ingress-nginx-helm/vendor/gonum.org/v1/gonum/lapack/gonum/dlabrd.go
Manuel Alejandro de Brito Fontes 3dd1699637
Add dependencies for code generator
2019-05-14 20:15:49 -04:00

173 lines
6.6 KiB
Go
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

// 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 gonum
import (
"gonum.org/v1/gonum/blas"
"gonum.org/v1/gonum/blas/blas64"
)
// Dlabrd reduces the first NB rows and columns of a real general m×n matrix
// A to upper or lower bidiagonal form by an orthogonal transformation
// Q**T * A * P
// If m >= n, A is reduced to upper bidiagonal form and upon exit the elements
// on and below the diagonal in the first nb columns represent the elementary
// reflectors, and the elements above the diagonal in the first nb rows represent
// the matrix P. If m < n, A is reduced to lower bidiagonal form and the elements
// P is instead stored above the diagonal.
//
// The reduction to bidiagonal form is stored in d and e, where d are the diagonal
// elements, and e are the off-diagonal elements.
//
// The matrices Q and P are products of elementary reflectors
// Q = H_0 * H_1 * ... * H_{nb-1}
// P = G_0 * G_1 * ... * G_{nb-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, n = 5, and nb = 2
// [ 1 1 u1 u1 u1]
// [v1 1 1 u2 u2]
// [v1 v2 a a a]
// [v1 v2 a a a]
// [v1 v2 a a a]
// [v1 v2 a a a]
// and when m = 5, n = 6, and nb = 2
// [ 1 u1 u1 u1 u1 u1]
// [ 1 1 u2 u2 u2 u2]
// [v1 1 a a a a]
// [v1 v2 a a a a]
// [v1 v2 a a a a]
//
// Dlabrd also returns the matrices X and Y which are used with U and V to
// apply the transformation to the unreduced part of the matrix
// A := A - V*Y^T - X*U^T
// and returns the matrices X and Y which are needed to apply the
// transformation to the unreduced part of A.
//
// X is an m×nb matrix, Y is an n×nb matrix. d, e, taup, and tauq must all have
// length at least nb. Dlabrd will panic if these size constraints are violated.
//
// Dlabrd is an internal routine. It is exported for testing purposes.
func (impl Implementation) Dlabrd(m, n, nb int, a []float64, lda int, d, e, tauQ, tauP, x []float64, ldx int, y []float64, ldy int) {
switch {
case m < 0:
panic(mLT0)
case n < 0:
panic(nLT0)
case nb < 0:
panic(nbLT0)
case nb > n:
panic(nbGTN)
case nb > m:
panic(nbGTM)
case lda < max(1, n):
panic(badLdA)
case ldx < max(1, nb):
panic(badLdX)
case ldy < max(1, nb):
panic(badLdY)
}
if m == 0 || n == 0 || nb == 0 {
return
}
switch {
case len(a) < (m-1)*lda+n:
panic(shortA)
case len(d) < nb:
panic(shortD)
case len(e) < nb:
panic(shortE)
case len(tauQ) < nb:
panic(shortTauQ)
case len(tauP) < nb:
panic(shortTauP)
case len(x) < (m-1)*ldx+nb:
panic(shortX)
case len(y) < (n-1)*ldy+nb:
panic(shortY)
}
bi := blas64.Implementation()
if m >= n {
// Reduce to upper bidiagonal form.
for i := 0; i < nb; i++ {
bi.Dgemv(blas.NoTrans, m-i, i, -1, a[i*lda:], lda, y[i*ldy:], 1, 1, a[i*lda+i:], lda)
bi.Dgemv(blas.NoTrans, m-i, i, -1, x[i*ldx:], ldx, a[i:], lda, 1, a[i*lda+i:], lda)
a[i*lda+i], tauQ[i] = impl.Dlarfg(m-i, a[i*lda+i], a[min(i+1, m-1)*lda+i:], lda)
d[i] = a[i*lda+i]
if i < n-1 {
// Compute Y[i+1:n, i].
a[i*lda+i] = 1
bi.Dgemv(blas.Trans, m-i, n-i-1, 1, a[i*lda+i+1:], lda, a[i*lda+i:], lda, 0, y[(i+1)*ldy+i:], ldy)
bi.Dgemv(blas.Trans, m-i, i, 1, a[i*lda:], lda, a[i*lda+i:], lda, 0, y[i:], ldy)
bi.Dgemv(blas.NoTrans, n-i-1, i, -1, y[(i+1)*ldy:], ldy, y[i:], ldy, 1, y[(i+1)*ldy+i:], ldy)
bi.Dgemv(blas.Trans, m-i, i, 1, x[i*ldx:], ldx, a[i*lda+i:], lda, 0, y[i:], ldy)
bi.Dgemv(blas.Trans, i, n-i-1, -1, a[i+1:], lda, y[i:], ldy, 1, y[(i+1)*ldy+i:], ldy)
bi.Dscal(n-i-1, tauQ[i], y[(i+1)*ldy+i:], ldy)
// Update A[i, i+1:n].
bi.Dgemv(blas.NoTrans, n-i-1, i+1, -1, y[(i+1)*ldy:], ldy, a[i*lda:], 1, 1, a[i*lda+i+1:], 1)
bi.Dgemv(blas.Trans, i, n-i-1, -1, a[i+1:], lda, x[i*ldx:], 1, 1, a[i*lda+i+1:], 1)
// Generate reflection P[i] to annihilate A[i, i+2:n].
a[i*lda+i+1], tauP[i] = impl.Dlarfg(n-i-1, a[i*lda+i+1], a[i*lda+min(i+2, n-1):], 1)
e[i] = a[i*lda+i+1]
a[i*lda+i+1] = 1
// Compute X[i+1:m, i].
bi.Dgemv(blas.NoTrans, m-i-1, n-i-1, 1, a[(i+1)*lda+i+1:], lda, a[i*lda+i+1:], 1, 0, x[(i+1)*ldx+i:], ldx)
bi.Dgemv(blas.Trans, n-i-1, i+1, 1, y[(i+1)*ldy:], ldy, a[i*lda+i+1:], 1, 0, x[i:], ldx)
bi.Dgemv(blas.NoTrans, m-i-1, i+1, -1, a[(i+1)*lda:], lda, x[i:], ldx, 1, x[(i+1)*ldx+i:], ldx)
bi.Dgemv(blas.NoTrans, i, n-i-1, 1, a[i+1:], lda, a[i*lda+i+1:], 1, 0, x[i:], ldx)
bi.Dgemv(blas.NoTrans, m-i-1, i, -1, x[(i+1)*ldx:], ldx, x[i:], ldx, 1, x[(i+1)*ldx+i:], ldx)
bi.Dscal(m-i-1, tauP[i], x[(i+1)*ldx+i:], ldx)
}
}
return
}
// Reduce to lower bidiagonal form.
for i := 0; i < nb; i++ {
// Update A[i,i:n]
bi.Dgemv(blas.NoTrans, n-i, i, -1, y[i*ldy:], ldy, a[i*lda:], 1, 1, a[i*lda+i:], 1)
bi.Dgemv(blas.Trans, i, n-i, -1, a[i:], lda, x[i*ldx:], 1, 1, a[i*lda+i:], 1)
// Generate reflection P[i] to annihilate A[i, i+1:n]
a[i*lda+i], tauP[i] = impl.Dlarfg(n-i, a[i*lda+i], a[i*lda+min(i+1, n-1):], 1)
d[i] = a[i*lda+i]
if i < m-1 {
a[i*lda+i] = 1
// Compute X[i+1:m, i].
bi.Dgemv(blas.NoTrans, m-i-1, n-i, 1, a[(i+1)*lda+i:], lda, a[i*lda+i:], 1, 0, x[(i+1)*ldx+i:], ldx)
bi.Dgemv(blas.Trans, n-i, i, 1, y[i*ldy:], ldy, a[i*lda+i:], 1, 0, x[i:], ldx)
bi.Dgemv(blas.NoTrans, m-i-1, i, -1, a[(i+1)*lda:], lda, x[i:], ldx, 1, x[(i+1)*ldx+i:], ldx)
bi.Dgemv(blas.NoTrans, i, n-i, 1, a[i:], lda, a[i*lda+i:], 1, 0, x[i:], ldx)
bi.Dgemv(blas.NoTrans, m-i-1, i, -1, x[(i+1)*ldx:], ldx, x[i:], ldx, 1, x[(i+1)*ldx+i:], ldx)
bi.Dscal(m-i-1, tauP[i], x[(i+1)*ldx+i:], ldx)
// Update A[i+1:m, i].
bi.Dgemv(blas.NoTrans, m-i-1, i, -1, a[(i+1)*lda:], lda, y[i*ldy:], 1, 1, a[(i+1)*lda+i:], lda)
bi.Dgemv(blas.NoTrans, m-i-1, i+1, -1, x[(i+1)*ldx:], ldx, a[i:], lda, 1, a[(i+1)*lda+i:], lda)
// Generate reflection Q[i] to annihilate A[i+2:m, i].
a[(i+1)*lda+i], tauQ[i] = impl.Dlarfg(m-i-1, a[(i+1)*lda+i], a[min(i+2, m-1)*lda+i:], lda)
e[i] = a[(i+1)*lda+i]
a[(i+1)*lda+i] = 1
// Compute Y[i+1:n, i].
bi.Dgemv(blas.Trans, m-i-1, n-i-1, 1, a[(i+1)*lda+i+1:], lda, a[(i+1)*lda+i:], lda, 0, y[(i+1)*ldy+i:], ldy)
bi.Dgemv(blas.Trans, m-i-1, i, 1, a[(i+1)*lda:], lda, a[(i+1)*lda+i:], lda, 0, y[i:], ldy)
bi.Dgemv(blas.NoTrans, n-i-1, i, -1, y[(i+1)*ldy:], ldy, y[i:], ldy, 1, y[(i+1)*ldy+i:], ldy)
bi.Dgemv(blas.Trans, m-i-1, i+1, 1, x[(i+1)*ldx:], ldx, a[(i+1)*lda+i:], lda, 0, y[i:], ldy)
bi.Dgemv(blas.Trans, i+1, n-i-1, -1, a[i+1:], lda, y[i:], ldy, 1, y[(i+1)*ldy+i:], ldy)
bi.Dscal(n-i-1, tauQ[i], y[(i+1)*ldy+i:], ldy)
}
}
}