decrease memory overhead in model construction for expdesign (#765)

examples/experimentdesign/JuMP.jl

@@ -30,18 +30,19 @@ function build(inst::ExperimentDesignJuMP{T}) where {T <: Float64}
     JuMP.@variable(model, x[1:k] >= 0)
     JuMP.@constraint(model, sum(x) == k)
 
-    vec_dim = Cones.svec_length(d)
-    Q = V * diagm(x) * V' # information matrix
-    Q_vec = zeros(JuMP.AffExpr, vec_dim)
-    Cones.smat_to_svec!(Q_vec, Q, sqrt(T(2)))
+    # vectorized information matrix
+    rt2 = sqrt(T(2))
+    Q_vec = [JuMP.@expression(model, (i == j ? one(T) : rt2) *
+        sum(V[i, k] * x[k] * V[j, k] for k in 1:k)) for i in 1:d for j in 1:i]
 
     # convex objective
     JuMP.@variable(model, epi)
     JuMP.@objective(model, Min, epi)
     add_homog_spectral(inst.ext, d, vcat(1.0 * epi, Q_vec), model)
 
     # save for use in tests
-    model.ext[:Q_var] = Q
+    model.ext[:V] = V
+    model.ext[:x] = x
 
     return model
 end
@@ -53,8 +54,9 @@ function test_extra(inst::ExperimentDesignJuMP{T}, model::JuMP.Model) where T
 
     # check objective
     tol = eps(T)^0.2
-    Q_opt = JuMP.value.(model.ext[:Q_var])
-    λ = eigvals(Symmetric(Q_opt, :U))
+    V = model.ext[:V]
+    x_opt = JuMP.value.(model.ext[:x])
+    λ = eigvals(Symmetric(V * Diagonal(x_opt) * V', :U))
     @test minimum(λ) >= -tol
     obj_result = get_val(pos_only(λ), inst.ext)
     @test JuMP.objective_value(model) ≈ obj_result atol=tol rtol=tol