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This merges the three packages, matrix, mat64, and cmat128. It then renames this big package to mat. It fixes the import statements and corresponding code
173 lines
4.5 KiB
Go
173 lines
4.5 KiB
Go
// Copyright ©2013 The gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package mat
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import (
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"math/rand"
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"testing"
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"gonum.org/v1/gonum/floats"
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)
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func TestSVD(t *testing.T) {
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// Hand coded tests
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for _, test := range []struct {
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a *Dense
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u *Dense
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v *Dense
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s []float64
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}{
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{
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a: NewDense(4, 2, []float64{2, 4, 1, 3, 0, 0, 0, 0}),
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u: NewDense(4, 2, []float64{
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-0.8174155604703632, -0.5760484367663209,
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-0.5760484367663209, 0.8174155604703633,
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0, 0,
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0, 0,
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}),
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v: NewDense(2, 2, []float64{
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-0.4045535848337571, -0.9145142956773044,
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-0.9145142956773044, 0.4045535848337571,
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}),
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s: []float64{5.464985704219041, 0.365966190626258},
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},
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{
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// Issue #5.
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a: NewDense(3, 11, []float64{
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1, 1, 0, 1, 0, 0, 0, 0, 0, 11, 1,
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1, 0, 0, 0, 0, 0, 1, 0, 0, 12, 2,
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1, 1, 0, 0, 0, 0, 0, 0, 1, 13, 3,
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}),
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u: NewDense(3, 3, []float64{
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-0.5224167862273765, 0.7864430360363114, 0.3295270133658976,
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-0.5739526766688285, -0.03852203026050301, -0.8179818935216693,
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-0.6306021141833781, -0.6164603833618163, 0.4715056408282468,
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}),
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v: NewDense(11, 3, []float64{
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-0.08123293141915189, 0.08528085505260324, -0.013165501690885152,
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-0.05423546426886932, 0.1102707844980355, 0.622210623111631,
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0, 0, 0,
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-0.0245733326078166, 0.510179651760153, 0.25596360803140994,
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0, 0, 0,
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0, 0, 0,
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-0.026997467150282436, -0.024989929445430496, -0.6353761248025164,
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0, 0, 0,
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-0.029662131661052707, -0.3999088672621176, 0.3662470150802212,
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-0.9798839760830571, 0.11328174160898856, -0.047702613241813366,
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-0.16755466189153964, -0.7395268089170608, 0.08395240366704032,
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}),
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s: []float64{21.259500881097434, 1.5415021616856566, 1.2873979074613628},
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},
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} {
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var svd SVD
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ok := svd.Factorize(test.a, SVDThin)
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if !ok {
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t.Errorf("SVD failed")
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}
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s, u, v := extractSVD(&svd)
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if !floats.EqualApprox(s, test.s, 1e-10) {
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t.Errorf("Singular value mismatch. Got %v, want %v.", s, test.s)
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}
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if !EqualApprox(u, test.u, 1e-10) {
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t.Errorf("U mismatch.\nGot:\n%v\nWant:\n%v", Formatted(u), Formatted(test.u))
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}
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if !EqualApprox(v, test.v, 1e-10) {
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t.Errorf("V mismatch.\nGot:\n%v\nWant:\n%v", Formatted(v), Formatted(test.v))
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}
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m, n := test.a.Dims()
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sigma := NewDense(min(m, n), min(m, n), nil)
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for i := 0; i < min(m, n); i++ {
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sigma.Set(i, i, s[i])
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}
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var ans Dense
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ans.Product(u, sigma, v.T())
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if !EqualApprox(test.a, &ans, 1e-10) {
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t.Errorf("A reconstruction mismatch.\nGot:\n%v\nWant:\n%v\n", Formatted(&ans), Formatted(test.a))
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}
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}
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for _, test := range []struct {
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m, n int
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}{
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{5, 5},
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{5, 3},
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{3, 5},
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{150, 150},
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{200, 150},
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{150, 200},
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} {
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m := test.m
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n := test.n
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for trial := 0; trial < 10; trial++ {
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a := NewDense(m, n, nil)
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for i := range a.mat.Data {
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a.mat.Data[i] = rand.NormFloat64()
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}
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aCopy := DenseCopyOf(a)
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// Test Full decomposition.
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var svd SVD
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ok := svd.Factorize(a, SVDFull)
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if !ok {
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t.Errorf("SVD factorization failed")
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}
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if !Equal(a, aCopy) {
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t.Errorf("A changed during call to SVD with full")
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}
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s, u, v := extractSVD(&svd)
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sigma := NewDense(m, n, nil)
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for i := 0; i < min(m, n); i++ {
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sigma.Set(i, i, s[i])
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}
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var ansFull Dense
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ansFull.Product(u, sigma, v.T())
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if !EqualApprox(&ansFull, a, 1e-8) {
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t.Errorf("Answer mismatch when SVDFull")
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}
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// Test Thin decomposition.
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ok = svd.Factorize(a, SVDThin)
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if !ok {
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t.Errorf("SVD factorization failed")
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}
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if !Equal(a, aCopy) {
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t.Errorf("A changed during call to SVD with Thin")
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}
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sThin, u, v := extractSVD(&svd)
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if !floats.EqualApprox(s, sThin, 1e-8) {
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t.Errorf("Singular value mismatch between Full and Thin decomposition")
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}
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sigma = NewDense(min(m, n), min(m, n), nil)
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for i := 0; i < min(m, n); i++ {
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sigma.Set(i, i, sThin[i])
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}
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ansFull.Reset()
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ansFull.Product(u, sigma, v.T())
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if !EqualApprox(&ansFull, a, 1e-8) {
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t.Errorf("Answer mismatch when SVDFull")
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}
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// Test None decomposition.
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ok = svd.Factorize(a, SVDNone)
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if !ok {
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t.Errorf("SVD factorization failed")
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}
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if !Equal(a, aCopy) {
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t.Errorf("A changed during call to SVD with none")
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}
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sNone := make([]float64, min(m, n))
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svd.Values(sNone)
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if !floats.EqualApprox(s, sNone, 1e-8) {
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t.Errorf("Singular value mismatch between Full and None decomposition")
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}
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}
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}
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}
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func extractSVD(svd *SVD) (s []float64, u, v *Dense) {
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return svd.Values(nil), svd.UTo(nil), svd.VTo(nil)
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}
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