added support of user-defined functions in MathProgNLSModel

src/jump_model.jl

@@ -20,7 +20,8 @@ function MathProgNLSModel(cmodel :: JuMP.Model,
   ev = cmodel.internalModel.eval
 
   Fmodel = JuMP.Model()
-  @objective(Fmodel, Min, 0.0)
+  @NLobjective(Fmodel, Min, 0.0)
+  Fmodel.nlpdata.user_operators = cmodel.nlpdata.user_operators
   @variable(Fmodel, x[1:MathProgBase.numvar(cmodel)])
   for Fi in F
     expr = ev.subexpressions_as_julia_expressions[Fi.index]

test/hs30.jl

@@ -0,0 +1,24 @@
+# HS problem 30 in NLS format
+#
+#   Source:
+#   W. Hock and K. Schittkowski,
+#   Test examples for nonlinear programming codes,
+#   Lecture Notes in Economics and Mathematical Systems 187,
+#   Springer Verlag Berlin Heidelberg, 1981
+#   10.1007/978-3-642-48320-2
+#
+# A. S. Siqueira, Curitiba/BR, 04/2018.
+
+export hs30
+
+"Hock-Schittkowski problem 30 in NLS format"
+function hs30()
+
+  model = Model()
+  lvar = [1.0; -10.0; -10.0]
+  @variable(model, lvar[i] <= x[i=1:3] <= 10, start=1.0)
+  @NLexpression(model, F[i=1:3], x[i] + 0.0)
+  @NLconstraint(model, x[1]^2 + x[2]^2 >= 1.0)
+
+  return MathProgNLSModel(model, F, name="hs30")
+end

test/hs43.jl

@@ -0,0 +1,31 @@
+# HS problem 43 in NLS format without constants in the objective
+#
+#   Source:
+#   W. Hock and K. Schittkowski,
+#   Test examples for nonlinear programming codes,
+#   Lecture Notes in Economics and Mathematical Systems 187,
+#   Springer Verlag Berlin Heidelberg, 1981
+#   10.1007/978-3-642-48320-2
+#
+# A. S. Siqueira, Curitiba/BR, 04/2018.
+
+export hs43
+
+"Hock-Schittkowski problem 43 in NLS format without constants in the objective"
+function hs43()
+
+  model = Model()
+  @variable(model, x[1:4], start=0.0)
+  @NLexpression(model, F1, x[1] - 5/2)
+  @NLexpression(model, F2, x[2] - 5/2)
+  @NLexpression(model, F3, sqrt(2) * (x[3] - 21 / 4))
+  @NLexpression(model, F4, x[4] + 7/2)
+  @NLconstraint(model, 8 - x[1]^2 - x[2]^2 - x[3]^2 - x[4]^2 - x[1] +
+                x[2] - x[3] + x[4] >= 0.0)
+  @NLconstraint(model, 10 - x[1]^2 - 2 * x[2]^2 - x[3]^2 - 2 * x[4]^2 +
+                x[1] + x[4] >= 0.0)
+  @NLconstraint(model, 5 - 2 * x[1]^2 - x[2]^2 - x[3]^2 - 2 * x[1] +
+                x[2] + x[4] >= 0.0)
+
+  return MathProgNLSModel(model, [F1; F2; F3; F4], name="hs43")
+end

test/mgh07.jl

@@ -0,0 +1,27 @@
+# MGH problem 7 - Helical valley function
+#
+#  Source:
+#  J. J. Moré, B. S. Garbow and K. E. Hillstrom
+#  Testing Unconstrained Optimization Software
+#  ACM Transactions on Mathematical Software, 7(1):17-41, 1981
+#
+# A. Montoison, Montreal, 05/2018.
+
+export mgh07
+
+"Helical valley function"
+function mgh07()
+
+  nls  = Model()
+  x0   = [-1.0,  0.0,  0.0]
+  @variable(nls, x[i=1:3], start = x0[i])
+
+  θ_aux(t) = (t > 0 ? 0.0 : 0.5)
+  JuMP.register(nls, :θ_aux, 1, θ_aux, autodiff=true)
+
+  @NLexpression(nls, F1, 10*(x[3] - 10*(atan(x[2]/x[1])/(2*π) + θ_aux(x[1]))))
+  @NLexpression(nls, F2, 10*(sqrt(x[1]^2 + x[2]^2) - 1.0))
+  @NLexpression(nls, F3, 1*x[3])
+
+  return MathProgNLSModel(nls, [F1, F2, F3], name="mgh07")
+end

test/mgh35.jl

@@ -0,0 +1,45 @@
+# MGH problem 35 - Chebyquad function
+#
+#   Source:
+#   J. J. Moré, B. S. Garbow and K. E. Hillstrom
+#   Testing Unconstrained Optimization Software
+#   ACM Transactions on Mathematical Software, 7(1):17-41, 1981
+#
+# A. Montoison, Montreal, 05/2018.
+
+export mgh35
+
+"Chebyquad function"
+function mgh35(m :: Int = 10, n :: Int = 10)
+  if m < n
+    warn(": number of function must be ≥ number of variables. Adjusting to m = n")
+    m = n
+  end
+
+  nls  = Model()
+  x0   = collect(1:n)/(n+1)
+  @variable(nls, x[i=1:n], start = x0[i])
+
+  function Tsim(x, n)
+    if n == 0
+      return 1
+    elseif n == 1
+      return x
+    else
+      return 2*x*Tsim(x,n-1) - Tsim(x,n-2)
+    end
+  end
+
+  Ts = Vector{Function}(n)
+  Tnames = Vector{Symbol}(n)
+  for i = 1:n
+    Ts[i] = x -> Tsim(2*x-1, i)
+    Tnames[i] = gensym()
+    JuMP.register(nls, Tnames[i], 1, Ts[i], autodiff=true)
+  end
+
+  I = [i%2 == 0 ? -1/(i^2-1) : 0 for i = 1:n]
+  @NLexpression(nls, F[i=1:n], sum($(Tnames[i])(x[j]) for j = 1:n)/n - I[i])
+
+  return MathProgNLSModel(nls, F, name="mgh35")
+end

test/runtests.jl

@@ -1,7 +1,7 @@
 using Base.Test, Ipopt, JuMP, MathProgBase, NLPModels, LinearOperators
 
 # Including problems so that they won't be multiply loaded
-for problem in [:brownden, :genrose, :hs5, :hs6, :hs10, :hs11, :hs14, :hs15]
+for problem in [:brownden, :genrose, :hs5, :hs6, :hs10, :hs11, :hs14, :hs15, :hs30, :hs43, :mgh35, :mgh07]
   include("$problem.jl")
 end
 
@@ -40,6 +40,9 @@ end
 @assert isa(hess_op(model, [0.]), LinearOperator)
 @assert isa(jac_op(model, [0.]), LinearOperator)
 
+# Tests of MathProgNLSModel with constraints and user-defined functions
+include("test_mathprognlsmodel.jl")
+
 # ADNLPModel with no functions
 model = ADNLPModel(x->dot(x,x), zeros(2), name="square")
 @assert model.meta.name == "square"

test/test_mathprognlsmodel.jl

@@ -0,0 +1,21 @@
+println()
+println("Testing MathProgNLSModel")
+
+@printf("%-15s  %4s  %4s  %4s  %10s  %10s  %10s\n",
+        "Problem", "nequ", "nvar", "ncon", "‖F(x₀)‖²", "‖JᵀF‖",
+        "‖c(x₀)‖")
+# Test that every problem can be instantiated.
+for prob in [:mgh07,:mgh35,:hs30,:hs43]
+  prob_fn = eval(prob)
+  nls = prob_fn()
+  N, n, m = nls.nls_meta.nequ, nls.meta.nvar, nls.meta.ncon
+  x = nls.meta.x0
+  Fx = residual(nls, x)
+  Jx = jac_op_residual(nls, x)
+  nFx = dot(Fx, Fx)
+  JtF = norm(Jx' * Fx)
+  ncx = m > 0 ? @sprintf("%10.4e", norm(cons(nls, x))) : "NA"
+  @printf("%-15s  %4d  %4d  %4d  %10.4e  %10.4e  %10s\n",
+          prob, N, n, m, nFx, JtF, ncx)
+end
+println()