Example #1
0
func TestRosenbrock(t *testing.T) {
	mat.Register(cops)

	n := 10
	scale := 10.0
	xInit := mat.RandVec(n).Scal(scale)

	//Define input arguments
	obj := opt.Rosenbrock{}
	p := NewParams()
	p.FunEvalMax = 100000
	p.IterMax = 100000
	sol := NewSolution(xInit)

	//Steepest descent with armijo
	stDesc := NewSteepestDescent()
	res1 := stDesc.Solve(obj, sol, p, NewDisplay(100))

	t.Log(res1.ObjX, res1.FunEvals, res1.GradEvals, res1.Status)

	//Steepest descent with Quadratic
	stDesc.LineSearch = uni.DerivWrapper{uni.NewQuadratic()}
	res2 := stDesc.Solve(obj, sol, p, NewDisplay(100))

	t.Log(res2.ObjX, res2.FunEvals, res2.GradEvals, res2.Status)

	//LBFGS with armijo
	lbfgs := NewLBFGS()
	res3 := lbfgs.Solve(obj, sol, p, NewDisplay(10))

	t.Log(res3.ObjX, res3.FunEvals, res3.GradEvals, res3.Status)

	//LBFGS with Quadratic
	lbfgs.LineSearch = uni.DerivWrapper{uni.NewQuadratic()}
	res4 := lbfgs.Solve(obj, sol, p, NewDisplay(10))

	t.Log(res4.ObjX, res4.FunEvals, res4.GradEvals, res4.Status)

	//LBFGS with Cubic
	lbfgs.LineSearch = uni.NewCubic()
	res5 := lbfgs.Solve(obj, sol, p, NewDisplay(10))

	t.Log(res5.ObjX, res5.FunEvals, res5.GradEvals, res5.Status)

	if math.Abs(res1.ObjX) > 0.01 {
		t.Fail()
	}
	if math.Abs(res2.ObjX) > 0.01 {
		t.Fail()
	}
	if math.Abs(res3.ObjX) > 0.01 {
		t.Fail()
	}
	if math.Abs(res4.ObjX) > 0.01 {
		t.Fail()
	}
	if math.Abs(res5.ObjX) > 0.01 {
		t.Fail()
	}
}
Example #2
0
func TestQuadratic(t *testing.T) {
	mat.Register(cops)
	n := 10
	xStar := mat.NewVec(n)
	xStar.AddSc(1)
	A := mat.RandN(n)
	At := A.TrView()
	AtA := mat.New(n)
	AtA.Mul(At, A)

	bTmp := mat.NewVec(n)
	bTmp.Apply(A, xStar)
	b := mat.NewVec(n)
	b.Apply(At, bTmp)
	b.Scal(-2)

	c := bTmp.Nrm2Sq()

	//Define input arguments
	obj := opt.NewQuadratic(AtA, b, c)
	p := NewParams()
	sol := NewSolution(mat.NewVec(n))

	//Steepest descent with armijo
	stDesc := NewSteepestDescent()
	res1 := stDesc.Solve(obj, sol, p, NewDisplay(100))

	t.Log(res1.ObjX, res1.FunEvals, res1.GradEvals, res1.Status)

	//Steepest descent with Quadratic
	stDesc.LineSearch = uni.DerivWrapper{uni.NewQuadratic()}
	res2 := stDesc.Solve(obj, sol, p, NewDisplay(100))

	t.Log(res2.ObjX, res2.FunEvals, res2.GradEvals, res2.Status)

	//LBFGS with armijo
	lbfgs := NewLBFGS()
	res3 := lbfgs.Solve(obj, sol, p, NewDisplay(10))

	t.Log(res3.ObjX, res3.FunEvals, res3.GradEvals, res3.Status)

	//constrained problems (constraints described as projection)
	projGrad := NewProjGrad()

	res4 := projGrad.Solve(obj, opt.RealPlus{}, sol, p, NewDisplay(100))

	t.Log(res4.ObjX, res4.FunEvals, res4.GradEvals, res4.Status)

	if math.Abs(res1.ObjX) > 0.01 {
		t.Fail()
	}
	if math.Abs(res2.ObjX) > 0.01 {
		t.Fail()
	}
	if math.Abs(res3.ObjX) > 0.01 {
		t.Fail()
	}
	if math.Abs(res4.ObjX) > 0.01 {
		t.Fail()
	}
}
Example #3
0
func NewRosenbrock() *Rosenbrock {
	return &Rosenbrock{
		LineSearch: uni.NewQuadratic(),
	}
}