github.com/gopherd/gonum@v0.0.4/lapack/gonum/dgehd2.go (about) 1 // Copyright ©2016 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 gonum 6 7 import "github.com/gopherd/gonum/blas" 8 9 // Dgehd2 reduces a block of a general n×n matrix A to upper Hessenberg form H 10 // by an orthogonal similarity transformation Qᵀ * A * Q = H. 11 // 12 // The matrix Q is represented as a product of (ihi-ilo) elementary 13 // reflectors 14 // Q = H_{ilo} H_{ilo+1} ... H_{ihi-1}. 15 // Each H_i has the form 16 // H_i = I - tau[i] * v * vᵀ 17 // where v is a real vector with v[0:i+1] = 0, v[i+1] = 1 and v[ihi+1:n] = 0. 18 // v[i+2:ihi+1] is stored on exit in A[i+2:ihi+1,i]. 19 // 20 // On entry, a contains the n×n general matrix to be reduced. On return, the 21 // upper triangle and the first subdiagonal of A are overwritten with the upper 22 // Hessenberg matrix H, and the elements below the first subdiagonal, with the 23 // slice tau, represent the orthogonal matrix Q as a product of elementary 24 // reflectors. 25 // 26 // The contents of A are illustrated by the following example, with n = 7, ilo = 27 // 1 and ihi = 5. 28 // On entry, 29 // [ a a a a a a a ] 30 // [ a a a a a a ] 31 // [ a a a a a a ] 32 // [ a a a a a a ] 33 // [ a a a a a a ] 34 // [ a a a a a a ] 35 // [ a ] 36 // on return, 37 // [ a a h h h h a ] 38 // [ a h h h h a ] 39 // [ h h h h h h ] 40 // [ v1 h h h h h ] 41 // [ v1 v2 h h h h ] 42 // [ v1 v2 v3 h h h ] 43 // [ a ] 44 // where a denotes an element of the original matrix A, h denotes a 45 // modified element of the upper Hessenberg matrix H, and vi denotes an 46 // element of the vector defining H_i. 47 // 48 // ilo and ihi determine the block of A that will be reduced to upper Hessenberg 49 // form. It must hold that 0 <= ilo <= ihi <= max(0, n-1), otherwise Dgehd2 will 50 // panic. 51 // 52 // On return, tau will contain the scalar factors of the elementary reflectors. 53 // It must have length equal to n-1, otherwise Dgehd2 will panic. 54 // 55 // work must have length at least n, otherwise Dgehd2 will panic. 56 // 57 // Dgehd2 is an internal routine. It is exported for testing purposes. 58 func (impl Implementation) Dgehd2(n, ilo, ihi int, a []float64, lda int, tau, work []float64) { 59 switch { 60 case n < 0: 61 panic(nLT0) 62 case ilo < 0 || max(0, n-1) < ilo: 63 panic(badIlo) 64 case ihi < min(ilo, n-1) || n <= ihi: 65 panic(badIhi) 66 case lda < max(1, n): 67 panic(badLdA) 68 } 69 70 // Quick return if possible. 71 if n == 0 { 72 return 73 } 74 75 switch { 76 case len(a) < (n-1)*lda+n: 77 panic(shortA) 78 case len(tau) != n-1: 79 panic(badLenTau) 80 case len(work) < n: 81 panic(shortWork) 82 } 83 84 for i := ilo; i < ihi; i++ { 85 // Compute elementary reflector H_i to annihilate A[i+2:ihi+1,i]. 86 var aii float64 87 aii, tau[i] = impl.Dlarfg(ihi-i, a[(i+1)*lda+i], a[min(i+2, n-1)*lda+i:], lda) 88 a[(i+1)*lda+i] = 1 89 90 // Apply H_i to A[0:ihi+1,i+1:ihi+1] from the right. 91 impl.Dlarf(blas.Right, ihi+1, ihi-i, a[(i+1)*lda+i:], lda, tau[i], a[i+1:], lda, work) 92 93 // Apply H_i to A[i+1:ihi+1,i+1:n] from the left. 94 impl.Dlarf(blas.Left, ihi-i, n-i-1, a[(i+1)*lda+i:], lda, tau[i], a[(i+1)*lda+i+1:], lda, work) 95 a[(i+1)*lda+i] = aii 96 } 97 }