func TestExampleModel(t *testing.T) {
//badly conditioned Hessian leads to zig-zagging of the steepest descent
//algorithm
condNo := 100.0
optSol := mat.Vec{1, 2}
A := mat.NewFromArray([]float64{condNo, 0, 0, 1}, true, 2, 2)
b := mat.Vec{-2 * optSol[0] * condNo, -2 * optSol[1]}
c := -0.5 * mat.Dot(b, optSol)
//define objective function
fun := opt.NewQuadratic(A, b, c)
//set inital solution estimate
sol := NewSolution(mat.NewVec(2))
//set termination parameters
p := NewParams()
p.IterMax = 5
//Use steepest descent solver to solve the model
result := NewSteepestDescent().Solve(fun, sol, p, NewDisplay(1))
fmt.Println("x =", result.X)
//should be [1,2], but because of the bad conditioning we made little
//progress in the second dimension
//Use a BFGS solver to refine the result:
result = NewLBFGS().Solve(fun, result.Solution, p, NewDisplay(1))
fmt.Println("x =", result.X)
}
func TestLinprog2(t *testing.T) {
m := 1
n := 5
tol := 1e-8
a := mat.NewVec(n).AddSc(1)
xStar := mat.NewVec(n)
xStar[0] = 1
A := mat.NewFromArray(a, true, m, n)
At := A.TrView()
b := mat.NewVec(m).AddSc(1)
c := mat.NewVec(n)
c[0] = -1
prob := NewStandard(c, A, b)
result := Solve(prob, nil)
rd := mat.NewVec(n)
rp := mat.NewVec(m)
rs := mat.NewVec(n)
rd.Sub(c, result.S)
rd.AddMul(At, result.Y, -1)
rp.Apply(A, result.X)
rp.Sub(b, rp)
rs.Mul(result.X, result.S)
rs.Neg(rs)
dev := (rd.Asum() + rp.Asum() + rs.Asum()) / float64(n)
if dev > tol {
t.Fail()
}
temp := mat.NewVec(n)
temp.Sub(result.X, xStar)
if temp.Nrm2() > tol {
t.Log(result.X)
t.Fail()
}
}
