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dlantb.go
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dlantb.go
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// Copyright ©2020 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 testlapack
import (
"fmt"
"math"
"testing"
"golang.org/x/exp/rand"
"gonum.org/v1/gonum/blas"
"gonum.org/v1/gonum/floats"
"gonum.org/v1/gonum/lapack"
)
type Dlantber interface {
Dlantb(norm lapack.MatrixNorm, uplo blas.Uplo, diag blas.Diag, n, k int, a []float64, lda int, work []float64) float64
}
func DlantbTest(t *testing.T, impl Dlantber) {
rnd := rand.New(rand.NewSource(1))
for _, norm := range []lapack.MatrixNorm{lapack.MaxAbs, lapack.MaxRowSum, lapack.MaxColumnSum, lapack.Frobenius} {
for _, uplo := range []blas.Uplo{blas.Lower, blas.Upper} {
for _, diag := range []blas.Diag{blas.NonUnit, blas.Unit} {
name := normToString(norm) + uploToString(uplo) + diagToString(diag)
t.Run(name, func(t *testing.T) {
for _, n := range []int{0, 1, 2, 3, 4, 5, 10} {
for _, k := range []int{0, 1, 2, 3, n, n + 2} {
for _, lda := range []int{k + 1, k + 3} {
for iter := 0; iter < 10; iter++ {
dlantbTest(t, impl, rnd, norm, uplo, diag, n, k, lda)
}
}
}
}
})
}
}
}
}
func dlantbTest(t *testing.T, impl Dlantber, rnd *rand.Rand, norm lapack.MatrixNorm, uplo blas.Uplo, diag blas.Diag, n, k, lda int) {
const tol = 1e-14
name := fmt.Sprintf("n=%v,k=%v,lda=%v", n, k, lda)
// Deal with zero-sized matrices early.
if n == 0 {
got := impl.Dlantb(norm, uplo, diag, n, k, nil, lda, nil)
if got != 0 {
t.Errorf("%v: unexpected result for zero-sized matrix", name)
}
return
}
a := make([]float64, max(0, (n-1)*lda+k+1))
if rnd.Float64() < 0.5 {
// Sometimes fill A with elements between -0.5 and 0.5 so that for
// blas.Unit matrices the largest element is the 1 on the main diagonal.
for i := range a {
// Between -0.5 and 0.5.
a[i] = rnd.Float64() - 0.5
}
} else {
for i := range a {
// Between -2 and 2.
a[i] = 4*rnd.Float64() - 2
}
}
// Sometimes put a NaN into A.
if rnd.Float64() < 0.5 {
a[rnd.Intn(len(a))] = math.NaN()
}
// Make a copy of A for later comparison.
aCopy := make([]float64, len(a))
copy(aCopy, a)
var work []float64
if norm == lapack.MaxColumnSum {
work = make([]float64, n)
}
// Fill work with random garbage.
for i := range work {
work[i] = rnd.NormFloat64()
}
got := impl.Dlantb(norm, uplo, diag, n, k, a, lda, work)
if !floats.Same(a, aCopy) {
t.Fatalf("%v: unexpected modification of a", name)
}
// Generate a dense representation of A and compute the wanted result.
ldaGen := n
aGen := make([]float64, n*ldaGen)
if uplo == blas.Upper {
for i := 0; i < n; i++ {
for j := 0; j < min(n-i, k+1); j++ {
aGen[i*ldaGen+i+j] = a[i*lda+j]
}
}
} else {
for i := 0; i < n; i++ {
for j := max(0, k-i); j < k+1; j++ {
aGen[i*ldaGen+i-(k-j)] = a[i*lda+j]
}
}
}
if diag == blas.Unit {
for i := 0; i < n; i++ {
aGen[i*ldaGen+i] = 1
}
}
want := dlange(norm, n, n, aGen, ldaGen)
if math.IsNaN(want) {
if !math.IsNaN(got) {
t.Errorf("%v: unexpected result with NaN element; got %v, want %v", name, got, want)
}
return
}
if norm == lapack.MaxAbs {
if got != want {
t.Errorf("%v: unexpected result; got %v, want %v", name, got, want)
}
return
}
diff := math.Abs(got - want)
if diff > tol {
t.Errorf("%v: unexpected result; got %v, want %v, diff=%v", name, got, want, diff)
}
}