Update API

Author: amontoison

src/moi_nlp_model.jl

@@ -113,16 +113,37 @@ end
 
 function NLPModels.cons_nln!(nlp::MathOptNLPModel, x::AbstractVector, c::AbstractVector)
   increment!(nlp, :neval_cons_nln)
-  for i = 1:(nlp.quadcon.nquad)
-    qcon = nlp.quadcon.constraints[i]
-    c[i] = 0.5 * coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, x) + dot(qcon.b, x)
+  if nlp.quadcon.nquad > 0
+    for i = 1:(nlp.quadcon.nquad)
+      qcon = nlp.quadcon.constraints[i]
+      c[i] = 0.5 * coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, x) + dot(qcon.b, x)
+    end
   end
   if nlp.meta.nnln > nlp.quadcon.nquad
     MOI.eval_constraint(nlp.eval, view(c, (nlp.quadcon.nquad + 1):(nlp.meta.nnln)), x)
   end
   return c
 end
 
+function NLPModels.cons!(nlp::MathOptNLPModel, x::AbstractVector, c::AbstractVector)
+  increment!(nlp, :neval_cons)
+  if nlp.meta.nlin > 0
+    coo_prod!(nlp.lincon.jacobian.rows, nlp.lincon.jacobian.cols, nlp.lincon.jacobian.vals, x, c)
+  end
+  if nlp.meta.nnln > 0
+    if nlp.quadcon.nquad > 0
+      for i = 1:(nlp.quadcon.nquad)
+        qcon = nlp.quadcon.constraints[i]
+        c[nlp.meta.nlin + i] = 0.5 * coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, x) + dot(qcon.b, x)
+      end
+    end
+    if nlp.meta.nnln > nlp.quadcon.nquad
+      MOI.eval_constraint(nlp.eval, view(c, (nlp.meta.nlin + nlp.quadcon.nquad + 1):(nlp.meta.nlin + nlp.meta.nnln)), x)
+    end
+  end
+  return c
+end
+
 function NLPModels.jac_lin_structure!(
   nlp::MathOptNLPModel,
   rows::AbstractVector{<:Integer},
@@ -142,8 +163,9 @@ function NLPModels.jac_nln_structure!(
     index = 0
     for i = 1:(nlp.quadcon.nquad)
       qcon = nlp.quadcon.constraints[i]
-      view(rows, (index + 1):(index + qcon.nnzg)) .= i
-      view(cols, (index + 1):(index + qcon.nnzg)) .= qcon.g
+      ind_quad = (index + 1):(index + qcon.nnzg)
+      view(rows, ind_quad) .= i
+      view(cols, ind_quad) .= qcon.g
       index += qcon.nnzg
     end
   end
@@ -155,6 +177,35 @@ function NLPModels.jac_nln_structure!(
   return rows, cols
 end
 
+function NLPModels.jac_structure!(
+  nlp::MathOptNLPModel,
+  rows::AbstractVector{<:Integer},
+  cols::AbstractVector{<:Integer},
+)
+  if nlp.meta.nlin > 0
+    view(rows, 1:(nlp.lincon.nnzj)) .= nlp.lincon.jacobian.rows
+    view(cols, 1:(nlp.lincon.nnzj)) .= nlp.lincon.jacobian.cols
+  end
+  if nlp.meta.nnln > 0
+    if nlp.quadcon.nquad > 0
+      index = 0
+      for i = 1:(nlp.quadcon.nquad)
+        qcon = nlp.quadcon.constraints[i]
+        ind_quad = (nlp.lincon.nnzj + index + 1):(nlp.lincon.nnzj + index + qcon.nnzg)
+        view(rows, ind_quad) .= i
+        view(cols, ind_quad) .= qcon.g
+        index += qcon.nnzg
+      end
+    end
+    if nlp.meta.nnln > nlp.quadcon.nquad
+      ind_nnln = (nlp.lincon.nnzj + nlp.quadcon.nnzj + 1):(nlp.lincon.nnzj + nlp.quadcon.nnzj + nlp.nlcon.nnzj)
+      view(rows, ind_nnln) .= nlp.quadcon.nquad .+ nlp.nlcon.jac_rows
+      view(cols, ind_nnln) .= nlp.nlcon.jac_cols
+    end
+  end
+  return rows, cols
+end
+
 function NLPModels.jac_lin_coord!(nlp::MathOptNLPModel, x::AbstractVector, vals::AbstractVector)
   increment!(nlp, :neval_jac_lin)
   view(vals, 1:(nlp.lincon.nnzj)) .= nlp.lincon.jacobian.vals
@@ -193,6 +244,44 @@ function NLPModels.jac_nln_coord!(nlp::MathOptNLPModel, x::AbstractVector, vals:
   return vals
 end
 
+function NLPModels.jac_coord!(nlp::MathOptNLPModel, x::AbstractVector, vals::AbstractVector)
+  increment!(nlp, :neval_jac)
+  if nlp.meta.nlin > 0
+    view(vals, 1:(nlp.lincon.nnzj)) .= nlp.lincon.jacobian.vals
+  end
+  if nlp.meta.nnln > 0
+    if nlp.quadcon.nquad > 0
+      ind_quad = (nlp.lincon.nnzj + 1):(nlp.lincon.nnzj + nlp.quadcon.nnzj)
+      view(vals, ind_quad) .= 0.0
+      index = nlp.lincon.nnzj
+      for i = 1:(nlp.quadcon.nquad)
+        qcon = nlp.quadcon.constraints[i]
+        for (j, ind) in enumerate(qcon.b.nzind)
+          k = qcon.dg[ind]
+          vals[index + k] += qcon.b.nzval[j]
+        end
+        for j = 1:(qcon.nnzh)
+          row = qcon.A.rows[j]
+          col = qcon.A.cols[j]
+          val = qcon.A.vals[j]
+          k1 = qcon.dg[row]
+          vals[index + k1] += val * x[col]
+          if row != col
+            k2 = qcon.dg[col]
+            vals[index + k2] += val * x[row]
+          end
+        end
+        index += qcon.nnzg
+      end
+    end
+    if nlp.meta.nnln > nlp.quadcon.nquad
+      ind_nnln = (nlp.lincon.nnzj + nlp.quadcon.nnzj + 1):(nlp.lincon.nnzj + nlp.quadcon.nnzj + nlp.nlcon.nnzj)
+      MOI.eval_constraint_jacobian(nlp.eval, view(vals, ind_nnln), x)
+    end
+  end
+  return vals
+end
+
 function NLPModels.jprod_lin!(
   nlp::MathOptNLPModel,
   x::AbstractVector,