rule)")
+    push!(modifiers, "reinit_rule = $(alg.reinit_rule)")
+    push!(modifiers, "max_resets = $(alg.max_resets)")
+    push!(modifiers, "initialization = $(alg.initialization)")
+    print(io, "$(name)(\n    $(join(modifiers, ",\n    "))\n)")
+end
+
 function ApproximateJacobianSolveAlgorithm(; concrete_jac = nothing,
         name::Symbol = :unknown, kwargs...)
     return ApproximateJacobianSolveAlgorithm{concrete_jac, name}(; kwargs...)

src/core/generalized_first_order.jl

@@ -8,6 +8,18 @@
     reverse_ad
 end
 
+function Base.show(io::IO,
+        alg::GeneralizedFirstOrderAlgorithm{concrete_jac, name}) where {concrete_jac, name}
+    modifiers = String[]
+    __is_present(alg.linesearch) && push!(modifiers, "linesearch = $(alg.linesearch)")
+    __is_present(alg.trustregion) && push!(modifiers, "trustregion = $(alg.trustregion)")
+    push!(modifiers, "descent = $(alg.descent)")
+    __is_present(alg.jacobian_ad) && push!(modifiers, "jacobian_ad = $(alg.jacobian_ad)")
+    __is_present(alg.forward_ad) && push!(modifiers, "forward_ad = $(alg.forward_ad)")
+    __is_present(alg.reverse_ad) && push!(modifiers, "reverse_ad = $(alg.reverse_ad)")
+    print(io, "$(name)(\n    $(join(modifiers, ",\n    "))\n)")
+end
+
 function GeneralizedFirstOrderAlgorithm(; concrete_jac = nothing,
         name::Symbol = :unknown, kwargs...)
     return GeneralizedFirstOrderAlgorithm{concrete_jac, name}(; kwargs...)

src/core/spectral_methods.jl

@@ -8,6 +8,15 @@
     σ_1
 end
 
+function Base.show(io::IO, alg::GeneralizedDFSane{name}) where {name}
+    modifiers = String[]
+    __is_present(alg.linesearch) && push!(modifiers, "linesearch = $(alg.linesearch)")
+    push!(modifiers, "σ_min = $(alg.σ_min)")
+    push!(modifiers, "σ_max = $(alg.σ_max)")
+    push!(modifiers, "σ_1 = $(alg.σ_1)")
+    print(io, "$(name)(\n    $(join(modifiers, ",\n    "))\n)")
+end
+
 concrete_jac(::GeneralizedDFSane) = nothing
 
 @concrete mutable struct GeneralizedDFSaneCache{iip} <: AbstractNonlinearSolveCache{iip}

src/descent/damped_newton.jl

@@ -18,6 +18,15 @@ Based on the formulation we expect the damping factor returned to be a non-negat
     damping_fn
 end
 
+function Base.show(io::IO, d::DampedNewtonDescent)
+    modifiers = String[]
+    d.linsolve !== nothing && push!(modifiers, "linsolve = $(d.linsolve)")
+    d.precs !== DEFAULT_PRECS && push!(modifiers, "precs = $(d.precs)")
+    push!(modifiers, "initial_damping = $(d.initial_damping)")
+    push!(modifiers, "damping_fn = $(d.damping_fn)")
+    print(io, "DampedNewtonDescent($(join(modifiers, ", ")))")
+end
+
 supports_line_search(::DampedNewtonDescent) = true
 supports_trust_region(::DampedNewtonDescent) = true
 

src/descent/dogleg.jl

@@ -24,6 +24,11 @@ See also [`SteepestDescent`](@ref), [`NewtonDescent`](@ref), [`DampedNewtonDesce
     steepest_descent
 end
 
+function Base.show(io::IO, d::Dogleg)
+    print(io,
+        "Dogleg(newton_descent = $(d.newton_descent), steepest_descent = $(d.steepest_descent))")
+end
+
 supports_trust_region(::Dogleg) = true
 
 function Dogleg(; linsolve = nothing, precs = DEFAULT_PRECS, damping = False,

src/descent/geodesic_acceleration.jl

@@ -20,6 +20,11 @@ algorithm for nonlinear least-squares minimization." arXiv preprint arXiv:1201.5
     α
 end
 
+function Base.show(io::IO, alg::GeodesicAcceleration)
+    print(io, "GeodesicAcceleration(descent = $(alg.descent), finite_diff_step_geodesic = ",
+        "$(alg.finite_diff_step_geodesic), α = $(alg.α))")
+end
+
 supports_trust_region(::GeodesicAcceleration) = true
 
 @concrete mutable struct GeodesicAccelerationCache <: AbstractDescentCache

src/descent/newton.jl

@@ -23,6 +23,13 @@ See also [`Dogleg`](@ref), [`SteepestDescent`](@ref), [`DampedNewtonDescent`](@r
     precs = DEFAULT_PRECS
 end
 
+function Base.show(io::IO, d::NewtonDescent)
+    modifiers = String[]
+    d.linsolve !== nothing && push!(modifiers, "linsolve = $(d.linsolve)")
+    d.precs !== DEFAULT_PRECS && push!(modifiers, "precs = $(d.precs)")
+    print(io, "NewtonDescent($(join(modifiers, ", ")))")
+end
+
 supports_line_search(::NewtonDescent) = true
 
 @concrete mutable struct NewtonDescentCache{pre_inverted, normalform} <:

src/descent/steepest.jl

@@ -24,6 +24,13 @@ See also [`Dogleg`](@ref), [`NewtonDescent`](@ref), [`DampedNewtonDescent`](@ref
     precs = DEFAULT_PRECS
 end
 
+function Base.show(io::IO, d::SteepestDescent)
+    modifiers = String[]
+    d.linsolve !== nothing && push!(modifiers, "linsolve = $(d.linsolve)")
+    d.precs !== DEFAULT_PRECS && push!(modifiers, "precs = $(d.precs)")
+    print(io, "SteepestDescent($(join(modifiers, ", ")))")
+end
+
 supports_line_search(::SteepestDescent) = true
 
 @concrete mutable struct SteepestDescentCache{pre_inverted} <: AbstractDescentCache

src/globalization/line_search.jl

@@ -33,14 +33,24 @@ differentiation for fast Vector Jacobian Products.
     to `AutoFiniteDiff()`, which means that finite differencing is used to compute the VJP.
     `AutoZygote()` will be faster in most cases, but it requires `Zygote.jl` to be manually
     installed and loaded.
-  - `alpha`: the initial step size to use. Defaults to `true` (which is equivalent to `1`).
+  - `α`: the initial step size to use. Defaults to `true` (which is equivalent to `1`).
 """
 @concrete struct LineSearchesJL <: AbstractNonlinearSolveLineSearchAlgorithm
     method
     initial_alpha
     autodiff
 end
 
+function Base.show(io::IO, alg::LineSearchesJL)
+    str = "$(nameof(typeof(alg)))("
+    modifiers = String[]
+    alg.autodiff !== nothing &&
+        push!(modifiers, "autodiff = $(nameof(typeof(alg.autodiff)))()")
+    alg.initial_alpha != true && push!(modifiers, "initial_alpha = $(alg.initial_alpha)")
+    push!(modifiers, "method = $(alg.method)")
+    print(io, str, join(modifiers, ", "), ")")
+end
+
 LineSearchesJL(method; kwargs...) = LineSearchesJL(; method, kwargs...)
 function LineSearchesJL(; method = LineSearches.Static(), autodiff = nothing, α = true)
     return LineSearchesJL(method, α, autodiff)

src/utils.jl

@@ -81,3 +81,8 @@ LazyArrays.applied_axes(::typeof(__zero), x) = axes(x)
 @inline __get_nonsparse_ad(::AutoSparseFiniteDiff) = AutoFiniteDiff()
 @inline __get_nonsparse_ad(::AutoSparseZygote) = AutoZygote()
 @inline __get_nonsparse_ad(ad) = ad
+
+# Simple Checks
+@inline __is_present(::Nothing) = false
+@inline __is_present(::Missing) = false
+@inline __is_present(::Any) = true