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gonum/lapack/native/dgebrd.go
2017-05-23 00:03:03 -06:00

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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 native
import (
"gonum.org/v1/gonum/blas"
"gonum.org/v1/gonum/blas/blas64"
)
// Dgebrd reduces a general m×n matrix A to upper or lower bidiagonal form B by
// an orthogonal transformation:
// Q^T * A * P = B.
// The diagonal elements of B are stored in d and the off-diagonal elements are stored
// in e. These are additionally stored along the diagonal of A and the off-diagonal
// of A. If m >= n B is an upper-bidiagonal matrix, and if m < n B is a
// lower-bidiagonal matrix.
//
// The remaining elements of A store the data needed to construct Q and P.
// The matrices Q and P are products of elementary reflectors
// if m >= n, Q = H_0 * H_1 * ... * H_{n-1},
// P = G_0 * G_1 * ... * G_{n-2},
// if m < n, Q = H_0 * H_1 * ... * H_{m-2},
// P = G_0 * G_1 * ... * G_{m-1},
// where
// H_i = I - tauQ[i] * v_i * v_i^T,
// G_i = I - tauP[i] * u_i * u_i^T.
//
// As an example, on exit the entries of A when m = 6, and n = 5
// [ d e u1 u1 u1]
// [v1 d e u2 u2]
// [v1 v2 d e u3]
// [v1 v2 v3 d e]
// [v1 v2 v3 v4 d]
// [v1 v2 v3 v4 v5]
// and when m = 5, n = 6
// [ d u1 u1 u1 u1 u1]
// [ e d u2 u2 u2 u2]
// [v1 e d u3 u3 u3]
// [v1 v2 e d u4 u4]
// [v1 v2 v3 e d u5]
//
// d, tauQ, and tauP must all have length at least min(m,n), and e must have
// length min(m,n) - 1, unless lwork is -1 when there is no check except for
// work which must have a length of at least one.
//
// work is temporary storage, and lwork specifies the usable memory length.
// At minimum, lwork >= max(1,m,n) or be -1 and this function will panic otherwise.
// Dgebrd is blocked decomposition, but the block size is limited
// by the temporary space available. If lwork == -1, instead of performing Dgebrd,
// the optimal work length will be stored into work[0].
//
// Dgebrd is an internal routine. It is exported for testing purposes.
func (impl Implementation) Dgebrd(m, n int, a []float64, lda int, d, e, tauQ, tauP, work []float64, lwork int) {
checkMatrix(m, n, a, lda)
// Calculate optimal work.
nb := impl.Ilaenv(1, "DGEBRD", " ", m, n, -1, -1)
var lworkOpt int
if lwork == -1 {
if len(work) < 1 {
panic(badWork)
}
lworkOpt = ((m + n) * nb)
work[0] = float64(max(1, lworkOpt))
return
}
minmn := min(m, n)
if len(d) < minmn {
panic(badD)
}
if len(e) < minmn-1 {
panic(badE)
}
if len(tauQ) < minmn {
panic(badTauQ)
}
if len(tauP) < minmn {
panic(badTauP)
}
ws := max(m, n)
if lwork < max(1, ws) {
panic(badWork)
}
if len(work) < lwork {
panic(badWork)
}
var nx int
if nb > 1 && nb < minmn {
nx = max(nb, impl.Ilaenv(3, "DGEBRD", " ", m, n, -1, -1))
if nx < minmn {
ws = (m + n) * nb
if lwork < ws {
nbmin := impl.Ilaenv(2, "DGEBRD", " ", m, n, -1, -1)
if lwork >= (m+n)*nbmin {
nb = lwork / (m + n)
} else {
nb = minmn
nx = minmn
}
}
}
} else {
nx = minmn
}
bi := blas64.Implementation()
ldworkx := nb
ldworky := nb
var i int
// Netlib lapack has minmn - nx, but this makes the last nx rows (which by
// default is large) be unblocked. As written here, the blocking is more
// consistent.
for i = 0; i < minmn-nb; i += nb {
// Reduce rows and columns i:i+nb to bidiagonal form and return
// the matrices X and Y which are needed to update the unreduced
// part of the matrix.
// X is stored in the first m rows of work, y in the next rows.
x := work[:m*ldworkx]
y := work[m*ldworkx:]
impl.Dlabrd(m-i, n-i, nb, a[i*lda+i:], lda,
d[i:], e[i:], tauQ[i:], tauP[i:],
x, ldworkx, y, ldworky)
// Update the trailing submatrix A[i+nb:m,i+nb:n], using an update
// of the form A := A - V*Y**T - X*U**T
bi.Dgemm(blas.NoTrans, blas.Trans, m-i-nb, n-i-nb, nb,
-1, a[(i+nb)*lda+i:], lda, y[nb*ldworky:], ldworky,
1, a[(i+nb)*lda+i+nb:], lda)
bi.Dgemm(blas.NoTrans, blas.NoTrans, m-i-nb, n-i-nb, nb,
-1, x[nb*ldworkx:], ldworkx, a[i*lda+i+nb:], lda,
1, a[(i+nb)*lda+i+nb:], lda)
// Copy diagonal and off-diagonal elements of B back into A.
if m >= n {
for j := i; j < i+nb; j++ {
a[j*lda+j] = d[j]
a[j*lda+j+1] = e[j]
}
} else {
for j := i; j < i+nb; j++ {
a[j*lda+j] = d[j]
a[(j+1)*lda+j] = e[j]
}
}
}
// Use unblocked code to reduce the remainder of the matrix.
impl.Dgebd2(m-i, n-i, a[i*lda+i:], lda, d[i:], e[i:], tauQ[i:], tauP[i:], work)
work[0] = float64(lworkOpt)
}