Add more tests

Author: abelsiqueira

Project.toml

@@ -23,4 +23,4 @@ Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Printf","Test"]
+test = ["Printf", "Test"]

src/qpmodel.jl

@@ -23,7 +23,7 @@ function QuadraticModel(c :: AbstractVector,
                         Hrows :: AbstractVector{<: Integer}, Hcols :: AbstractVector{<: Integer}, Hvals :: AbstractVector;
                         Arows :: AbstractVector{<: Integer} = Int[], Acols :: AbstractVector{<: Integer} = Int[], Avals :: AbstractVector = Float64[],
                         lcon :: AbstractVector = Float64[], ucon :: AbstractVector = Float64[],
-                        lvar :: AbstractVector = fill(-Inf, length(c)), uvar :: AbstractVector = fill(Int, length(c)),
+                        lvar :: AbstractVector = fill(-Inf, length(c)), uvar :: AbstractVector = fill(Inf, length(c)),
                         c0 :: Float64=0.0, kwargs...)
   nnzh = length(Hvals)
   if !(nnzh == length(Hrows) == length(Hcols))

test/problems/bndqp.jl

@@ -0,0 +1,20 @@
+
+function bndqp_autodiff()
+
+  x0   = [0.5; 0.5]
+  f(x) = -x[1]^2 + 2x[2]^2 + 3x[1] * x[2] + x[1] + x[2]
+  uvar = [1.0; 1.0]
+  lvar = [0.0; 0.0]
+
+  return ADNLPModel(f, x0, lvar=lvar, uvar=uvar, name="bndqp_autodiff")
+end
+
+function bndqp_QP()
+  c    = [1.0; 1.0]
+  H    = [-2.0 0.0; 3.0 4.0]
+  uvar = [1.0; 1.0]
+  lvar = [0.0; 0.0]
+  x0   = [0.5; 0.5]
+
+  return QuadraticModel(c, H, lvar=lvar, uvar=uvar, x0=x0, name="bndqp_QP")
+end

test/problems/eqconqp.jl

@@ -0,0 +1,23 @@
+
+function eqconqp_autodiff()
+
+  n    = 50
+  x0   = zeros(n)
+  f(x) = sum(i * x[i]^2 for i = 1:n) / 2
+  c(x) = [sum(x) - 1.0]
+  lcon = [0.0]
+  ucon = [0.0]
+
+  return ADNLPModel(f, x0, c=c, lcon=lcon, ucon=ucon, name="eqconqp_autodiff")
+end
+
+function eqconqp_QP()
+  n    = 50
+  c    = zeros(n)
+  H    = spdiagm(0 => 1:n)
+  A    = ones(1, n)
+  lcon = [1.0]
+  ucon = [1.0]
+
+  return QuadraticModel(c, H, A=A, lcon=lcon, ucon=ucon, name="eqconqp_QP")
+end

test/problems/ineqconqp.jl

@@ -0,0 +1,27 @@
+
+function ineqconqp_autodiff()
+
+  x0   = ones(2)
+  f(x) = (x[1] - 1)^2 / 2 + (x[2] - 1)^2 / 2
+  c(x) = [x[1] - x[2]; x[2] - x[1]; x[1] + x[2]]
+  lcon = [0.0; -Inf; -1.0]
+  ucon = [Inf;  0.0;  1.0]
+
+  return ADNLPModel(f, x0, c=c, lcon=lcon, ucon=ucon, name="ineqconqp_autodiff")
+end
+
+function ineqconqp_QP()
+  c     = -ones(2)
+  Hrows = [1, 2]
+  Hcols = [1, 2]
+  Hvals = ones(2)
+  Arows = [1, 1, 2, 2, 3, 3]
+  Acols = [1, 2, 1, 2, 1, 2]
+  Avals = [1.0; -1.0; -1.0; 1.0; 1.0; 1.0]
+  c0    = 1.0
+  lcon  = [0.0; -Inf; -1.0]
+  ucon  = [Inf;  0.0;  1.0]
+  x0    = ones(2)
+
+  return QuadraticModel(c, Hrows, Hcols, Hvals, Arows=Arows, Acols=Acols, Avals=Avals, lcon=lcon, ucon=ucon, c0=c0, x0=x0, name="ineqconqp_QP")
+end

test/problems/uncqp.jl

@@ -0,0 +1,19 @@
+
+function uncqp_autodiff()
+
+  x0   = [-1.2; 1.0]
+  f(x) = 4*x[1]^2 + 5*x[2]^2 - x[1]*x[2] + 3.0*x[1] - 2*x[2] + 1.0
+
+  return ADNLPModel(f, x0, name="uncqp_autodiff")
+end
+
+function uncqp_QP()
+  c     = [3.0; -2.0]
+  Hrows = [1, 2, 2]
+  Hcols = [1, 1, 2]
+  Hvals = [8.0; -1.0; 10.0]
+  c0    = 1.0
+  x0    = [-1.2; 1.0]
+
+  return QuadraticModel(c, Hrows, Hcols, Hvals, c0=c0, x0=x0, name="uncqp_QP")
+end

test/runtests.jl

@@ -7,8 +7,11 @@ using LinearAlgebra, LinearOperators, NLPModels, QuadraticModels
 nlpmodels_path = joinpath(dirname(pathof(NLPModels)), "..", "test")
 nlpmodels_problems_path = joinpath(nlpmodels_path, "problems")
 
-# Definition of the quadratic problem in ADNLPModel
-include("simpleqp.jl")
+# Definition of quadratic problems
+qp_problems = ["uncqp", "bndqp", "eqconqp", "ineqconqp"]
+for qp in qp_problems
+  include(joinpath("problems", "$qp.jl"))
+end
 
 include(joinpath(nlpmodels_path, "consistency.jl"))
 include("test_consistency.jl")

test/simpleqp.jl

@@ -30,14 +30,13 @@ function check_quadratic_model(model, quadraticmodel)
   reset!(quadraticmodel)
 end
 
-for problem in ["simpleqp"]
-  @info "Testing consistency of problem $problem"
+for problem in qp_problems
+  @info "Checking consistency of problem $problem"
   nlp_ad = eval(Symbol(problem * "_autodiff"))()
   nlp_qm = eval(Symbol(problem * "_QP"))()
   nlps = [nlp_ad, nlp_qm]
-  # Excluding hprod until we change to coordinate format for H because
-  # hess_op uses opH, which doesn't increment the counters.
   consistent_nlps(nlps)
+  @info "  Consistency checks ✓"
 end
 
 for problem in [:brownden, :hs5, :hs6, :hs10, :hs11, :hs14, :lincon]