// 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 gonum import "gonum.org/v1/gonum/blas" // Dgehd2 reduces a block of a general n×n matrix A to upper Hessenberg form H // by an orthogonal similarity transformation Q^T * A * Q = H. // // The matrix Q is represented as a product of (ihi-ilo) elementary // reflectors // Q = H_{ilo} H_{ilo+1} ... H_{ihi-1}. // Each H_i has the form // H_i = I - tau[i] * v * v^T // where v is a real vector with v[0:i+1] = 0, v[i+1] = 1 and v[ihi+1:n] = 0. // v[i+2:ihi+1] is stored on exit in A[i+2:ihi+1,i]. // // On entry, a contains the n×n general matrix to be reduced. On return, the // upper triangle and the first subdiagonal of A are overwritten with the upper // Hessenberg matrix H, and the elements below the first subdiagonal, with the // slice tau, represent the orthogonal matrix Q as a product of elementary // reflectors. // // The contents of A are illustrated by the following example, with n = 7, ilo = // 1 and ihi = 5. // On entry, // [ a a a a a a a ] // [ a a a a a a ] // [ a a a a a a ] // [ a a a a a a ] // [ a a a a a a ] // [ a a a a a a ] // [ a ] // on return, // [ a a h h h h a ] // [ a h h h h a ] // [ h h h h h h ] // [ v1 h h h h h ] // [ v1 v2 h h h h ] // [ v1 v2 v3 h h h ] // [ a ] // where a denotes an element of the original matrix A, h denotes a // modified element of the upper Hessenberg matrix H, and vi denotes an // element of the vector defining H_i. // // ilo and ihi determine the block of A that will be reduced to upper Hessenberg // form. It must hold that 0 <= ilo <= ihi <= max(0, n-1), otherwise Dgehd2 will // panic. // // On return, tau will contain the scalar factors of the elementary reflectors. // It must have length equal to n-1, otherwise Dgehd2 will panic. // // work must have length at least n, otherwise Dgehd2 will panic. // // Dgehd2 is an internal routine. It is exported for testing purposes. func (impl Implementation) Dgehd2(n, ilo, ihi int, a []float64, lda int, tau, work []float64) { switch { case n < 0: panic(nLT0) case ilo < 0 || max(0, n-1) < ilo: panic(badIlo) case ihi < min(ilo, n-1) || n <= ihi: panic(badIhi) case lda < max(1, n): panic(badLdA) } // Quick return if possible. if n == 0 { return } switch { case len(a) < (n-1)*lda+n: panic(shortA) case len(tau) != n-1: panic(badLenTau) case len(work) < n: panic(shortWork) } for i := ilo; i < ihi; i++ { // Compute elementary reflector H_i to annihilate A[i+2:ihi+1,i]. var aii float64 aii, tau[i] = impl.Dlarfg(ihi-i, a[(i+1)*lda+i], a[min(i+2, n-1)*lda+i:], lda) a[(i+1)*lda+i] = 1 // Apply H_i to A[0:ihi+1,i+1:ihi+1] from the right. impl.Dlarf(blas.Right, ihi+1, ihi-i, a[(i+1)*lda+i:], lda, tau[i], a[i+1:], lda, work) // Apply H_i to A[i+1:ihi+1,i+1:n] from the left. 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) a[(i+1)*lda+i] = aii } }