Fixes in cubic and constraint interpretation

src/MOI_wrapper.jl

@@ -135,6 +135,7 @@ function MOI.is_empty(model::Optimizer)
            # obj
            model.affine_objective_cache === nothing &&
            model.quadratic_objective_cache === nothing &&
+           model.cubic_objective_cache === nothing &&
            MOI.is_empty(model.original_objective_cache) &&
            #
            isempty(model.vector_affine_constraint_cache) &&
@@ -878,7 +879,7 @@ function _add_constraint_with_parameters_on_function(
         end
     elseif model.constraints_interpretation == ONLY_CONSTRAINTS
         poi_ci = MOI.add_constraint(model, pf, set)
-    elseif model.constraints_interpretation == BOUNDS_AND_CONSTRAINTS
+    else #if model.constraints_interpretation == BOUNDS_AND_CONSTRAINTS
         if length(affine_variable_terms(pf)) == 1 &&
            isone(MOI.coefficient(affine_variable_terms(pf)[]))
             poi_ci = _add_vi_constraint(model, pf, set)
@@ -1886,23 +1887,25 @@ ParametricOptInterface.Optimizer{Float64, MOIU.Model{Float64}}
 └ NumberOfConstraints: 0
 
 julia> MOI.set(model, POI.ConstraintsInterpretation(), POI.ONLY_BOUNDS)
-ONLY_BOUNDS::ConstraintsInterpretationCode = 1
 
 julia> MOI.set(model, POI.ConstraintsInterpretation(), POI.ONLY_CONSTRAINTS)
-ONLY_CONSTRAINTS::ConstraintsInterpretationCode = 0
 
 julia> MOI.set(model, POI.ConstraintsInterpretation(), POI.BOUNDS_AND_CONSTRAINTS)
-BOUNDS_AND_CONSTRAINTS::ConstraintsInterpretationCode = 2
 ```
 """
 struct ConstraintsInterpretation <: MOI.AbstractOptimizerAttribute end
 
+function MOI.get(model::Optimizer, ::ConstraintsInterpretation)
+    return model.constraints_interpretation
+end
+
 function MOI.set(
     model::Optimizer,
     ::ConstraintsInterpretation,
     value::ConstraintsInterpretationCode,
 )
-    return model.constraints_interpretation = value
+    model.constraints_interpretation = value
+    return
 end
 
 #

src/cubic_objective.jl

@@ -38,7 +38,7 @@ function MOI.set(
             "optimizer. " *
             "This may be due to unsupported features in the cubic " *
             "expression. " *
-            "Original error: $(e.msg)",
+            "Original error: $(sprint(showerror, e))",
         )
     end
 

src/update_parameters.jl

@@ -50,24 +50,14 @@ function _update_affine_constraints!(
         MOI.AbstractScalarSet,
     },
 ) where {F,S<:Union{MOI.LessThan,MOI.GreaterThan,MOI.EqualTo},V}
-    # cis = MOI.ConstraintIndex{F,S}[]
-    # sets = S[]
-    # sizehint!(cis, length(affine_constraint_cache_inner))
-    # sizehint!(sets, length(affine_constraint_cache_inner))
     for (inner_ci, pf) in affine_constraint_cache_inner
         delta_constant = _delta_parametric_constant(model, pf)
         if !iszero(delta_constant)
             pf.current_constant += delta_constant
             new_set = S(pf.set_constant - pf.current_constant)
-            # new_set = _set_with_new_constant(set, param_constant)
             MOI.set(model.optimizer, MOI.ConstraintSet(), inner_ci, new_set)
-            # push!(cis, inner_ci)
-            # push!(sets, new_set)
         end
     end
-    # if !isempty(cis)
-    #     MOI.set(model.optimizer, MOI.ConstraintSet(), cis, sets)
-    # end
     return
 end
 
@@ -192,19 +182,12 @@ function _update_quadratic_constraints!(
         MOI.AbstractScalarSet,
     },
 ) where {F,S<:Union{MOI.LessThan,MOI.GreaterThan,MOI.EqualTo},V}
-    # cis = MOI.ConstraintIndex{F,S}[]
-    # sets = S[]
-    # sizehint!(cis, length(quadratic_constraint_cache_inner))
-    # sizehint!(sets, length(quadratic_constraint_cache_inner))
     for (inner_ci, pf) in quadratic_constraint_cache_inner
         delta_constant = _delta_parametric_constant(model, pf)
         if !iszero(delta_constant)
             pf.current_constant += delta_constant
             new_set = S(pf.set_constant - pf.current_constant)
-            # new_set = _set_with_new_constant(set, param_constant)
             MOI.set(model.optimizer, MOI.ConstraintSet(), inner_ci, new_set)
-            # push!(cis, inner_ci)
-            # push!(sets, new_set)
         end
         delta_terms = _delta_parametric_affine_terms(model, pf)
         if !isempty(delta_terms)
@@ -213,9 +196,6 @@ function _update_quadratic_constraints!(
             MOI.modify(model.optimizer, cis, changes)
         end
     end
-    # if !isempty(cis)
-    #     MOI.set(model.optimizer, MOI.ConstraintSet(), cis, sets)
-    # end
     return
 end
 

test/test_MathOptInterface.jl

@@ -2181,6 +2181,40 @@ function test_name_from_bound()
     return
 end
 
+function test_constraints_interpretation_get_set()
+    model = POI.Optimizer(MOI.Utilities.Model{Float64}())
+    # Default value
+    @test MOI.get(model, POI.ConstraintsInterpretation()) ==
+          POI.ONLY_CONSTRAINTS
+    # Round-trip for each value
+    MOI.set(model, POI.ConstraintsInterpretation(), POI.ONLY_BOUNDS)
+    @test MOI.get(model, POI.ConstraintsInterpretation()) == POI.ONLY_BOUNDS
+    MOI.set(model, POI.ConstraintsInterpretation(), POI.ONLY_CONSTRAINTS)
+    @test MOI.get(model, POI.ConstraintsInterpretation()) ==
+          POI.ONLY_CONSTRAINTS
+    MOI.set(model, POI.ConstraintsInterpretation(), POI.BOUNDS_AND_CONSTRAINTS)
+    @test MOI.get(model, POI.ConstraintsInterpretation()) ==
+          POI.BOUNDS_AND_CONSTRAINTS
+    return
+end
+
+function test_only_bounds_coefficient_not_one_errors()
+    # ONLY_BOUNDS with coefficient ≠ 1 must error.
+    # The function must contain a parameter so that the parametric path is taken;
+    # a plain ScalarAffineFunction without parameters bypasses the check entirely.
+    model = POI.Optimizer(MOI.Utilities.Model{Float64}())
+    x = MOI.add_variable(model)
+    p, _ = MOI.add_constrained_variable(model, MOI.Parameter(1.0))
+    MOI.set(model, POI.ConstraintsInterpretation(), POI.ONLY_BOUNDS)
+    # 2.0 * x + 1.0 * p: single variable term with coefficient 2.0 ≠ 1 — must throw
+    f = MOI.ScalarAffineFunction(
+        [MOI.ScalarAffineTerm(2.0, x), MOI.ScalarAffineTerm(1.0, p)],
+        0.0,
+    )
+    @test_throws ErrorException MOI.add_constraint(model, f, MOI.LessThan(5.0))
+    return
+end
+
 function test_get_constraint_set()
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     x = MOI.add_variable(model)

test/test_cubic.jl

@@ -1567,6 +1567,32 @@ function test_optimize_skips_update_without_parameter_change()
     return
 end
 
+function test_is_empty_with_cubic_objective()
+    # Regression test: cubic_objective_cache must be checked in MOI.is_empty.
+    # Before the fix, is_empty ignored this cache and returned true incorrectly.
+    model = POI.Optimizer(HiGHS.Optimizer())
+    MOI.set(model, MOI.Silent(), true)
+    @test MOI.is_empty(model)
+
+    # Set a cubic objective to populate cubic_objective_cache
+    x = MOI.add_variable(model)
+    p, _ = MOI.add_constrained_variable(model, MOI.Parameter(1.0))
+    p_v = POI.v_idx(POI.p_idx(p))
+    f = MOI.ScalarNonlinearFunction(:*, Any[1.0, p_v, x, x])
+    MOI.set(model, MOI.ObjectiveFunction{MOI.ScalarNonlinearFunction}(), f)
+    @test !MOI.is_empty(model)
+
+    # After full empty!, model must be empty
+    cubic_cache = model.cubic_objective_cache
+    MOI.empty!(model)
+    @test MOI.is_empty(model)
+
+    # Restore only the cubic cache — is_empty must now return false
+    model.cubic_objective_cache = cubic_cache
+    @test !MOI.is_empty(model)
+    return
+end
+
 function test_jump_cubic_pvv_partial_pair_update()
     # Two pvv terms with different parameters: p1*x*y and p2*x*z.
     # Update only p1 -> delta_quadratic has only (x,y).