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// Copyright ©2018 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 (
"testing"
"golang.org/x/exp/rand"
"gonum.org/v1/gonum/floats"
"gonum.org/v1/gonum/mat"
"gonum.org/v1/gonum/optimize/functions"
)
func TestListSearch(t *testing.T) {
t.Parallel()
rnd := rand.New(rand.NewSource(1))
for cas, test := range []struct {
r, c int
shortEvals int
fun func([]float64) float64
}{
{
r: 100,
c: 10,
fun: functions.ExtendedRosenbrock{}.Func,
},
} {
// Generate a random list of items.
r, c := test.r, test.c
locs := mat.NewDense(r, c, nil)
for i := 0; i < r; i++ {
for j := 0; j < c; j++ {
locs.Set(i, j, rnd.NormFloat64())
}
}
// Evaluate all of the items in the list and find the minimum value.
fs := make([]float64, r)
for i := 0; i < r; i++ {
fs[i] = test.fun(locs.RawRowView(i))
}
minIdx := floats.MinIdx(fs)
// Check that the global minimum is found under normal conditions.
p := Problem{Func: test.fun}
method := &ListSearch{
Locs: locs,
}
settings := &Settings{
Converger: NeverTerminate{},
}
initX := make([]float64, c)
result, err := Minimize(p, initX, settings, method)
if err != nil {
t.Errorf("cas %v: error optimizing: %s", cas, err)
}
if result.Status != MethodConverge {
t.Errorf("cas %v: status should be MethodConverge", cas)
}
if !floats.Equal(result.X, locs.RawRowView(minIdx)) {
t.Errorf("cas %v: did not find minimum of whole list", cas)
}
// Check that the optimization works concurrently.
concurrent := 6
settings.Concurrent = concurrent
result, err = Minimize(p, initX, settings, method)
if err != nil {
t.Errorf("cas %v: error optimizing: %s", cas, err)
}
if result.Status != MethodConverge {
t.Errorf("cas %v: status should be MethodConverge", cas)
}
if !floats.Equal(result.X, locs.RawRowView(minIdx)) {
t.Errorf("cas %v: did not find minimum of whole list concurrent", cas)
}
// Check that the optimization works concurrently with more than the number of samples.
settings.Concurrent = test.r + concurrent
result, err = Minimize(p, initX, settings, method)
if err != nil {
t.Errorf("cas %v: error optimizing: %s", cas, err)
}
if result.Status != MethodConverge {
t.Errorf("cas %v: status should be MethodConverge", cas)
}
if !floats.Equal(result.X, locs.RawRowView(minIdx)) {
t.Errorf("cas %v: did not find minimum of whole list concurrent", cas)
}
// Check that cleanup happens properly by setting the minimum location
// to the last sample.
swapSamples(locs, fs, minIdx, test.r-1)
minIdx = test.r - 1
settings.Concurrent = concurrent
result, err = Minimize(p, initX, settings, method)
if err != nil {
t.Errorf("cas %v: error optimizing: %s", cas, err)
}
if result.Status != MethodConverge {
t.Errorf("cas %v: status should be MethodConverge", cas)
}
if !floats.Equal(result.X, locs.RawRowView(minIdx)) {
t.Errorf("cas %v: did not find minimum of whole list last sample", cas)
}
// Test that the correct optimum is found when the optimization ends early.
// Note that the above test swapped the list minimum to the last sample,
// so it's guaranteed that the minimum of the shortened list is not the
// same as the minimum of the whole list.
evals := test.r / 3
minIdxFirst := floats.MinIdx(fs[:evals])
settings.Concurrent = 0
settings.FuncEvaluations = evals
result, err = Minimize(p, initX, settings, method)
if err != nil {
t.Errorf("cas %v: error optimizing: %s", cas, err)
}
if result.Status != FunctionEvaluationLimit {
t.Errorf("cas %v: status was not FunctionEvaluationLimit", cas)
}
if !floats.Equal(result.X, locs.RawRowView(minIdxFirst)) {
t.Errorf("cas %v: did not find minimum of shortened list serial", cas)
}
// Test the same but concurrently. We can't guarantee a specific number
// of function evaluations concurrently, so make sure that the list optimum
// is not between [evals:evals+concurrent]
for floats.MinIdx(fs[:evals]) != floats.MinIdx(fs[:evals+concurrent]) {
// Swap the minimum index with a random element.
minIdxFirst := floats.MinIdx(fs[:evals+concurrent])
new := rnd.Intn(evals)
swapSamples(locs, fs, minIdxFirst, new)
}
minIdxFirst = floats.MinIdx(fs[:evals])
settings.Concurrent = concurrent
result, err = Minimize(p, initX, settings, method)
if err != nil {
t.Errorf("cas %v: error optimizing: %s", cas, err)
}
if result.Status != FunctionEvaluationLimit {
t.Errorf("cas %v: status was not FunctionEvaluationLimit", cas)
}
if !floats.Equal(result.X, locs.RawRowView(minIdxFirst)) {
t.Errorf("cas %v: did not find minimum of shortened list concurrent", cas)
}
}
}
func swapSamples(m *mat.Dense, f []float64, i, j int) {
f[i], f[j] = f[j], f[i]
row := mat.Row(nil, i, m)
m.SetRow(i, m.RawRowView(j))
m.SetRow(j, row)
}
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