native: add Dormhr

This commit is contained in:
Vladimir Chalupecky
2016-06-12 22:23:10 +09:00
parent 1b8740f74c
commit 13de76eec4

117
native/dormhr.go Normal file
View File

@@ -0,0 +1,117 @@
// Copyright ©2016 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 native
import "github.com/gonum/blas"
// Dormhr multiplies an m×n general matrix C with an nq×nq orthogonal matrix Q
// Q * C, if side == blas.Left and trans == blas.NoTrans,
// Q^T * C, if side == blas.Left and trans == blas.Trans,
// C * Q, if side == blas.Right and trans == blas.NoTrans,
// C * Q^T, if side == blas.Right and trans == blas.Trans,
// where nq == m if side == blas.Left and nq == n if side == blas.Right.
//
// Q is defined implicitly as the product of ihi-ilo elementary reflectors, as
// returned by Dgehrd:
// Q = H_{ilo} H_{ilo+1} ... H_{ihi-1}.
// Q is equal to the identity matrix except in the submatrix
// Q[ilo+1:ihi+1,ilo+1:ihi+1].
//
// ilo and ihi must have the same values as in the previous call of Dgehrd. It
// must hold that
// 0 <= ilo <= ihi < m, if m > 0 and side == blas.Left,
// ilo = 0 and ihi = -1, if m = 0 and side == blas.Left,
// 0 <= ilo <= ihi < n, if n > 0 and side == blas.Right,
// ilo = 0 and ihi = -1, if n = 0 and side == blas.Right.
//
// a and lda represent an m×m matrix if side == blas.Left and an n×n matrix if
// side == blas.Right. The matrix contains vectors which define the elementary
// reflectors, as returned by Dgehrd.
//
// tau contains the scalar factors of the elementary reflectors, as returned by
// Dgehrd. tau must have length m-1 if side == blas.Left and n-1 if side ==
// blas.Right.
//
// c and ldc represent the m×n matrix C. On return, c is overwritten by the
// product with Q.
//
// work must have length at least max(1,lwork), and lwork must be at least
// max(1,n), if side == blas.Left, and max(1,m), if side == blas.Right. For
// optimum performance lwork should be at least n*nb if side == blas.Left and
// m*nb if side == blas.Right, where nb is the optimal block size. On return,
// work[0] will contain the optimal value of lwork.
//
// If lwork == -1, instead of performing Dormhr, only the optimal value of lwork
// will be stored in work[0].
//
// If any requirement on input sizes is not met, Dormhr will panic.
//
// Dormhr is an internal routine. It is exported for testing purposes.
func (impl Implementation) Dormhr(side blas.Side, trans blas.Transpose, m, n, ilo, ihi int, a []float64, lda int, tau, c []float64, ldc int, work []float64, lwork int) {
var (
nq int // The order of Q.
nw int // The minimum length of work.
)
switch side {
case blas.Left:
nq = m
nw = n
case blas.Right:
nq = n
nw = m
default:
panic(badSide)
}
checkMatrix(m, n, c, ldc)
checkMatrix(nq, nq, a, lda)
switch {
case trans != blas.NoTrans && trans != blas.Trans:
panic(badTrans)
case ilo < 0 || max(1, nq) <= ilo:
panic(badIlo)
case ihi < min(ilo, nq-1) || nq <= ihi:
panic(badIhi)
case nq > 0 && len(tau) != nq-1:
panic(badTau)
case lwork < max(1, nw) && lwork != -1:
panic(badWork)
case len(work) < max(1, lwork):
panic(shortWork)
}
nh := ihi - ilo
var nb int
if side == blas.Left {
opts := "LN"
if trans == blas.Trans {
opts = "LT"
}
nb = impl.Ilaenv(1, "DORMQR", opts, nh, n, nh, -1)
} else {
opts := "RN"
if trans == blas.Trans {
opts = "RT"
}
nb = impl.Ilaenv(1, "DORMQR", opts, m, nh, nh, -1)
}
lwkopt := max(1, nw) * nb
if lwork == -1 {
work[0] = float64(lwkopt)
return
}
if m == 0 || n == 0 || nh == 0 {
work[0] = 1
return
}
if side == blas.Left {
impl.Dormqr(side, trans, nh, n, nh, a[(ilo+1)*lda+ilo:], lda,
tau[ilo:ihi], c[(ilo+1)*ldc:], ldc, work, lwork)
} else {
impl.Dormqr(side, trans, m, nh, nh, a[(ilo+1)*lda+ilo:], lda,
tau[ilo:ihi], c[ilo+1:], ldc, work, lwork)
}
work[0] = float64(lwkopt)
}