github.com/gonum/lapack@v0.0.0-20181123203213-e4cdc5a0bff9/native/dlabrd.go (about) 1 // Copyright ©2015 The gonum Authors. All rights reserved. 2 // Use of this source code is governed by a BSD-style 3 // license that can be found in the LICENSE file. 4 5 package native 6 7 import ( 8 "github.com/gonum/blas" 9 "github.com/gonum/blas/blas64" 10 ) 11 12 // Dlabrd reduces the first NB rows and columns of a real general m×n matrix 13 // A to upper or lower bidiagonal form by an orthogonal transformation 14 // Q**T * A * P 15 // If m >= n, A is reduced to upper bidiagonal form and upon exit the elements 16 // on and below the diagonal in the first nb columns represent the elementary 17 // reflectors, and the elements above the diagonal in the first nb rows represent 18 // the matrix P. If m < n, A is reduced to lower bidiagonal form and the elements 19 // P is instead stored above the diagonal. 20 // 21 // The reduction to bidiagonal form is stored in d and e, where d are the diagonal 22 // elements, and e are the off-diagonal elements. 23 // 24 // The matrices Q and P are products of elementary reflectors 25 // Q = H_0 * H_1 * ... * H_{nb-1} 26 // P = G_0 * G_1 * ... * G_{nb-1} 27 // where 28 // H_i = I - tauQ[i] * v_i * v_i^T 29 // G_i = I - tauP[i] * u_i * u_i^T 30 // 31 // As an example, on exit the entries of A when m = 6, n = 5, and nb = 2 32 // [ 1 1 u1 u1 u1] 33 // [v1 1 1 u2 u2] 34 // [v1 v2 a a a] 35 // [v1 v2 a a a] 36 // [v1 v2 a a a] 37 // [v1 v2 a a a] 38 // and when m = 5, n = 6, and nb = 2 39 // [ 1 u1 u1 u1 u1 u1] 40 // [ 1 1 u2 u2 u2 u2] 41 // [v1 1 a a a a] 42 // [v1 v2 a a a a] 43 // [v1 v2 a a a a] 44 // 45 // Dlabrd also returns the matrices X and Y which are used with U and V to 46 // apply the transformation to the unreduced part of the matrix 47 // A := A - V*Y^T - X*U^T 48 // and returns the matrices X and Y which are needed to apply the 49 // transformation to the unreduced part of A. 50 // 51 // X is an m×nb matrix, Y is an n×nb matrix. d, e, taup, and tauq must all have 52 // length at least nb. Dlabrd will panic if these size constraints are violated. 53 // 54 // Dlabrd is an internal routine. It is exported for testing purposes. 55 func (impl Implementation) Dlabrd(m, n, nb int, a []float64, lda int, d, e, tauQ, tauP, x []float64, ldx int, y []float64, ldy int) { 56 checkMatrix(m, n, a, lda) 57 checkMatrix(m, nb, x, ldx) 58 checkMatrix(n, nb, y, ldy) 59 if len(d) < nb { 60 panic(badD) 61 } 62 if len(e) < nb { 63 panic(badE) 64 } 65 if len(tauQ) < nb { 66 panic(badTauQ) 67 } 68 if len(tauP) < nb { 69 panic(badTauP) 70 } 71 if m <= 0 || n <= 0 { 72 return 73 } 74 bi := blas64.Implementation() 75 if m >= n { 76 // Reduce to upper bidiagonal form. 77 for i := 0; i < nb; i++ { 78 bi.Dgemv(blas.NoTrans, m-i, i, -1, a[i*lda:], lda, y[i*ldy:], 1, 1, a[i*lda+i:], lda) 79 bi.Dgemv(blas.NoTrans, m-i, i, -1, x[i*ldx:], ldx, a[i:], lda, 1, a[i*lda+i:], lda) 80 81 a[i*lda+i], tauQ[i] = impl.Dlarfg(m-i, a[i*lda+i], a[min(i+1, m-1)*lda+i:], lda) 82 d[i] = a[i*lda+i] 83 if i < n-1 { 84 // Compute Y[i+1:n, i]. 85 a[i*lda+i] = 1 86 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) 87 bi.Dgemv(blas.Trans, m-i, i, 1, a[i*lda:], lda, a[i*lda+i:], lda, 0, y[i:], ldy) 88 bi.Dgemv(blas.NoTrans, n-i-1, i, -1, y[(i+1)*ldy:], ldy, y[i:], ldy, 1, y[(i+1)*ldy+i:], ldy) 89 bi.Dgemv(blas.Trans, m-i, i, 1, x[i*ldx:], ldx, a[i*lda+i:], lda, 0, y[i:], ldy) 90 bi.Dgemv(blas.Trans, i, n-i-1, -1, a[i+1:], lda, y[i:], ldy, 1, y[(i+1)*ldy+i:], ldy) 91 bi.Dscal(n-i-1, tauQ[i], y[(i+1)*ldy+i:], ldy) 92 93 // Update A[i, i+1:n]. 94 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) 95 bi.Dgemv(blas.Trans, i, n-i-1, -1, a[i+1:], lda, x[i*ldx:], 1, 1, a[i*lda+i+1:], 1) 96 97 // Generate reflection P[i] to annihilate A[i, i+2:n]. 98 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) 99 e[i] = a[i*lda+i+1] 100 a[i*lda+i+1] = 1 101 102 // Compute X[i+1:m, i]. 103 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) 104 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) 105 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) 106 bi.Dgemv(blas.NoTrans, i, n-i-1, 1, a[i+1:], lda, a[i*lda+i+1:], 1, 0, x[i:], ldx) 107 bi.Dgemv(blas.NoTrans, m-i-1, i, -1, x[(i+1)*ldx:], ldx, x[i:], ldx, 1, x[(i+1)*ldx+i:], ldx) 108 bi.Dscal(m-i-1, tauP[i], x[(i+1)*ldx+i:], ldx) 109 } 110 } 111 return 112 } 113 // Reduce to lower bidiagonal form. 114 for i := 0; i < nb; i++ { 115 // Update A[i,i:n] 116 bi.Dgemv(blas.NoTrans, n-i, i, -1, y[i*ldy:], ldy, a[i*lda:], 1, 1, a[i*lda+i:], 1) 117 bi.Dgemv(blas.Trans, i, n-i, -1, a[i:], lda, x[i*ldx:], 1, 1, a[i*lda+i:], 1) 118 119 // Generate reflection P[i] to annihilate A[i, i+1:n] 120 a[i*lda+i], tauP[i] = impl.Dlarfg(n-i, a[i*lda+i], a[i*lda+min(i+1, n-1):], 1) 121 d[i] = a[i*lda+i] 122 if i < m-1 { 123 a[i*lda+i] = 1 124 // Compute X[i+1:m, i]. 125 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) 126 bi.Dgemv(blas.Trans, n-i, i, 1, y[i*ldy:], ldy, a[i*lda+i:], 1, 0, x[i:], ldx) 127 bi.Dgemv(blas.NoTrans, m-i-1, i, -1, a[(i+1)*lda:], lda, x[i:], ldx, 1, x[(i+1)*ldx+i:], ldx) 128 bi.Dgemv(blas.NoTrans, i, n-i, 1, a[i:], lda, a[i*lda+i:], 1, 0, x[i:], ldx) 129 bi.Dgemv(blas.NoTrans, m-i-1, i, -1, x[(i+1)*ldx:], ldx, x[i:], ldx, 1, x[(i+1)*ldx+i:], ldx) 130 bi.Dscal(m-i-1, tauP[i], x[(i+1)*ldx+i:], ldx) 131 132 // Update A[i+1:m, i]. 133 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) 134 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) 135 136 // Generate reflection Q[i] to annihilate A[i+2:m, i]. 137 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) 138 e[i] = a[(i+1)*lda+i] 139 a[(i+1)*lda+i] = 1 140 141 // Compute Y[i+1:n, i]. 142 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) 143 bi.Dgemv(blas.Trans, m-i-1, i, 1, a[(i+1)*lda:], lda, a[(i+1)*lda+i:], lda, 0, y[i:], ldy) 144 bi.Dgemv(blas.NoTrans, n-i-1, i, -1, y[(i+1)*ldy:], ldy, y[i:], ldy, 1, y[(i+1)*ldy+i:], ldy) 145 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) 146 bi.Dgemv(blas.Trans, i+1, n-i-1, -1, a[i+1:], lda, y[i:], ldy, 1, y[(i+1)*ldy+i:], ldy) 147 bi.Dscal(n-i-1, tauQ[i], y[(i+1)*ldy+i:], ldy) 148 } 149 } 150 }