mirror of
https://github.com/gonum/gonum.git
synced 2025-11-02 03:23:03 +08:00
lapack/{gonum,testlapack}: add Dlangb and its test
This commit is contained in:
committed by
Vladimír Chalupecký
parent
911f47973b
commit
142fecace0
98
lapack/gonum/dlangb.go
Normal file
98
lapack/gonum/dlangb.go
Normal file
@@ -0,0 +1,98 @@
|
|||||||
|
// Copyright ©2021 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 gonum
|
||||||
|
|
||||||
|
import (
|
||||||
|
"math"
|
||||||
|
|
||||||
|
"gonum.org/v1/gonum/internal/asm/f64"
|
||||||
|
"gonum.org/v1/gonum/lapack"
|
||||||
|
)
|
||||||
|
|
||||||
|
// Dlangb returns the given norm of an n×n band matrix with kl sub-diagonals and
|
||||||
|
// ku super-diagonals.
|
||||||
|
//
|
||||||
|
// When norm is lapack.MaxColumnSum, the length of work must be at least n.
|
||||||
|
func (impl Implementation) Dlangb(norm lapack.MatrixNorm, n, kl, ku int, ab []float64, ldab int, work []float64) float64 {
|
||||||
|
ncol := kl + 1 + ku
|
||||||
|
switch {
|
||||||
|
case norm != lapack.MaxAbs && norm != lapack.MaxRowSum && norm != lapack.MaxColumnSum && norm != lapack.Frobenius:
|
||||||
|
panic(badNorm)
|
||||||
|
case n < 0:
|
||||||
|
panic(nLT0)
|
||||||
|
case kl < 0:
|
||||||
|
panic(klLT0)
|
||||||
|
case ku < 0:
|
||||||
|
panic(kuLT0)
|
||||||
|
case ldab < ncol:
|
||||||
|
panic(badLdA)
|
||||||
|
}
|
||||||
|
|
||||||
|
// Quick return if possible.
|
||||||
|
if n == 0 {
|
||||||
|
return 0
|
||||||
|
}
|
||||||
|
|
||||||
|
switch {
|
||||||
|
case len(ab) < (n-1)*ldab+ncol:
|
||||||
|
panic(shortAB)
|
||||||
|
case len(work) < n && norm == lapack.MaxColumnSum:
|
||||||
|
panic(shortWork)
|
||||||
|
}
|
||||||
|
|
||||||
|
var value float64
|
||||||
|
switch norm {
|
||||||
|
case lapack.MaxAbs:
|
||||||
|
for i := 0; i < n; i++ {
|
||||||
|
l := max(0, kl-i)
|
||||||
|
u := min(n+kl-i, ncol)
|
||||||
|
for _, aij := range ab[i*ldab+l : i*ldab+u] {
|
||||||
|
aij = math.Abs(aij)
|
||||||
|
if aij > value || math.IsNaN(aij) {
|
||||||
|
value = aij
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
case lapack.MaxRowSum:
|
||||||
|
for i := 0; i < n; i++ {
|
||||||
|
l := max(0, kl-i)
|
||||||
|
u := min(n+kl-i, ncol)
|
||||||
|
sum := f64.L1Norm(ab[i*ldab+l : i*ldab+u])
|
||||||
|
if sum > value || math.IsNaN(sum) {
|
||||||
|
value = sum
|
||||||
|
}
|
||||||
|
}
|
||||||
|
case lapack.MaxColumnSum:
|
||||||
|
work = work[:n]
|
||||||
|
for j := range work {
|
||||||
|
work[j] = 0
|
||||||
|
}
|
||||||
|
for i := 0; i < n; i++ {
|
||||||
|
l := max(0, kl-i)
|
||||||
|
u := min(n+kl-i, ncol)
|
||||||
|
for jb, aij := range ab[i*ldab+l : i*ldab+u] {
|
||||||
|
j := l + jb - kl + i
|
||||||
|
work[j] += math.Abs(aij)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
for _, sumj := range work {
|
||||||
|
if sumj > value || math.IsNaN(sumj) {
|
||||||
|
value = sumj
|
||||||
|
}
|
||||||
|
}
|
||||||
|
case lapack.Frobenius:
|
||||||
|
scale := 0.0
|
||||||
|
ssq := 1.0
|
||||||
|
for i := 0; i < n; i++ {
|
||||||
|
l := max(0, kl-i)
|
||||||
|
u := min(n+kl-i, ncol)
|
||||||
|
ilen := u - l
|
||||||
|
rowscale, rowssq := impl.Dlassq(ilen, ab[i*ldab+l:], 1, 0, 1)
|
||||||
|
scale, ssq = impl.Dcombssq(scale, ssq, rowscale, rowssq)
|
||||||
|
}
|
||||||
|
value = scale * math.Sqrt(ssq)
|
||||||
|
}
|
||||||
|
return value
|
||||||
|
}
|
||||||
@@ -65,6 +65,8 @@ const (
|
|||||||
kLT0 = "lapack: k < 0"
|
kLT0 = "lapack: k < 0"
|
||||||
kLT1 = "lapack: k < 1"
|
kLT1 = "lapack: k < 1"
|
||||||
kdLT0 = "lapack: kd < 0"
|
kdLT0 = "lapack: kd < 0"
|
||||||
|
klLT0 = "lapack: kl < 0"
|
||||||
|
kuLT0 = "lapack: ku < 0"
|
||||||
mGTN = "lapack: m > n"
|
mGTN = "lapack: m > n"
|
||||||
mLT0 = "lapack: m < 0"
|
mLT0 = "lapack: m < 0"
|
||||||
mmLT0 = "lapack: mm < 0"
|
mmLT0 = "lapack: mm < 0"
|
||||||
|
|||||||
@@ -208,6 +208,11 @@ func TestDlaln2(t *testing.T) {
|
|||||||
testlapack.Dlaln2Test(t, impl)
|
testlapack.Dlaln2Test(t, impl)
|
||||||
}
|
}
|
||||||
|
|
||||||
|
func TestDlangb(t *testing.T) {
|
||||||
|
t.Parallel()
|
||||||
|
testlapack.DlangbTest(t, impl)
|
||||||
|
}
|
||||||
|
|
||||||
func TestDlange(t *testing.T) {
|
func TestDlange(t *testing.T) {
|
||||||
t.Parallel()
|
t.Parallel()
|
||||||
testlapack.DlangeTest(t, impl)
|
testlapack.DlangeTest(t, impl)
|
||||||
|
|||||||
@@ -466,6 +466,20 @@ func Lange(norm lapack.MatrixNorm, a blas64.General, work []float64) float64 {
|
|||||||
return lapack64.Dlange(norm, a.Rows, a.Cols, a.Data, max(1, a.Stride), work)
|
return lapack64.Dlange(norm, a.Rows, a.Cols, a.Data, max(1, a.Stride), work)
|
||||||
}
|
}
|
||||||
|
|
||||||
|
// Langb returns the given norm of a square, n×n band matrix with kl sub-diagonals and
|
||||||
|
// ku super-diagonals.
|
||||||
|
//
|
||||||
|
// When norm is lapack.MaxColumnSum, the length of work must be at least n.
|
||||||
|
//
|
||||||
|
// Dlangb is not part of the lapack.Float64 interface and so calls to Langb are always
|
||||||
|
// executed by the Gonum implementation.
|
||||||
|
func Langb(norm lapack.MatrixNorm, a blas64.Band, work []float64) float64 {
|
||||||
|
if a.Rows != a.Cols {
|
||||||
|
panic("lapack64: matrix is not square")
|
||||||
|
}
|
||||||
|
return gonum.Implementation{}.Dlangb(norm, a.Rows, a.KL, a.KU, a.Data, a.Stride, work)
|
||||||
|
}
|
||||||
|
|
||||||
// Langt computes the specified norm of an n×n tridiagonal matrix.
|
// Langt computes the specified norm of an n×n tridiagonal matrix.
|
||||||
//
|
//
|
||||||
// Dlangt is not part of the lapack.Float64 interface and so calls to Langt are
|
// Dlangt is not part of the lapack.Float64 interface and so calls to Langt are
|
||||||
|
|||||||
109
lapack/testlapack/dlangb.go
Normal file
109
lapack/testlapack/dlangb.go
Normal file
@@ -0,0 +1,109 @@
|
|||||||
|
// Copyright ©2021 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/floats"
|
||||||
|
"gonum.org/v1/gonum/lapack"
|
||||||
|
)
|
||||||
|
|
||||||
|
type Dlangber interface {
|
||||||
|
Dlangb(norm lapack.MatrixNorm, n, kl, ku int, ab []float64, ldab int, work []float64) float64
|
||||||
|
}
|
||||||
|
|
||||||
|
func DlangbTest(t *testing.T, impl Dlangber) {
|
||||||
|
rnd := rand.New(rand.NewSource(1))
|
||||||
|
for _, norm := range []lapack.MatrixNorm{lapack.MaxAbs, lapack.MaxRowSum, lapack.MaxColumnSum, lapack.Frobenius} {
|
||||||
|
t.Run(normToString(norm), func(t *testing.T) {
|
||||||
|
for _, n := range []int{0, 1, 2, 3, 4, 5, 10} {
|
||||||
|
for _, kl := range []int{0, 1, 2, 3, 4, 5, 10} {
|
||||||
|
for _, ku := range []int{0, 1, 2, 3, 4, 5, 10} {
|
||||||
|
for _, ldab := range []int{kl + ku + 1, kl + ku + 1 + 7} {
|
||||||
|
for iter := 0; iter < 10; iter++ {
|
||||||
|
dlangbTest(t, impl, rnd, norm, n, kl, ku, ldab)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
})
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
func dlangbTest(t *testing.T, impl Dlangber, rnd *rand.Rand, norm lapack.MatrixNorm, n, kl, ku, ldab int) {
|
||||||
|
const tol = 1e-14
|
||||||
|
|
||||||
|
name := fmt.Sprintf("n=%v,kl=%v,ku=%v,ldab=%v", n, kl, ku, ldab)
|
||||||
|
|
||||||
|
// Generate a random band matrix.
|
||||||
|
ab := randomSlice(n*ldab, rnd)
|
||||||
|
// Sometimes put a NaN into the matrix.
|
||||||
|
if n > 0 && rnd.Float64() < 0.5 {
|
||||||
|
i := rnd.Intn(n)
|
||||||
|
ab[i*ldab+kl] = math.NaN()
|
||||||
|
}
|
||||||
|
abCopy := make([]float64, len(ab))
|
||||||
|
copy(abCopy, ab)
|
||||||
|
|
||||||
|
// Deal with zero-sized matrices early.
|
||||||
|
if n == 0 {
|
||||||
|
got := impl.Dlangb(norm, n, kl, ku, nil, ldab, nil)
|
||||||
|
if got != 0 {
|
||||||
|
t.Errorf("%v: unexpected result for zero-sized matrix with nil input", name)
|
||||||
|
}
|
||||||
|
got = impl.Dlangb(norm, n, kl, ku, ab, ldab, nil)
|
||||||
|
if !floats.Same(ab, abCopy) {
|
||||||
|
t.Errorf("%v: unexpected modification in dl", name)
|
||||||
|
}
|
||||||
|
if got != 0 {
|
||||||
|
t.Errorf("%v: unexpected result for zero-sized matrix with non-nil input", name)
|
||||||
|
}
|
||||||
|
return
|
||||||
|
}
|
||||||
|
|
||||||
|
// Generate a dense representation of the matrix and compute the wanted result.
|
||||||
|
a := zeros(n, n, n)
|
||||||
|
for i := 0; i < n; i++ {
|
||||||
|
for j := max(0, i-kl); j < min(i+ku+1, n); j++ {
|
||||||
|
a.Data[i*a.Stride+j] = ab[i*ldab+j-i+kl]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
var work []float64
|
||||||
|
if norm == lapack.MaxColumnSum {
|
||||||
|
work = make([]float64, n)
|
||||||
|
}
|
||||||
|
got := impl.Dlangb(norm, n, kl, ku, ab, ldab, work)
|
||||||
|
|
||||||
|
if !floats.Same(ab, abCopy) {
|
||||||
|
t.Errorf("%v: unexpected modification in ab", name)
|
||||||
|
}
|
||||||
|
|
||||||
|
want := dlange(norm, n, n, a.Data, a.Stride)
|
||||||
|
|
||||||
|
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)
|
||||||
|
}
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user