wip

Author: amontoison

src/moi_nlp_model.jl

@@ -162,6 +162,7 @@ function NLPModels.jac_nln_structure!(
   if nlp.quadcon.nquad > 0
     index = 0
     for i = 1:(nlp.quadcon.nquad)
+      # qcon.g is the sparsity pattern of the gradient of the quadratic constraint qcon
       qcon = nlp.quadcon.constraints[i]
       ind_quad = (index + 1):(index + qcon.nnzg)
       view(rows, ind_quad) .= i
@@ -190,6 +191,7 @@ function NLPModels.jac_structure!(
     if nlp.quadcon.nquad > 0
       index = 0
       for i = 1:(nlp.quadcon.nquad)
+        # qcon.g is the sparsity pattern of the gradient of the quadratic constraint qcon
         qcon = nlp.quadcon.constraints[i]
         ind_quad = (nlp.lincon.nnzj + index + 1):(nlp.lincon.nnzj + index + qcon.nnzg)
         view(rows, ind_quad) .= nlp.meta.nlin .+ i
@@ -288,6 +290,7 @@ function NLPModels.jprod_lin!(
   v::AbstractVector,
   Jv::AbstractVector,
 )
+  increment!(nlp, :neval_jprod_lin)
   jprod_lin!(
     nlp,
     nlp.lincon.jacobian.rows,
@@ -332,10 +335,10 @@ function NLPModels.jprod!(
   end
   if nlp.meta.nnln > 0
     if nlp.quadcon.nquad > 0
-      for i = (nlp.meta.nlin + 1):(nlp.meta.nlin + nlp.quadcon.nquad)
+      for i = 1:(nlp.quadcon.nquad)
         # Jv[i] = (Aᵢ * x + bᵢ)ᵀ * v
         qcon = nlp.quadcon.constraints[i]
-        Jv[i] = coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, v) + dot(qcon.b, v)
+        Jv[nlp.meta.nlin + i] = coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, v) + dot(qcon.b, v)
       end
     end
     if nlp.meta.nnln > nlp.quadcon.nquad
@@ -352,6 +355,7 @@ function NLPModels.jtprod_lin!(
   v::AbstractVector,
   Jtv::AbstractVector,
 )
+  increment!(nlp, :neval_jtprod_lin)
   jtprod_lin!(
     nlp,
     nlp.lincon.jacobian.rows,
@@ -386,6 +390,32 @@ function NLPModels.jtprod_nln!(
   return Jtv
 end
 
+function NLPModels.jtprod!(
+  nlp::MathOptNLPModel,
+  x::AbstractVector,
+  v::AbstractVector,
+  Jtv::AbstractVector,
+)
+  increment!(nlp, :neval_jtprod)
+  if nlp.meta.nnln > nlp.quadcon.nquad
+    ind_nnln = (nlp.quadcon.nquad + 1):(nlp.meta.nnln)
+    MOI.eval_constraint_jacobian_transpose_product(nlp.eval, Jtv, x, view(v, ind_nnln))
+  end
+  if nlp.meta.nlin > 0
+    jtprod_lin!(nlp, nlp.lincon.jacobian.rows, nlp.lincon.jacobian.cols, nlp.lincon.jacobian.vals, v, Jtv)
+  end
+  (nlp.meta.nnln == nlp.quadcon.nquad) && (Jtv .= 0.0)
+  if nlp.quadcon.nquad > 0
+    for i = 1:(nlp.quadcon.nquad)
+      # Jtv += v[i] * (Aᵢ * x + bᵢ)
+      qcon = nlp.quadcon.constraints[i]
+      coo_sym_add_mul!(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, Jtv, v[i])
+      Jtv .+= v[i] .* qcon.b
+    end
+  end
+  return Jtv
+end
+
 function NLPModels.hess_structure!(
   nlp::MathOptNLPModel,
   rows::AbstractVector{<:Integer},