github.com/gopherd/gonum@v0.0.4/lapack/gonum/dsytd2.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 ( 8 "github.com/gopherd/gonum/blas" 9 "github.com/gopherd/gonum/blas/blas64" 10 ) 11 12 // Dsytd2 reduces a symmetric n×n matrix A to symmetric tridiagonal form T by 13 // an orthogonal similarity transformation 14 // Qᵀ * A * Q = T 15 // On entry, the matrix is contained in the specified triangle of a. On exit, 16 // if uplo == blas.Upper, the diagonal and first super-diagonal of a are 17 // overwritten with the elements of T. The elements above the first super-diagonal 18 // are overwritten with the elementary reflectors that are used with 19 // the elements written to tau in order to construct Q. If uplo == blas.Lower, 20 // the elements are written in the lower triangular region. 21 // 22 // d must have length at least n. e and tau must have length at least n-1. Dsytd2 23 // will panic if these sizes are not met. 24 // 25 // Q is represented as a product of elementary reflectors. 26 // If uplo == blas.Upper 27 // Q = H_{n-2} * ... * H_1 * H_0 28 // and if uplo == blas.Lower 29 // Q = H_0 * H_1 * ... * H_{n-2} 30 // where 31 // H_i = I - tau * v * vᵀ 32 // where tau is stored in tau[i], and v is stored in a. 33 // 34 // If uplo == blas.Upper, v[0:i-1] is stored in A[0:i-1,i+1], v[i] = 1, and 35 // v[i+1:] = 0. The elements of a are 36 // [ d e v2 v3 v4] 37 // [ d e v3 v4] 38 // [ d e v4] 39 // [ d e] 40 // [ d] 41 // If uplo == blas.Lower, v[0:i+1] = 0, v[i+1] = 1, and v[i+2:] is stored in 42 // A[i+2:n,i]. 43 // The elements of a are 44 // [ d ] 45 // [ e d ] 46 // [v1 e d ] 47 // [v1 v2 e d ] 48 // [v1 v2 v3 e d] 49 // 50 // Dsytd2 is an internal routine. It is exported for testing purposes. 51 func (impl Implementation) Dsytd2(uplo blas.Uplo, n int, a []float64, lda int, d, e, tau []float64) { 52 switch { 53 case uplo != blas.Upper && uplo != blas.Lower: 54 panic(badUplo) 55 case n < 0: 56 panic(nLT0) 57 case lda < max(1, n): 58 panic(badLdA) 59 } 60 61 // Quick return if possible. 62 if n == 0 { 63 return 64 } 65 66 switch { 67 case len(a) < (n-1)*lda+n: 68 panic(shortA) 69 case len(d) < n: 70 panic(shortD) 71 case len(e) < n-1: 72 panic(shortE) 73 case len(tau) < n-1: 74 panic(shortTau) 75 } 76 77 bi := blas64.Implementation() 78 79 if uplo == blas.Upper { 80 // Reduce the upper triangle of A. 81 for i := n - 2; i >= 0; i-- { 82 // Generate elementary reflector H_i = I - tau * v * vᵀ to 83 // annihilate A[i:i-1, i+1]. 84 var taui float64 85 a[i*lda+i+1], taui = impl.Dlarfg(i+1, a[i*lda+i+1], a[i+1:], lda) 86 e[i] = a[i*lda+i+1] 87 if taui != 0 { 88 // Apply H_i from both sides to A[0:i,0:i]. 89 a[i*lda+i+1] = 1 90 91 // Compute x := tau * A * v storing x in tau[0:i]. 92 bi.Dsymv(uplo, i+1, taui, a, lda, a[i+1:], lda, 0, tau, 1) 93 94 // Compute w := x - 1/2 * tau * (xᵀ * v) * v. 95 alpha := -0.5 * taui * bi.Ddot(i+1, tau, 1, a[i+1:], lda) 96 bi.Daxpy(i+1, alpha, a[i+1:], lda, tau, 1) 97 98 // Apply the transformation as a rank-2 update 99 // A = A - v * wᵀ - w * vᵀ. 100 bi.Dsyr2(uplo, i+1, -1, a[i+1:], lda, tau, 1, a, lda) 101 a[i*lda+i+1] = e[i] 102 } 103 d[i+1] = a[(i+1)*lda+i+1] 104 tau[i] = taui 105 } 106 d[0] = a[0] 107 return 108 } 109 // Reduce the lower triangle of A. 110 for i := 0; i < n-1; i++ { 111 // Generate elementary reflector H_i = I - tau * v * vᵀ to 112 // annihilate A[i+2:n, i]. 113 var taui float64 114 a[(i+1)*lda+i], taui = impl.Dlarfg(n-i-1, a[(i+1)*lda+i], a[min(i+2, n-1)*lda+i:], lda) 115 e[i] = a[(i+1)*lda+i] 116 if taui != 0 { 117 // Apply H_i from both sides to A[i+1:n, i+1:n]. 118 a[(i+1)*lda+i] = 1 119 120 // Compute x := tau * A * v, storing y in tau[i:n-1]. 121 bi.Dsymv(uplo, n-i-1, taui, a[(i+1)*lda+i+1:], lda, a[(i+1)*lda+i:], lda, 0, tau[i:], 1) 122 123 // Compute w := x - 1/2 * tau * (xᵀ * v) * v. 124 alpha := -0.5 * taui * bi.Ddot(n-i-1, tau[i:], 1, a[(i+1)*lda+i:], lda) 125 bi.Daxpy(n-i-1, alpha, a[(i+1)*lda+i:], lda, tau[i:], 1) 126 127 // Apply the transformation as a rank-2 update 128 // A = A - v * wᵀ - w * vᵀ. 129 bi.Dsyr2(uplo, n-i-1, -1, a[(i+1)*lda+i:], lda, tau[i:], 1, a[(i+1)*lda+i+1:], lda) 130 a[(i+1)*lda+i] = e[i] 131 } 132 d[i] = a[i*lda+i] 133 tau[i] = taui 134 } 135 d[n-1] = a[(n-1)*lda+n-1] 136 }