Cleanup terms getters

src/MOI_wrapper.jl

@@ -71,7 +71,7 @@ function _cache_multiplicative_params!(
     model::Optimizer{T},
     f::ParametricQuadraticFunction{T},
 ) where {T}
-    for term in f.pv
+    for term in quadratic_parameter_variable_terms(f)
         push!(model.multiplicative_parameters_pv, term.variable_1.value)
     end
     return
@@ -81,7 +81,7 @@ function _cache_multiplicative_params!(
     model::Optimizer{T},
     f::ParametricVectorQuadraticFunction{T},
 ) where {T}
-    for term in f.pv
+    for term in vector_quadratic_parameter_variable_terms(f)
         push!(
             model.multiplicative_parameters_pv,
             term.scalar_term.variable_1.value,
@@ -94,13 +94,13 @@ function _cache_multiplicative_params!(
     model::Optimizer{T},
     f::ParametricCubicFunction{T},
 ) where {T}
-    for term in f.pv
+    for term in cubic_parameter_variable_terms(f)
         push!(model.multiplicative_parameters_pv, term.variable_1.value)
     end
-    for term in f.pvv
+    for term in cubic_parameter_variable_variable_terms(f)
         push!(model.multiplicative_parameters_pv, term.index_1.value)
     end
-    for term in f.ppv
+    for term in cubic_parameter_parameter_variable_terms(f)
         push!(model.multiplicative_parameters_pv, term.index_1.value)
         push!(model.multiplicative_parameters_pv, term.index_2.value)
     end
@@ -868,7 +868,8 @@ function _add_constraint_with_parameters_on_function(
 ) where {T,S}
     pf = ParametricAffineFunction(f)
     if model.constraints_interpretation == ONLY_BOUNDS
-        if length(pf.v) == 1 && isone(MOI.coefficient(pf.v[]))
+        if length(affine_variable_terms(pf)) == 1 &&
+           isone(MOI.coefficient(affine_variable_terms(pf)[]))
             poi_ci = _add_vi_constraint(model, pf, set)
         else
             error(
@@ -878,7 +879,8 @@ function _add_constraint_with_parameters_on_function(
     elseif model.constraints_interpretation == ONLY_CONSTRAINTS
         poi_ci = MOI.add_constraint(model, pf, set)
     elseif model.constraints_interpretation == BOUNDS_AND_CONSTRAINTS
-        if length(pf.v) == 1 && isone(MOI.coefficient(pf.v[]))
+        if length(affine_variable_terms(pf)) == 1 &&
+           isone(MOI.coefficient(affine_variable_terms(pf)[]))
             poi_ci = _add_vi_constraint(model, pf, set)
         else
             poi_ci = MOI.add_constraint(model, pf, set)
@@ -896,7 +898,7 @@ function MOI.add_constraint(
     _update_cache!(pf, model)
     inner_ci = MOI.add_constraint(
         model.optimizer,
-        MOI.ScalarAffineFunction{T}(pf.v, 0.0),
+        MOI.ScalarAffineFunction{T}(affine_variable_terms(pf), 0.0),
         _set_with_new_constant(set, pf.current_constant),
     )
     model.last_affine_added += 1
@@ -919,7 +921,7 @@ function _add_vi_constraint(
     _update_cache!(pf, model)
     inner_ci = MOI.add_constraint(
         model.optimizer,
-        pf.v[].variable,
+        affine_variable_terms(pf)[].variable,
         _set_with_new_constant(set, pf.current_constant),
     )
     model.last_affine_added += 1
@@ -1920,7 +1922,7 @@ function MOI.compute_conflict!(model::Optimizer)
                 ) == MOI.NOT_IN_CONFLICT
                     continue
                 end
-                for term in pf.p
+                for term in affine_parameter_terms(pf)
                     push!(model.parameters_in_conflict, term.variable)
                 end
             end
@@ -1936,14 +1938,14 @@ function MOI.compute_conflict!(model::Optimizer)
                 ) == MOI.NOT_IN_CONFLICT
                     continue
                 end
-                for term in pf.p
+                for term in affine_parameter_terms(pf)
                     push!(model.parameters_in_conflict, term.variable)
                 end
-                for term in pf.pp
+                for term in quadratic_parameter_parameter_terms(pf)
                     push!(model.parameters_in_conflict, term.variable_1)
                     push!(model.parameters_in_conflict, term.variable_2)
                 end
-                for term in pf.pv
+                for term in quadratic_parameter_variable_terms(pf)
                     push!(model.parameters_in_conflict, term.variable_1)
                 end
             end
@@ -1959,7 +1961,7 @@ function MOI.compute_conflict!(model::Optimizer)
                 ) == MOI.NOT_IN_CONFLICT
                     continue
                 end
-                for term in pf.p
+                for term in vector_affine_parameter_terms(pf)
                     push!(
                         model.parameters_in_conflict,
                         term.scalar_term.variable,

src/duals.jl

@@ -71,7 +71,7 @@ function _compute_parameters_in_ci!(
     ci::MOI.ConstraintIndex{F,S},
 ) where {F,S,T}
     cons_dual = MOI.get(model.optimizer, MOI.ConstraintDual(), ci)
-    for term in pf.p
+    for term in affine_parameter_terms(pf)
         model.dual_value_of_parameters[p_val(term.variable)] -=
             cons_dual * term.coefficient
     end
@@ -84,11 +84,11 @@ function _compute_parameters_in_ci!(
     ci::MOI.ConstraintIndex{F,S},
 ) where {F,S,T}
     cons_dual = MOI.get(model.optimizer, MOI.ConstraintDual(), ci)
-    for term in pf.p
+    for term in affine_parameter_terms(pf)
         model.dual_value_of_parameters[p_val(term.variable)] -=
             cons_dual * term.coefficient
     end
-    for term in pf.pp
+    for term in quadratic_parameter_parameter_terms(pf)
         mult = cons_dual * term.coefficient
         if term.variable_1 == term.variable_2
             mult /= 2
@@ -107,7 +107,7 @@ function _compute_parameters_in_ci!(
     ci::MOI.ConstraintIndex{F,S},
 ) where {F<:MOI.VectorAffineFunction{T},S} where {T}
     cons_dual = MOI.get(model.optimizer, MOI.ConstraintDual(), ci)
-    for term in pf.p
+    for term in vector_affine_parameter_terms(pf)
         model.dual_value_of_parameters[p_val(term.scalar_term.variable)] -=
             cons_dual[term.output_index] * term.scalar_term.coefficient
     end
@@ -116,7 +116,7 @@ end
 
 function _update_duals_from_objective!(model::Optimizer{T}, pf) where {T}
     is_min = MOI.get(model.optimizer, MOI.ObjectiveSense()) == MOI.MIN_SENSE
-    for param in pf.p
+    for param in affine_parameter_terms(pf)
         model.dual_value_of_parameters[p_val(param.variable)] +=
             ifelse(is_min, 1, -1) * param.coefficient
     end
@@ -130,12 +130,12 @@ function _update_duals_from_objective!(
     is_min = MOI.get(model.optimizer, MOI.ObjectiveSense()) == MOI.MIN_SENSE
     sign = ifelse(is_min, one(T), -one(T))
     # p terms: ∂(c·p_i)/∂p_i = c
-    for term in pf.p
+    for term in affine_parameter_terms(pf)
         model.dual_value_of_parameters[p_val(term.variable)] +=
             sign * term.coefficient
     end
     # pp terms: ∂(c·p_i·p_j)/∂p_i = c·p_j
-    for term in pf.pp
+    for term in quadratic_parameter_parameter_terms(pf)
         mult = sign * term.coefficient
         if term.variable_1 == term.variable_2
             mult /= 2
@@ -155,12 +155,12 @@ function _update_duals_from_objective!(
     is_min = MOI.get(model.optimizer, MOI.ObjectiveSense()) == MOI.MIN_SENSE
     sign = ifelse(is_min, one(T), -one(T))
     # p terms: ∂(c·p_i)/∂p_i = c
-    for term in pf.p
+    for term in cubic_affine_parameter_terms(pf)
         model.dual_value_of_parameters[p_val(term.variable)] +=
             sign * term.coefficient
     end
     # pp terms: ∂(c·p_i·p_j)/∂p_i = c·p_j (diagonal: c/2·2·p_i = c·p_i)
-    for term in pf.pp
+    for term in cubic_parameter_parameter_terms(pf)
         mult = sign * term.coefficient
         if term.variable_1 == term.variable_2
             mult /= 2
@@ -171,7 +171,7 @@ function _update_duals_from_objective!(
             mult * model.parameters[p_idx(term.variable_1)]
     end
     # ppp terms: ∂(c·p_i·p_j·p_k)/∂p_i = c·p_j·p_k
-    for term in pf.ppp
+    for term in cubic_parameter_parameter_parameter_terms(pf)
         coef = sign * term.coefficient
         p1_val = model.parameters[p_idx(term.index_1)]
         p2_val = model.parameters[p_idx(term.index_2)]
@@ -225,11 +225,11 @@ function _compute_parameters_in_ci!(
     ci::MOI.ConstraintIndex{F,S},
 ) where {F,S,T}
     cons_dual = MOI.get(model.optimizer, MOI.ConstraintDual(), ci)
-    for term in pf.p
+    for term in vector_affine_parameter_terms(pf)
         model.dual_value_of_parameters[p_val(term.scalar_term.variable)] -=
             cons_dual[term.output_index] * term.scalar_term.coefficient
     end
-    for t in pf.pp
+    for t in vector_quadratic_parameter_parameter_terms(pf)
         mult = cons_dual[t.output_index] * t.scalar_term.coefficient
         if t.scalar_term.variable_1 == t.scalar_term.variable_2
             mult /= 2

src/parametric_cubic_function.jl

@@ -129,9 +129,12 @@ function ParametricCubicFunction(parsed::_ParsedCubicExpression{T}) where {T}
 end
 
 # Accessors for cubic terms by type (direct field access)
-_cubic_pvv_terms(f::ParametricCubicFunction) = f.pvv
-_cubic_ppv_terms(f::ParametricCubicFunction) = f.ppv
-_cubic_ppp_terms(f::ParametricCubicFunction) = f.ppp
+cubic_affine_parameter_terms(f::ParametricCubicFunction) = f.p
+cubic_parameter_variable_terms(f::ParametricCubicFunction) = f.pv
+cubic_parameter_parameter_terms(f::ParametricCubicFunction) = f.pp
+cubic_parameter_variable_variable_terms(f::ParametricCubicFunction) = f.pvv
+cubic_parameter_parameter_variable_terms(f::ParametricCubicFunction) = f.ppv
+cubic_parameter_parameter_parameter_terms(f::ParametricCubicFunction) = f.ppp
 
 """
     _effective_param_value(model, pi::ParameterIndex)
@@ -156,15 +159,15 @@ function _parametric_constant(model, f::ParametricCubicFunction{T}) where {T}
     constant = f.c
 
     # From affine parameter terms (p)
-    for term in f.p
+    for term in cubic_affine_parameter_terms(f)
         constant +=
             term.coefficient *
             _effective_param_value(model, p_idx(term.variable))
     end
 
     # From quadratic parameter-parameter terms (pp)
     # MOI convention: diagonal C means C/2*p^2, off-diagonal C means C*p1*p2
-    for term in f.pp
+    for term in cubic_parameter_parameter_terms(f)
         divisor = term.variable_1 == term.variable_2 ? 2 : 1
         constant +=
             (term.coefficient / divisor) *
@@ -173,7 +176,7 @@ function _parametric_constant(model, f::ParametricCubicFunction{T}) where {T}
     end
 
     # From cubic ppp terms (all 3 indices are parameters)
-    for term in _cubic_ppp_terms(f)
+    for term in cubic_parameter_parameter_parameter_terms(f)
         p1 = term.index_1
         p2 = term.index_2
         p3 = term.index_3
@@ -202,15 +205,15 @@ function _parametric_affine_terms(
 
     # Add contributions from pv terms (parameter * variable)
     # These are always off-diagonal (p != v), so coefficient is used as-is
-    for term in f.pv
+    for term in cubic_parameter_variable_terms(f)
         var = term.variable_2
         coef = term.coefficient
         p_val = _effective_param_value(model, p_idx(term.variable_1))
         terms_dict[var] = get(terms_dict, var, zero(T)) + coef * p_val
     end
 
     # Add contributions from ppv cubic terms
-    for term in _cubic_ppv_terms(f)
+    for term in cubic_parameter_parameter_variable_terms(f)
         var = term.index_3
         p1_val = _effective_param_value(model, p_idx(term.index_1))
         p2_val = _effective_param_value(model, p_idx(term.index_2))
@@ -235,7 +238,7 @@ function _parametric_quadratic_terms(
     terms_dict = copy(f.quadratic_data)
 
     # Add contributions from pvv cubic terms
-    for term in _cubic_pvv_terms(f)
+    for term in cubic_parameter_variable_variable_terms(f)
         p = term.index_1
         first_is_greater = term.index_2.value > term.index_3.value
         v1 = ifelse(first_is_greater, term.index_3, term.index_2)
@@ -314,7 +317,7 @@ function _delta_parametric_constant(
     delta = zero(T)
 
     # From p terms
-    for term in f.p
+    for term in cubic_affine_parameter_terms(f)
         p_i = p_idx(term.variable)
         if haskey(model.updated_parameters, p_i) &&
            !isnan(model.updated_parameters[p_i])
@@ -325,7 +328,7 @@ function _delta_parametric_constant(
     end
 
     # From pp terms
-    for term in f.pp
+    for term in cubic_parameter_parameter_terms(f)
         pi1 = p_idx(term.variable_1)
         pi2 = p_idx(term.variable_2)
         updated1 =
@@ -351,7 +354,7 @@ function _delta_parametric_constant(
     end
 
     # From ppp cubic terms
-    for term in _cubic_ppp_terms(f)
+    for term in cubic_parameter_parameter_parameter_terms(f)
         pi1 = p_idx(term.index_1)
         pi2 = p_idx(term.index_2)
         pi3 = p_idx(term.index_3)
@@ -397,7 +400,7 @@ function _delta_parametric_affine_terms(
     delta_dict = Dict{MOI.VariableIndex,T}()
 
     # From pv terms (parameter * variable, always off-diagonal)
-    for term in f.pv
+    for term in cubic_parameter_variable_terms(f)
         p_i = p_idx(term.variable_1)
         if haskey(model.updated_parameters, p_i) &&
            !isnan(model.updated_parameters[p_i])
@@ -411,7 +414,7 @@ function _delta_parametric_affine_terms(
     end
 
     # From ppv cubic terms
-    for term in _cubic_ppv_terms(f)
+    for term in cubic_parameter_parameter_variable_terms(f)
         var = term.index_3
         pi1 = p_idx(term.index_1)
         pi2 = p_idx(term.index_2)
@@ -449,7 +452,7 @@ function _delta_parametric_quadratic_terms(
 ) where {T}
     delta_dict = Dict{Tuple{MOI.VariableIndex,MOI.VariableIndex},T}()
 
-    for term in _cubic_pvv_terms(f)
+    for term in cubic_parameter_variable_variable_terms(f)
         p_i = p_idx(term.index_1)
         first_is_greater = term.index_2.value > term.index_3.value
         v1 = ifelse(first_is_greater, term.index_3, term.index_2)

src/parametric_functions.jl

@@ -189,7 +189,11 @@ function _current_function(f::ParametricQuadraticFunction{T}) where {T}
     for (v, c) in f.affine_data_np
         push!(affine, MOI.ScalarAffineTerm{T}(c, v))
     end
-    return MOI.ScalarQuadraticFunction{T}(f.vv, affine, f.current_constant)
+    return MOI.ScalarQuadraticFunction{T}(
+        quadratic_variable_variable_terms(f),
+        affine,
+        f.current_constant,
+    )
 end
 
 function _parametric_constant(
@@ -720,7 +724,7 @@ function _delta_parametric_constant(
     delta_constants = zeros(T, length(f.current_constant))
 
     # Handle parameter-only affine terms
-    for term in f.p
+    for term in vector_affine_parameter_terms(f)
         p_idx_val = p_idx(term.scalar_term.variable)
         output_idx = term.output_index
 
@@ -733,7 +737,7 @@ function _delta_parametric_constant(
     end
 
     # Handle parameter-parameter quadratic terms
-    for term in f.pp
+    for term in vector_quadratic_parameter_parameter_terms(f)
         idx = term.output_index
         var1 = term.scalar_term.variable_1
         var2 = term.scalar_term.variable_2
@@ -767,7 +771,7 @@ function _delta_parametric_affine_terms(
     )
 
     # Handle parameter-variable quadratic terms (px) that become affine (x) when p is updated
-    for term in f.pv
+    for term in vector_quadratic_parameter_variable_terms(f)
         p_idx_val = p_idx(term.scalar_term.variable_1)
         var = term.scalar_term.variable_2
         output_idx = term.output_index
@@ -835,7 +839,10 @@ end
 
 function _current_function(f::ParametricVectorQuadraticFunction{T}) where {T}
     affine_terms = MOI.VectorAffineTerm{T}[]
-    sizehint!(affine_terms, length(f.current_constant) + length(f.v))
+    sizehint!(
+        affine_terms,
+        length(f.current_constant) + length(vector_affine_variable_terms(f)),
+    )
     for ((var, idx), coef) in f.current_terms_with_p
         push!(
             affine_terms,