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linesearcher_test.go
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linesearcher_test.go
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// Copyright ©2015 The gonum Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package optimize
import (
"fmt"
"math"
"reflect"
"testing"
"github.com/gonum/optimize/functions"
)
func TestMoreThuente(t *testing.T) {
d := 0.001
c := 0.001
ls := &MoreThuente{
DecreaseFactor: d,
CurvatureFactor: c,
}
testLinesearcher(t, ls, d, c, true)
}
func TestBisection(t *testing.T) {
c := 0.1
ls := &Bisection{
CurvatureFactor: c,
}
testLinesearcher(t, ls, 0, c, true)
}
func TestBacktracking(t *testing.T) {
d := 0.001
ls := &Backtracking{
DecreaseFactor: d,
}
testLinesearcher(t, ls, d, 0, false)
}
type funcGrader interface {
Func([]float64) float64
Grad([]float64, []float64)
}
type linesearcherTest struct {
name string
f func(float64) float64
g func(float64) float64
}
func newLinesearcherTest(name string, fg funcGrader) linesearcherTest {
grad := make([]float64, 1)
return linesearcherTest{
name: name,
f: func(x float64) float64 {
return fg.Func([]float64{x})
},
g: func(x float64) float64 {
fg.Grad(grad, []float64{x})
return grad[0]
},
}
}
func testLinesearcher(t *testing.T, ls Linesearcher, decrease, curvature float64, strongWolfe bool) {
for i, prob := range []linesearcherTest{
newLinesearcherTest("Concave-to-the-right function", functions.ConcaveRight{}),
newLinesearcherTest("Concave-to-the-left function", functions.ConcaveLeft{}),
newLinesearcherTest("Plassmann wiggly function (l=39, beta=0.01)", functions.Plassmann{39, 0.01}),
newLinesearcherTest("Yanai-Ozawa-Kaneko function (beta1=0.001, beta2=0.001)", functions.YanaiOzawaKaneko{0.001, 0.001}),
newLinesearcherTest("Yanai-Ozawa-Kaneko function (beta1=0.01, beta2=0.001)", functions.YanaiOzawaKaneko{0.01, 0.001}),
newLinesearcherTest("Yanai-Ozawa-Kaneko function (beta1=0.001, beta2=0.01)", functions.YanaiOzawaKaneko{0.001, 0.01}),
} {
for _, initStep := range []float64{0.001, 0.1, 1, 10, 1000} {
prefix := fmt.Sprintf("test %d (%v started from %v)", i, prob.name, initStep)
f0 := prob.f(0)
g0 := prob.g(0)
if g0 >= 0 {
panic("bad test function")
}
op := ls.Init(f0, g0, initStep)
if !op.isEvaluation() {
t.Errorf("%v: Linesearcher.Init returned non-evaluating operation %v", op)
continue
}
var (
err error
k int
f, g float64
step float64
)
loop:
for {
switch op {
case MajorIteration:
if f > f0+step*decrease*g0 {
t.Errorf("%v: %v found step %v that does not satisfy the sufficient decrease condition",
prefix, reflect.TypeOf(ls), step)
}
if strongWolfe && math.Abs(g) > curvature*(-g0) {
t.Errorf("%v: %v found step %v that does not satisfy the curvature condition",
prefix, reflect.TypeOf(ls), step)
}
break loop
case FuncEvaluation:
f = prob.f(step)
case GradEvaluation:
g = prob.g(step)
case FuncEvaluation | GradEvaluation:
f = prob.f(step)
g = prob.g(step)
default:
t.Errorf("%v: Linesearcher returned an invalid operation %v", op)
break loop
}
k++
if k == 1000 {
t.Errorf("%v: %v did not finish", prefix, reflect.TypeOf(ls))
break
}
op, step, err = ls.Iterate(f, g)
if err != nil {
t.Errorf("%v: %v failed at step %v with %v", prefix, reflect.TypeOf(ls), step, err)
break
}
}
}
}
}