VectorQuadratic as VectorAffine (#231)

* VectorQuadratic as VectorAffine

* format

Author: joaquimg

.gitignore

@@ -2,3 +2,4 @@ docs/build
 docs/src/release_notes.md
 Manifest.toml
 .DS_Store
+*.cov

src/MOI_wrapper.jl

@@ -1107,6 +1107,24 @@ function MOI.add_constraint(
     set::MOI.AbstractVectorSet,
 ) where {T}
     if !_has_parameters(f)
+        # The user might construct a VectorQuadraticFunction with no actual
+        # quadratic terms (e.g. from a JuMP expression that simplifies to
+        # affine). Convert to VectorAffineFunction while still recording the
+        # outer_to_inner map so that get(ConstraintFunction) can return the
+        # original VectorQuadraticFunction type.
+        if _is_vector_affine(f)
+            fa = MOI.VectorAffineFunction(f.affine_terms, f.constants)
+            inner_ci = MOI.add_constraint(model.optimizer, fa, set)
+            model.last_vec_quad_add_added += 1
+            outer_ci =
+                MOI.ConstraintIndex{MOI.VectorQuadraticFunction{T},typeof(set)}(
+                    model.last_vec_quad_add_added,
+                )
+            model.vector_quadratic_outer_to_inner[outer_ci] = inner_ci
+            model.constraint_outer_to_inner[outer_ci] = inner_ci
+            model.vector_quadratic_constraint_cache_set[inner_ci] = set
+            return outer_ci
+        end
         return _add_constraint_direct_and_cache_map!(model, f, set)
     else
         return _add_constraint_with_parameters_on_function(model, f, set)

test/test_MathOptInterface.jl

@@ -2346,6 +2346,25 @@ function test_constraint_primal_start_get_for_parameter()
     return
 end
 
+function test_vector_quadratic_no_parameters_affine_get_constraint_function()
+    # A VectorQuadraticFunction with no parameters and no quadratic terms
+    # (empty quadratic_terms) should use the affine fast path. The outer
+    # constraint index is a VectorQuadraticFunction index (preserving the
+    # original type), but the inner optimizer stores it as VectorAffine.
+    # get(ConstraintFunction) must reconstruct the original VQF.
+    model = POI.Optimizer(MOI.Utilities.Model{Float64}())
+    x = MOI.add_variable(model)
+    quadratic_terms = MOI.VectorQuadraticTerm{Float64}[]
+    affine_terms = [MOI.VectorAffineTerm(1, MOI.ScalarAffineTerm(2.0, x))]
+    constants = [1.0]
+    f = MOI.VectorQuadraticFunction(quadratic_terms, affine_terms, constants)
+    ci = MOI.add_constraint(model, f, MOI.Zeros(1))
+    @test MOI.is_valid(model, ci)
+    f2 = MOI.get(model, MOI.ConstraintFunction(), ci)
+    @test canonical_compare(f, f2)
+    return
+end
+
 end # module
 
 TestMathOptInterfaceTests.runtests()