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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 testlapack
import (
"math"
"testing"
"golang.org/x/exp/rand"
"gonum.org/v1/gonum/blas"
"gonum.org/v1/gonum/lapack"
)
type Dlansyer interface {
Dlanger
Dlansy(norm lapack.MatrixNorm, uplo blas.Uplo, n int, a []float64, lda int, work []float64) float64
}
func DlansyTest(t *testing.T, impl Dlansyer) {
rnd := rand.New(rand.NewSource(1))
for _, norm := range []lapack.MatrixNorm{lapack.MaxAbs, lapack.MaxColumnSum, lapack.MaxRowSum, lapack.Frobenius} {
for _, uplo := range []blas.Uplo{blas.Lower, blas.Upper} {
for _, test := range []struct {
n, lda int
}{
{1, 0},
{3, 0},
{1, 10},
{3, 10},
} {
for trial := 0; trial < 100; trial++ {
n := test.n
lda := test.lda
if lda == 0 {
lda = n
}
// Allocate n×n matrix A and fill it.
// Only the uplo triangle of A will be used below
// to represent a symmetric matrix.
a := make([]float64, lda*n)
if trial == 0 {
// In the first trial fill the matrix
// with predictable integers.
for i := range a {
a[i] = float64(i)
}
} else {
// Otherwise fill it with random numbers.
for i := range a {
a[i] = rnd.NormFloat64()
}
}
// Create a dense representation of the symmetric matrix
// stored in the uplo triangle of A.
aDense := make([]float64, n*n)
if uplo == blas.Upper {
for i := 0; i < n; i++ {
for j := i; j < n; j++ {
v := a[i*lda+j]
aDense[i*n+j] = v
aDense[j*n+i] = v
}
}
} else {
for i := 0; i < n; i++ {
for j := 0; j <= i; j++ {
v := a[i*lda+j]
aDense[i*n+j] = v
aDense[j*n+i] = v
}
}
}
work := make([]float64, n)
// Compute the norm of the symmetric matrix A.
got := impl.Dlansy(norm, uplo, n, a, lda, work)
// Compute the reference norm value using Dlange
// and the dense representation of A.
want := impl.Dlange(norm, n, n, aDense, n, work)
if math.Abs(want-got) > 1e-14 {
t.Errorf("Norm mismatch. norm = %c, upper = %v, n = %v, lda = %v, want %v, got %v.",
norm, uplo == blas.Upper, n, lda, got, want)
}
}
}
}
}
}
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