Merge branch 'libprima:main' into main

Project.toml

@@ -8,7 +8,17 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 PRIMA_jll = "eead6e0c-2d5b-5641-a95c-b722de96d551"
 TypeUtils = "c3b1956e-8857-4d84-9b79-890df85b1e67"
 
+[weakdeps]
+CUTEst = "1b53aba6-35b6-5f92-a507-53c67d53f819"
+NLPModels = "a4795742-8479-5a88-8948-cc11e1c8c1a6"
+
+[extensions]
+PRIMACUTEstExt = "CUTEst"
+PRIMANLPModelsExt = "NLPModels"
+
 [compat]
+CUTEst = "0.13"
+NLPModels = "0.20"
 PRIMA_jll = "0.7.1"
 TypeUtils = "0.3"
 julia = "1.6"

ext/PRIMACUTEstExt.jl

@@ -0,0 +1,24 @@
+module PRIMACUTEstExt
+
+if isdefined(Base, :get_extension)
+    using NLPModels
+    using CUTEst
+    using PRIMA
+else
+    using ..NLPModels
+    using ..CUTEst
+    using ..PRIMA
+end
+
+for func in (:uobyqa, :newuoa, :bobyqa, :lincoa, :cobyla, :prima)
+    @eval function PRIMA.$(Symbol(func,"_CUTEst"))(name::AbstractString; kwds...)
+        nlp = CUTEstModel(name)
+        try
+            return $func(nlp; kwds...)
+        finally
+            finalize(nlp)
+        end
+    end
+end
+
+end # module

ext/PRIMANLPModelsExt.jl

@@ -0,0 +1,82 @@
+module PRIMANLPModelsExt
+
+if isdefined(Base, :get_extension)
+    using NLPModels
+    using PRIMA
+else
+    using ..NLPModels
+    using ..PRIMA
+end
+
+# This structure is to wrap a non-linear problem model into a callable object.
+struct ObjectiveFunction{F<:AbstractNLPModel} <: Function
+    nlp::F
+end
+(f::ObjectiveFunction)(x::AbstractVector) = obj(f.nlp, x)
+
+function check_variables(nlp::AbstractNLPModel, x0::AbstractVector)
+    length(x0) == get_nvar(nlp) || error(
+        "initial variables must have $(get_nvar(nlp)) elements")
+    return x0
+end
+
+const Variables = AbstractVector{<:Real}
+
+for func in (:uobyqa, :newuoa)
+    @eval function PRIMA.$func(nlp::AbstractNLPModel, x0::Variables = get_x0(nlp); kwds...)
+        has_bounds(nlp) && error("`$($func)` cannot solve problems with bound constraints")
+        has_equalities(nlp) && error("`$($func)` cannot solve problems with equality constraints")
+        has_inequalities(nlp) && error("`$($func)` cannot solve problems with inequality constraints")
+        return uobyqa(ObjectiveFunction(nlp), check_variables(nlp, x0);  kwds...)
+    end
+end
+
+function PRIMA.bobyqa(nlp::AbstractNLPModel, x0::Variables = get_x0(nlp); kwds...)
+    has_equalities(nlp) && error("`bobyqa` cannot solve problems with equality constraints")
+    has_inequalities(nlp) && error("`bobyqa` cannot solve problems with inequality constraints")
+    return bobyqa(ObjectiveFunction(nlp), check_variables(nlp, x0); kwds...,
+                  xl = get_lvar(nlp), xu = get_uvar(nlp))
+end
+
+function PRIMA.lincoa(nlp::AbstractNLPModel, x0::Variables = get_x0(nlp); kwds...)
+    nlin = get_nlin(nlp) # number of linear constraints
+    nnln = get_nnln(nlp) # number of non-linear constraints
+    nlin == 0 || error("linear constraints not yet implemented for NLPModels in `lincoa`")
+    nnln == 0 || error("`lincoa` cannot solve problems with non-linear constraints")
+    return lincoa(ObjectiveFunction(nlp), check_variables(nlp, x0); kwds...,
+                  xl = get_lvar(nlp), xu = get_uvar(nlp),
+                  linear_eq = nothing, linear_ineq = nothing)
+end
+
+function PRIMA.cobyla(nlp::AbstractNLPModel, x0::Variables = get_x0(nlp); kwds...)
+    nlin = get_nlin(nlp) # number of linear constraints
+    nnln = get_nnln(nlp) # number of non-linear constraints
+    nlin == 0 || error("linear constraints not yet implemented for NLPModels in `cobyla`")
+    nnln == 0 || error("non-linear constraints not yet implemented for NLPModels in `cobyla`")
+    return cobyla(ObjectiveFunction(nlp), check_variables(nlp, x0); kwds...,
+                  xl = get_lvar(nlp), xu = get_uvar(nlp),
+                  linear_eq = nothing, linear_ineq = nothing,
+                  nonlinear_eq = nothing, nonlinear_ineq = nothing)
+end
+
+function PRIMA.prima(nlp::AbstractNLPModel, x0::Variables = get_x0(nlp); kwds...)
+    nlin = get_nlin(nlp) # number of linear constraints
+    nnln = get_nnln(nlp) # number of non-linear constraints
+    if nnln > 0
+        # Only COBYLA can deal with non-linear constraints.
+        error("solving problem with non-linear constraints by COBYLA not yet implemented")
+        return cobyla(nlp, x0; kwds...)
+    elseif nlin > 0
+        # LINCOA can deal with bounds and linear constraints.
+        error("solving problem with linear constraints by LINCOA not yet implemented")
+        return lincoa(nlp, x0; kwds...)
+    elseif has_bounds(nlp)
+        # BOBYQA can deal with bounds.
+        return bobyqa(nlp, x0; kwds...)
+    else
+        # Use NEWUOA for unconstrained problems.
+        return newuoa(nlp, x0; kwds...)
+    end
+end
+
+end # module

src/PRIMA.jl

@@ -985,4 +985,21 @@ function _get_scaling(scl::AbstractVector{<:Real}, n::Int)
     return convert(Vector{Cdouble}, scl)
 end
 
+for func in (:uobyqa, :newuoa, :bobyqa, :lincoa, :cobyla, :prima)
+    @eval $(Symbol(func,"_CUTEst"))(args...; kwds...) =
+        error("invalid arguments or `CUTEst` package not yet loaded")
+end
+
+@static if !isdefined(Base, :get_extension)
+    using Requires
+    function __init__()
+        if !isdefined(Base, :get_extension)
+            @require CUTEst = "1b53aba6-35b6-5f92-a507-53c67d53f819" include(
+                "../ext/PRIMACUTEstExt.jl")
+            @require NLPModels = "a4795742-8479-5a88-8948-cc11e1c8c1a6" include(
+                "../ext/PRIMANLPModelsExt.jl")
+        end
+    end
+end
+
 end # module