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// Copyright ©2013 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 mat
import (
"math/rand"
"testing"
"gonum.org/v1/gonum/floats"
)
func TestSVD(t *testing.T) {
// Hand coded tests
for _, test := range []struct {
a *Dense
u *Dense
v *Dense
s []float64
}{
{
a: NewDense(4, 2, []float64{2, 4, 1, 3, 0, 0, 0, 0}),
u: NewDense(4, 2, []float64{
-0.8174155604703632, -0.5760484367663209,
-0.5760484367663209, 0.8174155604703633,
0, 0,
0, 0,
}),
v: NewDense(2, 2, []float64{
-0.4045535848337571, -0.9145142956773044,
-0.9145142956773044, 0.4045535848337571,
}),
s: []float64{5.464985704219041, 0.365966190626258},
},
{
// Issue #5.
a: NewDense(3, 11, []float64{
1, 1, 0, 1, 0, 0, 0, 0, 0, 11, 1,
1, 0, 0, 0, 0, 0, 1, 0, 0, 12, 2,
1, 1, 0, 0, 0, 0, 0, 0, 1, 13, 3,
}),
u: NewDense(3, 3, []float64{
-0.5224167862273765, 0.7864430360363114, 0.3295270133658976,
-0.5739526766688285, -0.03852203026050301, -0.8179818935216693,
-0.6306021141833781, -0.6164603833618163, 0.4715056408282468,
}),
v: NewDense(11, 3, []float64{
-0.08123293141915189, 0.08528085505260324, -0.013165501690885152,
-0.05423546426886932, 0.1102707844980355, 0.622210623111631,
0, 0, 0,
-0.0245733326078166, 0.510179651760153, 0.25596360803140994,
0, 0, 0,
0, 0, 0,
-0.026997467150282436, -0.024989929445430496, -0.6353761248025164,
0, 0, 0,
-0.029662131661052707, -0.3999088672621176, 0.3662470150802212,
-0.9798839760830571, 0.11328174160898856, -0.047702613241813366,
-0.16755466189153964, -0.7395268089170608, 0.08395240366704032,
}),
s: []float64{21.259500881097434, 1.5415021616856566, 1.2873979074613628},
},
} {
var svd SVD
ok := svd.Factorize(test.a, SVDThin)
if !ok {
t.Errorf("SVD failed")
}
s, u, v := extractSVD(&svd)
if !floats.EqualApprox(s, test.s, 1e-10) {
t.Errorf("Singular value mismatch. Got %v, want %v.", s, test.s)
}
if !EqualApprox(u, test.u, 1e-10) {
t.Errorf("U mismatch.\nGot:\n%v\nWant:\n%v", Formatted(u), Formatted(test.u))
}
if !EqualApprox(v, test.v, 1e-10) {
t.Errorf("V mismatch.\nGot:\n%v\nWant:\n%v", Formatted(v), Formatted(test.v))
}
m, n := test.a.Dims()
sigma := NewDense(min(m, n), min(m, n), nil)
for i := 0; i < min(m, n); i++ {
sigma.Set(i, i, s[i])
}
var ans Dense
ans.Product(u, sigma, v.T())
if !EqualApprox(test.a, &ans, 1e-10) {
t.Errorf("A reconstruction mismatch.\nGot:\n%v\nWant:\n%v\n", Formatted(&ans), Formatted(test.a))
}
}
for _, test := range []struct {
m, n int
}{
{5, 5},
{5, 3},
{3, 5},
{150, 150},
{200, 150},
{150, 200},
} {
m := test.m
n := test.n
for trial := 0; trial < 10; trial++ {
a := NewDense(m, n, nil)
for i := range a.mat.Data {
a.mat.Data[i] = rand.NormFloat64()
}
aCopy := DenseCopyOf(a)
// Test Full decomposition.
var svd SVD
ok := svd.Factorize(a, SVDFull)
if !ok {
t.Errorf("SVD factorization failed")
}
if !Equal(a, aCopy) {
t.Errorf("A changed during call to SVD with full")
}
s, u, v := extractSVD(&svd)
sigma := NewDense(m, n, nil)
for i := 0; i < min(m, n); i++ {
sigma.Set(i, i, s[i])
}
var ansFull Dense
ansFull.Product(u, sigma, v.T())
if !EqualApprox(&ansFull, a, 1e-8) {
t.Errorf("Answer mismatch when SVDFull")
}
// Test Thin decomposition.
ok = svd.Factorize(a, SVDThin)
if !ok {
t.Errorf("SVD factorization failed")
}
if !Equal(a, aCopy) {
t.Errorf("A changed during call to SVD with Thin")
}
sThin, u, v := extractSVD(&svd)
if !floats.EqualApprox(s, sThin, 1e-8) {
t.Errorf("Singular value mismatch between Full and Thin decomposition")
}
sigma = NewDense(min(m, n), min(m, n), nil)
for i := 0; i < min(m, n); i++ {
sigma.Set(i, i, sThin[i])
}
ansFull.Reset()
ansFull.Product(u, sigma, v.T())
if !EqualApprox(&ansFull, a, 1e-8) {
t.Errorf("Answer mismatch when SVDFull")
}
// Test None decomposition.
ok = svd.Factorize(a, SVDNone)
if !ok {
t.Errorf("SVD factorization failed")
}
if !Equal(a, aCopy) {
t.Errorf("A changed during call to SVD with none")
}
sNone := make([]float64, min(m, n))
svd.Values(sNone)
if !floats.EqualApprox(s, sNone, 1e-8) {
t.Errorf("Singular value mismatch between Full and None decomposition")
}
}
}
}
func extractSVD(svd *SVD) (s []float64, u, v *Dense) {
return svd.Values(nil), svd.UTo(nil), svd.VTo(nil)
}