Refactor code base

Author: devmotion

.github/workflows/Test.yml

@@ -23,12 +23,6 @@ jobs:
           - 'lts'
           - '1'
         os: [ubuntu-latest, windows-latest, macOS-latest]
-        exclude:
-          - os: macOS-latest # Apple Silicon
-            version: 'min'
-        include:
-          - os: macOS-13 # Intel
-            version: 'min'
     steps:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v2

Project.toml

@@ -1,6 +1,6 @@
 name = "NLSolversBase"
 uuid = "d41bc354-129a-5804-8e4c-c37616107c6c"
-version = "7.10.0"
+version = "7.11.0"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"

README.md

@@ -175,10 +175,10 @@ interface as shown below.
 ```julia
 function fg!(F, G, x)
     common_calc(...)
-    if !(G == nothing)
+    if G !== nothing
         # mutating calculations specific to g!
     end
-    if !(F == nothing)
+    if F !== nothing
         # calculations specific to f
         return f
     end

src/NLSolversBase.jl

@@ -1,5 +1,3 @@
-__precompile__(true)
-
 module NLSolversBase
 
 using ADTypes: AbstractADType, AutoForwardDiff, AutoFiniteDiff
@@ -51,7 +49,7 @@ function finitediff_fdtype(autodiff)
         fdtype = Val{:forward}
     elseif autodiff == :finitecomplex
         fdtype = Val{:complex}
-    elseif any(autodiff .== (:finite, :central, :finitecentral))
+    elseif autodiff == :finite || autodiff == :central || autodiff == :finitecentral
         fdtype = Val{:central}
     end
     fdtype
@@ -71,11 +69,11 @@ function get_adtype(autodiff::Union{Symbol,Bool}, chunk=nothing)
     elseif is_forwarddiff(autodiff)
         return AutoForwardDiff(; chunksize=forwarddiff_chunksize(chunk))
     else
-        error("The autodiff value $autodiff is not supported. Use :finite or :forward.")
+        throw(ArgumentError(LazyString("The autodiff value `", repr(autodiff), "` is not supported. Use `:finite` or `:forward`.")))
     end
 end
 
-x_of_nans(x, Tf=eltype(x)) = fill!(Tf.(x), Tf(NaN))
+x_of_nans(x::AbstractArray, ::Type{Tf}=float(eltype(x))) where {Tf} = fill!(similar(x, Tf), NaN)
 
 include("objective_types/inplace_factory.jl")
 include("objective_types/abstract.jl")

src/interface.jl

@@ -4,7 +4,7 @@ Force (re-)evaluation of the objective value at `x`.
 Returns `f(x)` and stores the value in `obj.F`
 """
 function value!!(obj::AbstractObjective, x)
-    obj.f_calls .+= 1
+    obj.f_calls += 1
     copyto!(obj.x_f, x)
     obj.F = obj.f(x)
     value(obj)
@@ -15,7 +15,7 @@ Evaluates the objective value at `x`.
 Returns `f(x)`, but does *not* store the value in `obj.F`
 """
 function value(obj::AbstractObjective, x)
-    obj.f_calls .+= 1
+    obj.f_calls += 1
     return obj.f(x)
 end
 """
@@ -38,7 +38,7 @@ This does *not* update `obj.DF` or `obj.x_df`.
 function gradient(obj::AbstractObjective, x)
     newdf = copy(obj.DF)
     obj.df(newdf, x)
-    obj.df_calls .+= 1
+    obj.df_calls += 1
     return newdf
 end
 """
@@ -58,7 +58,7 @@ Force (re-)evaluation of the gradient value at `x`.
 Stores the value in `obj.DF`.
 """
 function gradient!!(obj::AbstractObjective, x)
-    obj.df_calls .+= 1
+    obj.df_calls += 1
     copyto!(obj.x_df, x)
     obj.df(obj.DF, x)
     gradient(obj)
@@ -75,8 +75,8 @@ function value_gradient!(obj::AbstractObjective, x)
     value(obj), gradient(obj)
 end
 function value_gradient!!(obj::AbstractObjective, x)
-    obj.f_calls .+= 1
-    obj.df_calls .+= 1
+    obj.f_calls += 1
+    obj.df_calls += 1
     copyto!(obj.x_f, x)
     copyto!(obj.x_df, x)
     obj.F = obj.fdf(gradient(obj), x)
@@ -90,7 +90,7 @@ function hessian!(obj::AbstractObjective, x)
     hessian(obj)
 end
 function hessian!!(obj::AbstractObjective, x)
-    obj.h_calls .+= 1
+    obj.h_calls += 1
     copyto!(obj.x_h, x)
     obj.h(obj.H, x)
     hessian(obj)
@@ -124,8 +124,8 @@ function value_jacobian!!(obj, F, J, x)
     obj.fdf(F, J, x)
     copyto!(obj.x_f, x)
     copyto!(obj.x_df, x)
-    obj.f_calls .+= 1
-    obj.df_calls .+= 1
+    obj.f_calls += 1
+    obj.df_calls += 1
     obj.df_calls
     F, J
 end
@@ -141,7 +141,7 @@ jacobian!!(obj, x) = jacobian!!(obj, obj.DF, x)
 function jacobian!!(obj, J, x)
     obj.df(J, x)
     copyto!(obj.x_df, x)
-    obj.df_calls .+= 1
+    obj.df_calls += 1
     obj.df_calls
     J
 end
@@ -156,7 +156,7 @@ end
 value(obj::NonDifferentiable{TF, TX}, x) where {TF<:AbstractArray, TX} = value(obj, copy(obj.F), x)
 value(obj::OnceDifferentiable{TF, TDF, TX}, x) where {TF<:AbstractArray, TDF, TX} = value(obj, copy(obj.F), x)
 function value(obj::AbstractObjective, F, x)
-    obj.f_calls .+= 1
+    obj.f_calls += 1
     return obj.f(F, x)
 end
 
@@ -165,41 +165,41 @@ value!!(obj::OnceDifferentiable{TF, TDF, TX}, x) where {TF<:AbstractArray, TDF,
 function value!!(obj::AbstractObjective, F, x)
     obj.f(F, x)
     copyto!(obj.x_f, x)
-    obj.f_calls .+= 1
+    obj.f_calls += 1
     obj.f_calls
     F
 end
 
 function _clear_f!(d::NLSolversBase.AbstractObjective)
-    d.f_calls .= 0
-    if typeof(d.F) <: AbstractArray
-        d.F .= eltype(d.F)(NaN)
+    d.f_calls = 0
+    if d.F isa AbstractArray
+        fill!(d.F, NaN)
     else
-        d.F = typeof(d.F)(NaN)
+        d.F = NaN
     end
-    d.x_f .= eltype(d.x_f)(NaN)
+    fill!(d.x_f, NaN)
     nothing
 end
 
 function _clear_df!(d::NLSolversBase.AbstractObjective)
-    d.df_calls .= 0
-    d.DF .= eltype(d.DF)(NaN)
-    d.x_df .= eltype(d.x_df)(NaN)
+    d.df_calls = 0
+    fill!(d.DF, NaN)
+    fill!(d.x_df, NaN)
     nothing
 end
 
 function _clear_h!(d::NLSolversBase.AbstractObjective)
-    d.h_calls .= 0
-    d.H .= eltype(d.H)(NaN)
-    d.x_h .= eltype(d.x_h)(NaN)
+    d.h_calls = 0
+    fill!(d.H, NaN)
+    fill!(d.x_h, NaN)
     nothing
 end
 
 function _clear_hv!(d::NLSolversBase.AbstractObjective)
-    d.hv_calls .= 0
-    d.Hv .= eltype(d.Hv)(NaN)
-    d.x_hv .= eltype(d.x_hv)(NaN)
-    d.v_hv .= eltype(d.v_hv)(NaN)
+    d.hv_calls = 0
+    fill!(d.Hv, NaN)
+    fill!(d.x_hv, NaN)
+    fill!(d.v_hv, NaN)
     nothing
 end
 
@@ -227,9 +227,9 @@ end
 
 g_calls(d::NonDifferentiable) = 0
 h_calls(d::Union{NonDifferentiable, OnceDifferentiable}) = 0
-f_calls(d) = first(d.f_calls)
-g_calls(d) = first(d.df_calls)
-h_calls(d) = first(d.h_calls)
+f_calls(d) = d.f_calls
+g_calls(d) = d.df_calls
+h_calls(d) = d.h_calls
 hv_calls(d) = 0
 h_calls(d::TwiceDifferentiableHV) = 0
-hv_calls(d::TwiceDifferentiableHV) = first(d.hv_calls)
+hv_calls(d::TwiceDifferentiableHV) = d.hv_calls

src/objective_types/constraints.jl

@@ -40,10 +40,10 @@ function _cb(lx::AbstractArray{Tx}, ux::AbstractArray{Tx}, lc::AbstractVector{Tc
 end
 
 Base.eltype(::Type{ConstraintBounds{T}}) where T = T
-Base.eltype(cb::ConstraintBounds) = eltype(typeof(cb))
 
+Base.convert(::Type{ConstraintBounds{T}}, cb::ConstraintBounds{T}) where {T} = cb
 Base.convert(::Type{ConstraintBounds{T}}, cb::ConstraintBounds{S}) where {T,S} =
-    ConstraintBounds(cb.nc, cb.eqx, convert(Vector{T}, cb.valx),
+    ConstraintBounds{T}(cb.nc, cb.eqx, convert(Vector{T}, cb.valx),
                      cb.ineqx, cb.σx, convert(Vector{T}, cb.bx),
                      cb.eqc, convert(Vector{T}, cb.valc), cb.ineqc,
                      cb.σc, convert(Vector{T}, cb.bc))
@@ -80,11 +80,11 @@ function Base.show(io::IO, cb::ConstraintBounds)
     indent = "    "
     print(io, "ConstraintBounds:")
     print(io, "\n  Variables:")
-    showeq(io, indent, cb.eqx, cb.valx, 'x', :bracket)
-    showineq(io, indent, cb.ineqx, cb.σx, cb.bx, 'x', :bracket)
+    showeq(io, indent, cb.eqx, cb.valx, 'x', true) # bracket
+    showineq(io, indent, cb.ineqx, cb.σx, cb.bx, 'x', true) # bracket
     print(io, "\n  Linear/nonlinear constraints:")
-    showeq(io, indent, cb.eqc, cb.valc, 'c', :subscript)
-    showineq(io, indent, cb.ineqc, cb.σc, cb.bc, 'c', :subscript)
+    showeq(io, indent, cb.eqc, cb.valc, 'c', false) # subscript
+    showineq(io, indent, cb.ineqc, cb.σc, cb.bc, 'c', false) # subscript
     nothing
 end
 
@@ -281,17 +281,17 @@ corresponding entry in `ineq`/`σ`/`b`.
 T is the element-type of the non-Int outputs
 """
 function parse_constraints(::Type{T}, l, u) where T
-    size(l) == size(u) || throw(DimensionMismatch("l and u must be the same size, got $(size(l)) and $(size(u))"))
+    if size(l) != size(u)
+        throw(DimensionMismatch(LazyString("Size of lower bounds (", size(l), ") and number of upper bounds (", size(u), ") must be equal.")))
+    end
     eq, ineq = Int[], Int[]
+    σ = Int8[]
     val, b = T[], T[]
-    σ = Array{Int8}(undef, 0)
-    for i = 1:length(l)
-        li, ui = l[i], u[i]
-        li <= ui || throw(ArgumentError("l must be smaller than u, got $li, $ui"))
+    for (i, (li, ui)) in enumerate(zip(l, u))
         if li == ui
             push!(eq, i)
             push!(val, ui)
-        else
+        elseif li < ui
             if isfinite(li)
                 push!(ineq, i)
                 push!(σ, 1)
@@ -302,36 +302,55 @@ function parse_constraints(::Type{T}, l, u) where T
                 push!(σ, -1)
                 push!(b, ui)
             end
+        else
+            throw(ArgumentError(LazyString("Lower bound (", li, ") must not be greater than upper bound (", ui, ").")))
         end
     end
     eq, val, ineq, σ, b
 end
 
 ### Compact printing of constraints
 
-function showeq(io, indent, eq, val, chr, style)
-    if !isempty(eq)
+function showeq(io::IO, indent::String, eqs::Vector{Int}, vals::Vector, chr::Char, bracket::Bool)
+    if !isempty(eqs)
         print(io, '\n', indent)
-        if style == :bracket
-            eqstrs = map((i, v)->"$chr[$i]=$v", eq, val)
+        if bracket
+            for (i, (eq, val)) in enumerate(zip(eqs, vals))
+                if i != 1
+                    print(io, ", ")
+                end
+                print(io, chr, "[", eq, "]=", val)
+            end
         else
-            eqstrs = map((i, v)->"$(chr)_$i=$v", eq, val)
+            for (i, (eq, val)) in enumerate(zip(eqs, vals))
+                if i != 1
+                    print(io, ", ")
+                end
+                print(io, chr, "_", eq, "=", val)
+            end
         end
-        foreach(s->print(io, s * ", "), eqstrs[1:end - 1])
-        print(io, eqstrs[end])
     end
+    return nothing
 end
 
-function showineq(io, indent, ineqs, σs, bs, chr, style)
+function showineq(io::IO, indent::String, ineqs::Vector{Int}, σs::Vector{Int8}, bs::Vector, chr::Char, bracket::Bool)
     if !isempty(ineqs)
         print(io, '\n', indent)
-        if style == :bracket
-            ineqstrs = map((i, σ, b)->"$chr[$i]" * ineqstr(σ, b), ineqs, σs, bs)
+        if bracket
+            for (i, (ineq, σ, b)) in enumerate(zip(ineqs, σs, bs))
+                if i != 1
+                    print(io, ", ")
+                end
+                print(io, chr, "[", ineq, "]", σ > 0 ? '≥' : '≤', b)
+            end
         else
-            ineqstrs = map((i, σ, b)->"$(chr)_$i" * ineqstr(σ, b), ineqs, σs, bs)
+            for (i, (ineq, σ, b)) in enumerate(zip(ineqs, σs, bs))
+                if i != 1
+                    print(io, ", ")
+                end
+                print(io, chr, "_", ineq, σ > 0 ? '≥' : '≤', b)
+            end
         end
-        foreach(s->print(io, s * ", "), ineqstrs[1:end - 1])
-        print(io, ineqstrs[end])
     end
+    return nothing
 end
-ineqstr(σ, b) = σ > 0 ? "≥$b" : "≤$b"

src/objective_types/incomplete.jl

@@ -4,7 +4,7 @@
 # and have NLSolversBase wrap them up properly so "F" can be
 # calculated on its own and the save for partial derivatives.
 # Note, that for TwiceDifferentiable we cannot provide con-
-# structors if h == nothing, as that requires automatic dif-
+# structors if h === nothing, as that requires automatic dif-
 # fferentiation of some sort.
 struct InplaceObjective{DF, FDF, FGH, Hv, FGHv}
     df::DF
@@ -106,7 +106,7 @@ function TwiceDifferentiable(t::InPlaceFGH, x::AbstractArray, F::Real = real(zer
     TwiceDifferentiable(f, df, fdf, dfh, fdfh, h,
                                         copy(F), copy(G), copy(H),
                                         x_f, x_df, x_h,
-                                        [0,], [0,], [0,])
+                                        0, 0, 0)
 end
 function TwiceDifferentiable(t::InPlaceFGH, x::AbstractVector{T}, F::Real = real(zero(eltype(x))), G::AbstractVector{Tx} = alloc_DF(x, F)) where {T, Tx}
     f   =     x  -> t.fgh(F, nothing, nothing, x)
@@ -122,15 +122,15 @@ function TwiceDifferentiable(t::InPlaceFGH, x::AbstractVector{T}, F::Real = real
     TwiceDifferentiable(f, df, fdf, dfh, fdfh, h,
                                         copy(F), copy(G), copy(H),
                                         x_f, x_df, x_h,
-                                        [0,], [0,], [0,])
+                                        0, 0, 0)
 end
 function value_gradient_hessian!!(obj, x)
-    obj.f_calls .+= 1
-    obj.df_calls .+= 1
-    obj.h_calls .+= 1
-    obj.x_f  .= x
-    obj.x_df .= x
-    obj.x_h  .= x
+    obj.f_calls += 1
+    obj.df_calls += 1
+    obj.h_calls += 1
+    copyto!(obj.x_f, x)
+    copyto!(obj.x_df, x)
+    copyto!(obj.x_h, x)
     if obj.fdfh === nothing
         obj.F = obj.fdf(obj.DF, x)
         obj.h(obj.H, x)
@@ -145,10 +145,10 @@ function gradient_hessian!!(obj, x)
         gradient!!(obj, x)
         hessian!!(obj, x)
     else
-        obj.df_calls .+= 1
-        obj.h_calls .+= 1
-        obj.x_df .= x
-        obj.x_h  .= x
+        obj.df_calls += 1
+        obj.h_calls += 1
+        copyto!(obj.x_df, x)
+        copyto!(obj.x_h, x)
         obj.dfh(obj.DF, obj.H, x)
     end
     obj.DF, obj.H