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greatly improve dlanhs impl, docs and tests

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This commit is contained in:
soypat
2023-09-06 18:34:53 -03:00
committed by Vladimír Chalupecký
parent 92392f3782
commit b79b9f7740
2 changed files with 12 additions and 6 deletions
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10
lapack/gonum/dlanhs.go
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@@ -15,15 +15,19 @@ import (
// the infinity norm, or the element of largest absolute value of a
// Hessenberg matrix A.
//
// On using norm=lapack.MaxRowSum, the vector work must have length n.
// On using norm=lapack.MaxColumnSum, the vector work must have length n.
func (impl Implementation) Dlanhs(norm lapack.MatrixNorm, n int, a []float64, lda int, work []float64) float64 {
switch {
case n < 0:
panic(nLT0)
case lda < max(1, n):
panic(badLdA)
case norm == lapack.MaxRowSum && len(work) < n:
case len(a) < (n-1)*lda+n:
panic(shortA)
case norm == lapack.MaxColumnSum && len(work) < n:
panic(badLWork)
case norm != lapack.MaxRowSum && norm != lapack.MaxAbs && norm != lapack.MaxColumnSum && norm != lapack.Frobenius:
panic(badNorm)
}
if n == 0 {
return 0 // Early return.
@@ -32,8 +36,6 @@ func (impl Implementation) Dlanhs(norm lapack.MatrixNorm, n int, a []float64, ld
bi := blas64.Implementation()
var value float64
switch norm {
default:
panic(badNorm)
case lapack.MaxAbs:
for i := 0; i < n; i++ {
minj := max(0, i-1)