testlapack: move local implementations of Lapack functions to separate file

This commit is contained in:
Vladimir Chalupecky
2020-10-22 18:31:32 +02:00
committed by Vladimír Chalupecký
parent 6703b9cb87
commit cdda7148b1
2 changed files with 517 additions and 514 deletions

View File

@@ -14,7 +14,6 @@ import (
"gonum.org/v1/gonum/blas"
"gonum.org/v1/gonum/blas/blas64"
"gonum.org/v1/gonum/internal/asm/f64"
"gonum.org/v1/gonum/lapack"
)
@@ -1392,516 +1391,3 @@ func residualOrthogonal(q blas64.General, rowwise bool) float64 {
blas64.Syrk(transq, -1, q, 1, work)
return dlansy(lapack.MaxColumnSum, blas.Upper, work.N, work.Data, work.Stride)
}
// dlansy is a local implementation of Dlansy to keep code paths independent.
func dlansy(norm lapack.MatrixNorm, uplo blas.Uplo, n int, a []float64, lda int) float64 {
if n == 0 {
return 0
}
work := make([]float64, n)
switch norm {
case lapack.MaxAbs:
if uplo == blas.Upper {
var max float64
for i := 0; i < n; i++ {
for j := i; j < n; j++ {
v := math.Abs(a[i*lda+j])
if math.IsNaN(v) {
return math.NaN()
}
if v > max {
max = v
}
}
}
return max
}
var max float64
for i := 0; i < n; i++ {
for j := 0; j <= i; j++ {
v := math.Abs(a[i*lda+j])
if math.IsNaN(v) {
return math.NaN()
}
if v > max {
max = v
}
}
}
return max
case lapack.MaxRowSum, lapack.MaxColumnSum:
// A symmetric matrix has the same 1-norm and ∞-norm.
for i := 0; i < n; i++ {
work[i] = 0
}
if uplo == blas.Upper {
for i := 0; i < n; i++ {
work[i] += math.Abs(a[i*lda+i])
for j := i + 1; j < n; j++ {
v := math.Abs(a[i*lda+j])
work[i] += v
work[j] += v
}
}
} else {
for i := 0; i < n; i++ {
for j := 0; j < i; j++ {
v := math.Abs(a[i*lda+j])
work[i] += v
work[j] += v
}
work[i] += math.Abs(a[i*lda+i])
}
}
var max float64
for i := 0; i < n; i++ {
v := work[i]
if math.IsNaN(v) {
return math.NaN()
}
if v > max {
max = v
}
}
return max
case lapack.Frobenius:
panic("not implemented")
default:
panic("invalid norm")
}
}
// dlange is a local implementation of Dlange to keep code paths independent.
func dlange(norm lapack.MatrixNorm, m, n int, a []float64, lda int) float64 {
if m == 0 || n == 0 {
return 0
}
var value float64
switch norm {
case lapack.MaxAbs:
for i := 0; i < m; i++ {
for j := 0; j < n; j++ {
value = math.Max(value, math.Abs(a[i*lda+j]))
}
}
case lapack.MaxColumnSum:
work := make([]float64, n)
for i := 0; i < m; i++ {
for j := 0; j < n; j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
for i := 0; i < n; i++ {
value = math.Max(value, work[i])
}
case lapack.MaxRowSum:
for i := 0; i < m; i++ {
var sum float64
for j := 0; j < n; j++ {
sum += math.Abs(a[i*lda+j])
}
value = math.Max(value, sum)
}
case lapack.Frobenius:
for i := 0; i < m; i++ {
row := f64.L2NormUnitary(a[i*lda : i*lda+n])
value = math.Hypot(value, row)
}
default:
panic("invalid norm")
}
return value
}
// dlansb is a local implementation of Dlansb to keep code paths independent.
func dlansb(norm lapack.MatrixNorm, uplo blas.Uplo, n, kd int, ab []float64, ldab int, work []float64) float64 {
if n == 0 {
return 0
}
var value float64
switch norm {
case lapack.MaxAbs:
if uplo == blas.Upper {
for i := 0; i < n; i++ {
for j := 0; j < min(n-i, kd+1); j++ {
aij := math.Abs(ab[i*ldab+j])
if aij > value || math.IsNaN(aij) {
value = aij
}
}
}
} else {
for i := 0; i < n; i++ {
for j := max(0, kd-i); j < kd+1; j++ {
aij := math.Abs(ab[i*ldab+j])
if aij > value || math.IsNaN(aij) {
value = aij
}
}
}
}
case lapack.MaxColumnSum, lapack.MaxRowSum:
work = work[:n]
var sum float64
if uplo == blas.Upper {
for i := range work {
work[i] = 0
}
for i := 0; i < n; i++ {
sum := work[i] + math.Abs(ab[i*ldab])
for j := i + 1; j < min(i+kd+1, n); j++ {
aij := math.Abs(ab[i*ldab+j-i])
sum += aij
work[j] += aij
}
if sum > value || math.IsNaN(sum) {
value = sum
}
}
} else {
for i := 0; i < n; i++ {
sum = 0
for j := max(0, i-kd); j < i; j++ {
aij := math.Abs(ab[i*ldab+kd+j-i])
sum += aij
work[j] += aij
}
work[i] = sum + math.Abs(ab[i*ldab+kd])
}
for _, sum := range work {
if sum > value || math.IsNaN(sum) {
value = sum
}
}
}
case lapack.Frobenius:
panic("not implemented")
default:
panic("invalid norm")
}
return value
}
func dlantr(norm lapack.MatrixNorm, uplo blas.Uplo, diag blas.Diag, m, n int, a []float64, lda int, work []float64) float64 {
// Quick return if possible.
minmn := min(m, n)
if minmn == 0 {
return 0
}
switch norm {
case lapack.MaxAbs:
if diag == blas.Unit {
value := 1.0
if uplo == blas.Upper {
for i := 0; i < m; i++ {
for j := i + 1; j < n; j++ {
tmp := math.Abs(a[i*lda+j])
if math.IsNaN(tmp) {
return tmp
}
if tmp > value {
value = tmp
}
}
}
return value
}
for i := 1; i < m; i++ {
for j := 0; j < min(i, n); j++ {
tmp := math.Abs(a[i*lda+j])
if math.IsNaN(tmp) {
return tmp
}
if tmp > value {
value = tmp
}
}
}
return value
}
var value float64
if uplo == blas.Upper {
for i := 0; i < m; i++ {
for j := i; j < n; j++ {
tmp := math.Abs(a[i*lda+j])
if math.IsNaN(tmp) {
return tmp
}
if tmp > value {
value = tmp
}
}
}
return value
}
for i := 0; i < m; i++ {
for j := 0; j <= min(i, n-1); j++ {
tmp := math.Abs(a[i*lda+j])
if math.IsNaN(tmp) {
return tmp
}
if tmp > value {
value = tmp
}
}
}
return value
case lapack.MaxColumnSum:
if diag == blas.Unit {
for i := 0; i < minmn; i++ {
work[i] = 1
}
for i := minmn; i < n; i++ {
work[i] = 0
}
if uplo == blas.Upper {
for i := 0; i < m; i++ {
for j := i + 1; j < n; j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
} else {
for i := 1; i < m; i++ {
for j := 0; j < min(i, n); j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
}
} else {
for i := 0; i < n; i++ {
work[i] = 0
}
if uplo == blas.Upper {
for i := 0; i < m; i++ {
for j := i; j < n; j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
} else {
for i := 0; i < m; i++ {
for j := 0; j <= min(i, n-1); j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
}
}
var max float64
for _, v := range work[:n] {
if math.IsNaN(v) {
return math.NaN()
}
if v > max {
max = v
}
}
return max
case lapack.MaxRowSum:
var maxsum float64
if diag == blas.Unit {
if uplo == blas.Upper {
for i := 0; i < m; i++ {
var sum float64
if i < minmn {
sum = 1
}
for j := i + 1; j < n; j++ {
sum += math.Abs(a[i*lda+j])
}
if math.IsNaN(sum) {
return math.NaN()
}
if sum > maxsum {
maxsum = sum
}
}
return maxsum
} else {
for i := 0; i < m; i++ {
var sum float64
if i < minmn {
sum = 1
}
for j := 0; j < min(i, n); j++ {
sum += math.Abs(a[i*lda+j])
}
if math.IsNaN(sum) {
return math.NaN()
}
if sum > maxsum {
maxsum = sum
}
}
return maxsum
}
} else {
if uplo == blas.Upper {
for i := 0; i < m; i++ {
var sum float64
for j := i; j < n; j++ {
sum += math.Abs(a[i*lda+j])
}
if math.IsNaN(sum) {
return sum
}
if sum > maxsum {
maxsum = sum
}
}
return maxsum
} else {
for i := 0; i < m; i++ {
var sum float64
for j := 0; j <= min(i, n-1); j++ {
sum += math.Abs(a[i*lda+j])
}
if math.IsNaN(sum) {
return sum
}
if sum > maxsum {
maxsum = sum
}
}
return maxsum
}
}
case lapack.Frobenius:
panic("not implemented")
default:
panic("invalid norm")
}
}
// dlantb is a local implementation of Dlantb to keep code paths independent.
func dlantb(norm lapack.MatrixNorm, uplo blas.Uplo, diag blas.Diag, n, k int, a []float64, lda int, work []float64) float64 {
if n == 0 {
return 0
}
var value float64
switch norm {
case lapack.MaxAbs:
if uplo == blas.Upper {
var jfirst int
if diag == blas.Unit {
value = 1
jfirst = 1
}
for i := 0; i < n; i++ {
for _, aij := range a[i*lda+jfirst : i*lda+min(n-i, k+1)] {
if math.IsNaN(aij) {
return aij
}
aij = math.Abs(aij)
if aij > value {
value = aij
}
}
}
} else {
jlast := k + 1
if diag == blas.Unit {
value = 1
jlast = k
}
for i := 0; i < n; i++ {
for _, aij := range a[i*lda+max(0, k-i) : i*lda+jlast] {
if math.IsNaN(aij) {
return math.NaN()
}
aij = math.Abs(aij)
if aij > value {
value = aij
}
}
}
}
case lapack.MaxRowSum:
var sum float64
if uplo == blas.Upper {
var jfirst int
if diag == blas.Unit {
jfirst = 1
}
for i := 0; i < n; i++ {
sum = 0
if diag == blas.Unit {
sum = 1
}
for _, aij := range a[i*lda+jfirst : i*lda+min(n-i, k+1)] {
sum += math.Abs(aij)
}
if math.IsNaN(sum) {
return math.NaN()
}
if sum > value {
value = sum
}
}
} else {
jlast := k + 1
if diag == blas.Unit {
jlast = k
}
for i := 0; i < n; i++ {
sum = 0
if diag == blas.Unit {
sum = 1
}
for _, aij := range a[i*lda+max(0, k-i) : i*lda+jlast] {
sum += math.Abs(aij)
}
if math.IsNaN(sum) {
return math.NaN()
}
if sum > value {
value = sum
}
}
}
case lapack.MaxColumnSum:
work = work[:n]
if diag == blas.Unit {
for i := range work {
work[i] = 1
}
} else {
for i := range work {
work[i] = 0
}
}
if uplo == blas.Upper {
var jfirst int
if diag == blas.Unit {
jfirst = 1
}
for i := 0; i < n; i++ {
for j, aij := range a[i*lda+jfirst : i*lda+min(n-i, k+1)] {
work[i+jfirst+j] += math.Abs(aij)
}
}
} else {
jlast := k + 1
if diag == blas.Unit {
jlast = k
}
for i := 0; i < n; i++ {
off := max(0, k-i)
for j, aij := range a[i*lda+off : i*lda+jlast] {
work[i+j+off-k] += math.Abs(aij)
}
}
}
for _, wi := range work {
if math.IsNaN(wi) {
return math.NaN()
}
if wi > value {
value = wi
}
}
case lapack.Frobenius:
panic("not implemented")
default:
panic("invalid norm")
}
return value
}

View File

@@ -8,9 +8,11 @@ import (
"math"
"gonum.org/v1/gonum/blas"
"gonum.org/v1/gonum/internal/asm/f64"
"gonum.org/v1/gonum/lapack"
)
// dlagtm is a local implementation of Dlagtm to keep code paths independent.
func dlagtm(trans blas.Transpose, m, n int, alpha float64, dl, d, du []float64, b []float64, ldb int, beta float64, c []float64, ldc int) {
if m == 0 || n == 0 {
return
@@ -82,6 +84,7 @@ func dlagtm(trans blas.Transpose, m, n int, alpha float64, dl, d, du []float64,
}
}
// dlangt is a local implementation of Dlangt to keep code paths independent.
func dlangt(norm lapack.MatrixNorm, n int, dl, d, du []float64) float64 {
if n == 0 {
return 0
@@ -160,3 +163,517 @@ func dlangt(norm lapack.MatrixNorm, n int, dl, d, du []float64) float64 {
}
return anorm
}
// dlansy is a local implementation of Dlansy to keep code paths independent.
func dlansy(norm lapack.MatrixNorm, uplo blas.Uplo, n int, a []float64, lda int) float64 {
if n == 0 {
return 0
}
work := make([]float64, n)
switch norm {
case lapack.MaxAbs:
if uplo == blas.Upper {
var max float64
for i := 0; i < n; i++ {
for j := i; j < n; j++ {
v := math.Abs(a[i*lda+j])
if math.IsNaN(v) {
return math.NaN()
}
if v > max {
max = v
}
}
}
return max
}
var max float64
for i := 0; i < n; i++ {
for j := 0; j <= i; j++ {
v := math.Abs(a[i*lda+j])
if math.IsNaN(v) {
return math.NaN()
}
if v > max {
max = v
}
}
}
return max
case lapack.MaxRowSum, lapack.MaxColumnSum:
// A symmetric matrix has the same 1-norm and ∞-norm.
for i := 0; i < n; i++ {
work[i] = 0
}
if uplo == blas.Upper {
for i := 0; i < n; i++ {
work[i] += math.Abs(a[i*lda+i])
for j := i + 1; j < n; j++ {
v := math.Abs(a[i*lda+j])
work[i] += v
work[j] += v
}
}
} else {
for i := 0; i < n; i++ {
for j := 0; j < i; j++ {
v := math.Abs(a[i*lda+j])
work[i] += v
work[j] += v
}
work[i] += math.Abs(a[i*lda+i])
}
}
var max float64
for i := 0; i < n; i++ {
v := work[i]
if math.IsNaN(v) {
return math.NaN()
}
if v > max {
max = v
}
}
return max
case lapack.Frobenius:
panic("not implemented")
default:
panic("invalid norm")
}
}
// dlange is a local implementation of Dlange to keep code paths independent.
func dlange(norm lapack.MatrixNorm, m, n int, a []float64, lda int) float64 {
if m == 0 || n == 0 {
return 0
}
var value float64
switch norm {
case lapack.MaxAbs:
for i := 0; i < m; i++ {
for j := 0; j < n; j++ {
value = math.Max(value, math.Abs(a[i*lda+j]))
}
}
case lapack.MaxColumnSum:
work := make([]float64, n)
for i := 0; i < m; i++ {
for j := 0; j < n; j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
for i := 0; i < n; i++ {
value = math.Max(value, work[i])
}
case lapack.MaxRowSum:
for i := 0; i < m; i++ {
var sum float64
for j := 0; j < n; j++ {
sum += math.Abs(a[i*lda+j])
}
value = math.Max(value, sum)
}
case lapack.Frobenius:
for i := 0; i < m; i++ {
row := f64.L2NormUnitary(a[i*lda : i*lda+n])
value = math.Hypot(value, row)
}
default:
panic("invalid norm")
}
return value
}
// dlansb is a local implementation of Dlansb to keep code paths independent.
func dlansb(norm lapack.MatrixNorm, uplo blas.Uplo, n, kd int, ab []float64, ldab int, work []float64) float64 {
if n == 0 {
return 0
}
var value float64
switch norm {
case lapack.MaxAbs:
if uplo == blas.Upper {
for i := 0; i < n; i++ {
for j := 0; j < min(n-i, kd+1); j++ {
aij := math.Abs(ab[i*ldab+j])
if aij > value || math.IsNaN(aij) {
value = aij
}
}
}
} else {
for i := 0; i < n; i++ {
for j := max(0, kd-i); j < kd+1; j++ {
aij := math.Abs(ab[i*ldab+j])
if aij > value || math.IsNaN(aij) {
value = aij
}
}
}
}
case lapack.MaxColumnSum, lapack.MaxRowSum:
work = work[:n]
var sum float64
if uplo == blas.Upper {
for i := range work {
work[i] = 0
}
for i := 0; i < n; i++ {
sum := work[i] + math.Abs(ab[i*ldab])
for j := i + 1; j < min(i+kd+1, n); j++ {
aij := math.Abs(ab[i*ldab+j-i])
sum += aij
work[j] += aij
}
if sum > value || math.IsNaN(sum) {
value = sum
}
}
} else {
for i := 0; i < n; i++ {
sum = 0
for j := max(0, i-kd); j < i; j++ {
aij := math.Abs(ab[i*ldab+kd+j-i])
sum += aij
work[j] += aij
}
work[i] = sum + math.Abs(ab[i*ldab+kd])
}
for _, sum := range work {
if sum > value || math.IsNaN(sum) {
value = sum
}
}
}
case lapack.Frobenius:
panic("not implemented")
default:
panic("invalid norm")
}
return value
}
// dlantr is a local implementation of Dlantr to keep code paths independent.
func dlantr(norm lapack.MatrixNorm, uplo blas.Uplo, diag blas.Diag, m, n int, a []float64, lda int, work []float64) float64 {
// Quick return if possible.
minmn := min(m, n)
if minmn == 0 {
return 0
}
switch norm {
case lapack.MaxAbs:
if diag == blas.Unit {
value := 1.0
if uplo == blas.Upper {
for i := 0; i < m; i++ {
for j := i + 1; j < n; j++ {
tmp := math.Abs(a[i*lda+j])
if math.IsNaN(tmp) {
return tmp
}
if tmp > value {
value = tmp
}
}
}
return value
}
for i := 1; i < m; i++ {
for j := 0; j < min(i, n); j++ {
tmp := math.Abs(a[i*lda+j])
if math.IsNaN(tmp) {
return tmp
}
if tmp > value {
value = tmp
}
}
}
return value
}
var value float64
if uplo == blas.Upper {
for i := 0; i < m; i++ {
for j := i; j < n; j++ {
tmp := math.Abs(a[i*lda+j])
if math.IsNaN(tmp) {
return tmp
}
if tmp > value {
value = tmp
}
}
}
return value
}
for i := 0; i < m; i++ {
for j := 0; j <= min(i, n-1); j++ {
tmp := math.Abs(a[i*lda+j])
if math.IsNaN(tmp) {
return tmp
}
if tmp > value {
value = tmp
}
}
}
return value
case lapack.MaxColumnSum:
if diag == blas.Unit {
for i := 0; i < minmn; i++ {
work[i] = 1
}
for i := minmn; i < n; i++ {
work[i] = 0
}
if uplo == blas.Upper {
for i := 0; i < m; i++ {
for j := i + 1; j < n; j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
} else {
for i := 1; i < m; i++ {
for j := 0; j < min(i, n); j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
}
} else {
for i := 0; i < n; i++ {
work[i] = 0
}
if uplo == blas.Upper {
for i := 0; i < m; i++ {
for j := i; j < n; j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
} else {
for i := 0; i < m; i++ {
for j := 0; j <= min(i, n-1); j++ {
work[j] += math.Abs(a[i*lda+j])
}
}
}
}
var max float64
for _, v := range work[:n] {
if math.IsNaN(v) {
return math.NaN()
}
if v > max {
max = v
}
}
return max
case lapack.MaxRowSum:
var maxsum float64
if diag == blas.Unit {
if uplo == blas.Upper {
for i := 0; i < m; i++ {
var sum float64
if i < minmn {
sum = 1
}
for j := i + 1; j < n; j++ {
sum += math.Abs(a[i*lda+j])
}
if math.IsNaN(sum) {
return math.NaN()
}
if sum > maxsum {
maxsum = sum
}
}
return maxsum
} else {
for i := 0; i < m; i++ {
var sum float64
if i < minmn {
sum = 1
}
for j := 0; j < min(i, n); j++ {
sum += math.Abs(a[i*lda+j])
}
if math.IsNaN(sum) {
return math.NaN()
}
if sum > maxsum {
maxsum = sum
}
}
return maxsum
}
} else {
if uplo == blas.Upper {
for i := 0; i < m; i++ {
var sum float64
for j := i; j < n; j++ {
sum += math.Abs(a[i*lda+j])
}
if math.IsNaN(sum) {
return sum
}
if sum > maxsum {
maxsum = sum
}
}
return maxsum
} else {
for i := 0; i < m; i++ {
var sum float64
for j := 0; j <= min(i, n-1); j++ {
sum += math.Abs(a[i*lda+j])
}
if math.IsNaN(sum) {
return sum
}
if sum > maxsum {
maxsum = sum
}
}
return maxsum
}
}
case lapack.Frobenius:
panic("not implemented")
default:
panic("invalid norm")
}
}
// dlantb is a local implementation of Dlantb to keep code paths independent.
func dlantb(norm lapack.MatrixNorm, uplo blas.Uplo, diag blas.Diag, n, k int, a []float64, lda int, work []float64) float64 {
if n == 0 {
return 0
}
var value float64
switch norm {
case lapack.MaxAbs:
if uplo == blas.Upper {
var jfirst int
if diag == blas.Unit {
value = 1
jfirst = 1
}
for i := 0; i < n; i++ {
for _, aij := range a[i*lda+jfirst : i*lda+min(n-i, k+1)] {
if math.IsNaN(aij) {
return aij
}
aij = math.Abs(aij)
if aij > value {
value = aij
}
}
}
} else {
jlast := k + 1
if diag == blas.Unit {
value = 1
jlast = k
}
for i := 0; i < n; i++ {
for _, aij := range a[i*lda+max(0, k-i) : i*lda+jlast] {
if math.IsNaN(aij) {
return math.NaN()
}
aij = math.Abs(aij)
if aij > value {
value = aij
}
}
}
}
case lapack.MaxRowSum:
var sum float64
if uplo == blas.Upper {
var jfirst int
if diag == blas.Unit {
jfirst = 1
}
for i := 0; i < n; i++ {
sum = 0
if diag == blas.Unit {
sum = 1
}
for _, aij := range a[i*lda+jfirst : i*lda+min(n-i, k+1)] {
sum += math.Abs(aij)
}
if math.IsNaN(sum) {
return math.NaN()
}
if sum > value {
value = sum
}
}
} else {
jlast := k + 1
if diag == blas.Unit {
jlast = k
}
for i := 0; i < n; i++ {
sum = 0
if diag == blas.Unit {
sum = 1
}
for _, aij := range a[i*lda+max(0, k-i) : i*lda+jlast] {
sum += math.Abs(aij)
}
if math.IsNaN(sum) {
return math.NaN()
}
if sum > value {
value = sum
}
}
}
case lapack.MaxColumnSum:
work = work[:n]
if diag == blas.Unit {
for i := range work {
work[i] = 1
}
} else {
for i := range work {
work[i] = 0
}
}
if uplo == blas.Upper {
var jfirst int
if diag == blas.Unit {
jfirst = 1
}
for i := 0; i < n; i++ {
for j, aij := range a[i*lda+jfirst : i*lda+min(n-i, k+1)] {
work[i+jfirst+j] += math.Abs(aij)
}
}
} else {
jlast := k + 1
if diag == blas.Unit {
jlast = k
}
for i := 0; i < n; i++ {
off := max(0, k-i)
for j, aij := range a[i*lda+off : i*lda+jlast] {
work[i+j+off-k] += math.Abs(aij)
}
}
}
for _, wi := range work {
if math.IsNaN(wi) {
return math.NaN()
}
if wi > value {
value = wi
}
}
case lapack.Frobenius:
panic("not implemented")
default:
panic("invalid norm")
}
return value
}