Fix errors in parser_VQF

Author: amontoison

src/utils.jl

@@ -291,53 +291,53 @@ function parser_VQF(fun, set, nvar, qcons, quad_lcon, quad_ucon, index_map)
   _index(v::MOI.VariableIndex) = index_map[v].value
 
   ncon = length(fun.constants)
-  for i = 1:ncon
+  for k = 1:ncon
     b = spzeros(Float64, nvar)
     rows = Int[]
     cols = Int[]
     vals = Float64[]
 
-    quadratic_terms = fun.quadratic_terms[i]
-    affine_terms = fun.affine_terms[i]
-    constant = fun.constants[i]
-
     # Parse a VectorAffineTerm{Float64}(output_index, scalar_term)
-    for term in affine_terms
-      @assert term.output_index == i
-      b[_index(term.scalar_term.variable)] = term.scalar_term.coefficient
+    for affine_term in fun.affine_terms
+      if affine_term.output_index == k
+        b[_index(affine_term.scalar_term.variable)] = affine_term.scalar_term.coefficient
+      end
     end
 
     # Parse a VectorQuadraticTerm{Float64}(output_index, scalar_term)
-    for term in quadratic_terms
-      @assert term.output_index == i
-      i = _index(term.scalar_term.variable_1)
-      j = _index(term.scalar_term.variable_2)
-      if i ≥ j
-        push!(rows, i)
-        push!(cols, j)
-      else
-        push!(rows, j)
-        push!(cols, i)
+    for quadratic_term in fun.quadratic_terms
+      if quadratic_term.output_index == k
+        i = _index(quadratic_term.scalar_term.variable_1)
+        j = _index(quadratic_term.scalar_term.variable_2)
+        if i ≥ j
+          push!(rows, i)
+          push!(cols, j)
+        else
+          push!(rows, j)
+          push!(cols, i)
+        end
+        push!(vals, quadratic_term.scalar_term.coefficient)
       end
-      push!(vals, term.scalar_term.coefficient)
     end
 
+    constant = fun.constants[k]
+
     if typeof(set) in (MOI.Nonnegatives, MOI.Zeros)
-      append!(lin_lcon, constant)
+      append!(quad_lcon, constant)
     else
-      append!(lin_lcon, -Inf)
+      append!(quad_lcon, -Inf)
     end
 
     if typeof(set) in (MOI.Nonpositives, MOI.Zeros)
-      append!(lin_ucon, -constant)
+      append!(quad_ucon, -constant)
     else
-      append!(lin_ucon, Inf)
+      append!(quad_ucon, Inf)
     end
 
     A = COO(rows, cols, vals)
     g = unique(vcat(rows, b.nzind))  # sparsity pattern of Ax + b
     nnzg = length(g)
-    dg = Dict{Int,Int}(g[i] => i for i = 1:nnzg)
+    dg = Dict{Int,Int}(g[p] => p for p=1:nnzg)
     nnzh = length(vals)
     qcon = QuadraticConstraint(A, b, g, dg, nnzg, nnzh)
     push!(qcons, qcon)

test/nlp_problems/quadcon.jl

@@ -0,0 +1,13 @@
+function quadcon()
+  nlp = Model()
+
+  @variable(nlp, x[1:3])
+
+  @constraint(nlp, [x[1], x[1]^2 + x[1] * x[2] + 3.0] in MOI.Nonnegatives(2))
+  @constraint(nlp, [x[2], x[2]^2 + x[2] * x[3] + 4.0] in MOI.Nonpositives(2))
+  @constraint(nlp, [x[3], x[3]^2 + x[3] * x[1] + 5.0] in MOI.Zeros(2))
+
+  @objective(nlp, Min, x[1] * x[2] * exp(x[3]))
+
+  return nlp
+end

test/nls_problems/nlsqc.jl

@@ -0,0 +1,13 @@
+function nlsqc()
+  nls = Model()
+
+  @variable(nls, x[1:3])
+
+  @constraint(nls, [x[1], x[1]^2 + x[1] * x[2] + 3.0] in MOI.Nonnegatives(2))
+  @constraint(nls, [x[2], x[2]^2 + x[2] * x[3] + 4.0] in MOI.Nonpositives(2))
+  @constraint(nls, [x[3], x[3]^2 + x[3] * x[1] + 5.0] in MOI.Zeros(2))
+
+  @NLexpression(nls, F[i = 1:3], x[i]^2 - i^2)
+
+  return MathOptNLSModel(nls, F, name = "nlsqc")
+end

test/runtests.jl

@@ -4,9 +4,11 @@ using Test, Printf
 
 nlp_problems = setdiff(NLPModelsTest.nlp_problems, ["MGH01Feas"])
 nls_problems = NLPModelsTest.nls_problems
-extra_nls_problems = ["HS30", "HS43", "MGH07", "nlsnohesspb"]
 
-for problem in lowercase.(nlp_problems ∪ ["nohesspb", "hs61", "hs100", "hs219"])
+extra_nlp_problems = ["nohesspb", "hs61", "hs100", "hs219", "quadcon"]
+extra_nls_problems = ["nlsnohesspb", "HS30", "HS43", "MGH07", "nlsqc"]
+
+for problem in lowercase.(nlp_problems ∪ extra_nlp_problems)
   include(joinpath("nlp_problems", "$problem.jl"))
 end
 

test/test_moi_nlp_model.jl

@@ -11,7 +11,7 @@ println("Testing MathOptNLPModel")
   "‖c(x₀)‖"
 )
 # Test that every problem can be instantiated.
-for prob in Symbol.(lowercase.(nlp_problems ∪ ["nohesspb", "hs61", "hs100", "hs219"]))
+for prob in Symbol.(lowercase.(nlp_problems ∪ extra_nlp_problems))
   prob_fn = eval(prob)
   nlp = MathOptNLPModel(prob_fn(), hessian = (prob != :nohesspb))
   n = nlp.meta.nvar