1 | /************************************************************************* |
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2 | Copyright (c) 1992-2007 The University of Tennessee. All rights reserved. |
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3 | |
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4 | Contributors: |
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5 | * Sergey Bochkanov (ALGLIB project). Translation from FORTRAN to |
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6 | pseudocode. |
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7 | |
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8 | See subroutines comments for additional copyrights. |
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9 | |
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10 | Redistribution and use in source and binary forms, with or without |
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11 | modification, are permitted provided that the following conditions are |
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12 | met: |
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13 | |
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14 | - Redistributions of source code must retain the above copyright |
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15 | notice, this list of conditions and the following disclaimer. |
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16 | |
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17 | - Redistributions in binary form must reproduce the above copyright |
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18 | notice, this list of conditions and the following disclaimer listed |
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19 | in this license in the documentation and/or other materials |
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20 | provided with the distribution. |
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21 | |
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22 | - Neither the name of the copyright holders nor the names of its |
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23 | contributors may be used to endorse or promote products derived from |
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24 | this software without specific prior written permission. |
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25 | |
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26 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
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27 | "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
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28 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
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29 | A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT |
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30 | OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, |
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31 | SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT |
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32 | LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, |
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33 | DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY |
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34 | THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
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35 | (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
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36 | OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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37 | *************************************************************************/ |
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38 | |
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39 | #ifndef _qr_h |
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40 | #define _qr_h |
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41 | |
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42 | #include "ap.h" |
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43 | #include "amp.h" |
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44 | #include "reflections.h" |
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45 | namespace qr |
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46 | { |
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47 | template<unsigned int Precision> |
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48 | void rmatrixqr(ap::template_2d_array< amp::ampf<Precision> >& a, |
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49 | int m, |
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50 | int n, |
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51 | ap::template_1d_array< amp::ampf<Precision> >& tau); |
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52 | template<unsigned int Precision> |
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53 | void rmatrixqrunpackq(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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54 | int m, |
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55 | int n, |
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56 | const ap::template_1d_array< amp::ampf<Precision> >& tau, |
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57 | int qcolumns, |
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58 | ap::template_2d_array< amp::ampf<Precision> >& q); |
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59 | template<unsigned int Precision> |
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60 | void rmatrixqrunpackr(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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61 | int m, |
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62 | int n, |
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63 | ap::template_2d_array< amp::ampf<Precision> >& r); |
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64 | template<unsigned int Precision> |
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65 | void qrdecomposition(ap::template_2d_array< amp::ampf<Precision> >& a, |
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66 | int m, |
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67 | int n, |
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68 | ap::template_1d_array< amp::ampf<Precision> >& tau); |
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69 | template<unsigned int Precision> |
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70 | void unpackqfromqr(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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71 | int m, |
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72 | int n, |
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73 | const ap::template_1d_array< amp::ampf<Precision> >& tau, |
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74 | int qcolumns, |
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75 | ap::template_2d_array< amp::ampf<Precision> >& q); |
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76 | template<unsigned int Precision> |
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77 | void qrdecompositionunpacked(ap::template_2d_array< amp::ampf<Precision> > a, |
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78 | int m, |
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79 | int n, |
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80 | ap::template_2d_array< amp::ampf<Precision> >& q, |
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81 | ap::template_2d_array< amp::ampf<Precision> >& r); |
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82 | |
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83 | |
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84 | /************************************************************************* |
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85 | QR decomposition of a rectangular matrix of size MxN |
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86 | |
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87 | Input parameters: |
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88 | A - matrix A whose indexes range within [0..M-1, 0..N-1]. |
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89 | M - number of rows in matrix A. |
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90 | N - number of columns in matrix A. |
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91 | |
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92 | Output parameters: |
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93 | A - matrices Q and R in compact form (see below). |
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94 | Tau - array of scalar factors which are used to form |
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95 | matrix Q. Array whose index ranges within [0.. Min(M-1,N-1)]. |
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96 | |
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97 | Matrix A is represented as A = QR, where Q is an orthogonal matrix of size |
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98 | MxM, R - upper triangular (or upper trapezoid) matrix of size M x N. |
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99 | |
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100 | The elements of matrix R are located on and above the main diagonal of |
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101 | matrix A. The elements which are located in Tau array and below the main |
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102 | diagonal of matrix A are used to form matrix Q as follows: |
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103 | |
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104 | Matrix Q is represented as a product of elementary reflections |
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105 | |
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106 | Q = H(0)*H(2)*...*H(k-1), |
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107 | |
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108 | where k = min(m,n), and each H(i) is in the form |
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109 | |
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110 | H(i) = 1 - tau * v * (v^T) |
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111 | |
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112 | where tau is a scalar stored in Tau[I]; v - real vector, |
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113 | so that v(0:i-1) = 0, v(i) = 1, v(i+1:m-1) stored in A(i+1:m-1,i). |
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114 | |
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115 | -- LAPACK routine (version 3.0) -- |
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116 | Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., |
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117 | Courant Institute, Argonne National Lab, and Rice University |
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118 | February 29, 1992. |
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119 | Translation from FORTRAN to pseudocode (AlgoPascal) |
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120 | by Sergey Bochkanov, ALGLIB project, 2005-2007. |
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121 | *************************************************************************/ |
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122 | template<unsigned int Precision> |
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123 | void rmatrixqr(ap::template_2d_array< amp::ampf<Precision> >& a, |
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124 | int m, |
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125 | int n, |
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126 | ap::template_1d_array< amp::ampf<Precision> >& tau) |
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127 | { |
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128 | ap::template_1d_array< amp::ampf<Precision> > work; |
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129 | ap::template_1d_array< amp::ampf<Precision> > t; |
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130 | int i; |
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131 | int k; |
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132 | int minmn; |
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133 | amp::ampf<Precision> tmp; |
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134 | |
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135 | |
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136 | if( m<=0 || n<=0 ) |
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137 | { |
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138 | return; |
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139 | } |
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140 | minmn = ap::minint(m, n); |
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141 | work.setbounds(0, n-1); |
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142 | t.setbounds(1, m); |
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143 | tau.setbounds(0, minmn-1); |
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144 | |
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145 | // |
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146 | // Test the input arguments |
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147 | // |
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148 | k = minmn; |
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149 | for(i=0; i<=k-1; i++) |
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150 | { |
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151 | |
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152 | // |
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153 | // Generate elementary reflector H(i) to annihilate A(i+1:m,i) |
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154 | // |
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155 | ap::vmove(t.getvector(1, m-i), a.getcolumn(i, i, m-1)); |
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156 | reflections::generatereflection<Precision>(t, m-i, tmp); |
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157 | tau(i) = tmp; |
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158 | ap::vmove(a.getcolumn(i, i, m-1), t.getvector(1, m-i)); |
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159 | t(1) = 1; |
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160 | if( i<n ) |
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161 | { |
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162 | |
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163 | // |
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164 | // Apply H(i) to A(i:m-1,i+1:n-1) from the left |
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165 | // |
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166 | reflections::applyreflectionfromtheleft<Precision>(a, tau(i), t, i, m-1, i+1, n-1, work); |
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167 | } |
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168 | } |
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169 | } |
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170 | |
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171 | |
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172 | /************************************************************************* |
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173 | Partial unpacking of matrix Q from the QR decomposition of a matrix A |
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174 | |
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175 | Input parameters: |
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176 | A - matrices Q and R in compact form. |
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177 | Output of RMatrixQR subroutine. |
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178 | M - number of rows in given matrix A. M>=0. |
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179 | N - number of columns in given matrix A. N>=0. |
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180 | Tau - scalar factors which are used to form Q. |
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181 | Output of the RMatrixQR subroutine. |
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182 | QColumns - required number of columns of matrix Q. M>=QColumns>=0. |
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183 | |
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184 | Output parameters: |
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185 | Q - first QColumns columns of matrix Q. |
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186 | Array whose indexes range within [0..M-1, 0..QColumns-1]. |
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187 | If QColumns=0, the array remains unchanged. |
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188 | |
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189 | -- ALGLIB -- |
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190 | Copyright 2005 by Bochkanov Sergey |
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191 | *************************************************************************/ |
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192 | template<unsigned int Precision> |
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193 | void rmatrixqrunpackq(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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194 | int m, |
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195 | int n, |
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196 | const ap::template_1d_array< amp::ampf<Precision> >& tau, |
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197 | int qcolumns, |
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198 | ap::template_2d_array< amp::ampf<Precision> >& q) |
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199 | { |
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200 | int i; |
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201 | int j; |
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202 | int k; |
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203 | int minmn; |
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204 | ap::template_1d_array< amp::ampf<Precision> > v; |
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205 | ap::template_1d_array< amp::ampf<Precision> > work; |
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206 | |
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207 | |
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208 | ap::ap_error::make_assertion(qcolumns<=m); |
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209 | if( m<=0 || n<=0 || qcolumns<=0 ) |
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210 | { |
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211 | return; |
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212 | } |
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213 | |
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214 | // |
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215 | // init |
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216 | // |
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217 | minmn = ap::minint(m, n); |
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218 | k = ap::minint(minmn, qcolumns); |
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219 | q.setbounds(0, m-1, 0, qcolumns-1); |
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220 | v.setbounds(1, m); |
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221 | work.setbounds(0, qcolumns-1); |
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222 | for(i=0; i<=m-1; i++) |
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223 | { |
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224 | for(j=0; j<=qcolumns-1; j++) |
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225 | { |
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226 | if( i==j ) |
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227 | { |
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228 | q(i,j) = 1; |
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229 | } |
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230 | else |
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231 | { |
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232 | q(i,j) = 0; |
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233 | } |
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234 | } |
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235 | } |
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236 | |
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237 | // |
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238 | // unpack Q |
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239 | // |
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240 | for(i=k-1; i>=0; i--) |
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241 | { |
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242 | |
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243 | // |
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244 | // Apply H(i) |
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245 | // |
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246 | ap::vmove(v.getvector(1, m-i), a.getcolumn(i, i, m-1)); |
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247 | v(1) = 1; |
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248 | reflections::applyreflectionfromtheleft<Precision>(q, tau(i), v, i, m-1, 0, qcolumns-1, work); |
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249 | } |
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250 | } |
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251 | |
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252 | |
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253 | /************************************************************************* |
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254 | Unpacking of matrix R from the QR decomposition of a matrix A |
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255 | |
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256 | Input parameters: |
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257 | A - matrices Q and R in compact form. |
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258 | Output of RMatrixQR subroutine. |
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259 | M - number of rows in given matrix A. M>=0. |
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260 | N - number of columns in given matrix A. N>=0. |
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261 | |
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262 | Output parameters: |
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263 | R - matrix R, array[0..M-1, 0..N-1]. |
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264 | |
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265 | -- ALGLIB -- |
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266 | Copyright 2005 by Bochkanov Sergey |
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267 | *************************************************************************/ |
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268 | template<unsigned int Precision> |
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269 | void rmatrixqrunpackr(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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270 | int m, |
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271 | int n, |
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272 | ap::template_2d_array< amp::ampf<Precision> >& r) |
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273 | { |
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274 | int i; |
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275 | int k; |
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276 | |
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277 | |
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278 | if( m<=0 || n<=0 ) |
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279 | { |
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280 | return; |
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281 | } |
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282 | k = ap::minint(m, n); |
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283 | r.setbounds(0, m-1, 0, n-1); |
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284 | for(i=0; i<=n-1; i++) |
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285 | { |
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286 | r(0,i) = 0; |
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287 | } |
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288 | for(i=1; i<=m-1; i++) |
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289 | { |
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290 | ap::vmove(r.getrow(i, 0, n-1), r.getrow(0, 0, n-1)); |
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291 | } |
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292 | for(i=0; i<=k-1; i++) |
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293 | { |
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294 | ap::vmove(r.getrow(i, i, n-1), a.getrow(i, i, n-1)); |
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295 | } |
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296 | } |
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297 | |
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298 | |
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299 | /************************************************************************* |
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300 | Obsolete 1-based subroutine. See RMatrixQR for 0-based replacement. |
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301 | *************************************************************************/ |
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302 | template<unsigned int Precision> |
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303 | void qrdecomposition(ap::template_2d_array< amp::ampf<Precision> >& a, |
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304 | int m, |
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305 | int n, |
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306 | ap::template_1d_array< amp::ampf<Precision> >& tau) |
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307 | { |
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308 | ap::template_1d_array< amp::ampf<Precision> > work; |
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309 | ap::template_1d_array< amp::ampf<Precision> > t; |
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310 | int i; |
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311 | int k; |
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312 | int mmip1; |
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313 | int minmn; |
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314 | amp::ampf<Precision> tmp; |
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315 | |
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316 | |
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317 | minmn = ap::minint(m, n); |
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318 | work.setbounds(1, n); |
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319 | t.setbounds(1, m); |
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320 | tau.setbounds(1, minmn); |
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321 | |
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322 | // |
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323 | // Test the input arguments |
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324 | // |
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325 | k = ap::minint(m, n); |
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326 | for(i=1; i<=k; i++) |
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327 | { |
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328 | |
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329 | // |
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330 | // Generate elementary reflector H(i) to annihilate A(i+1:m,i) |
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331 | // |
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332 | mmip1 = m-i+1; |
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333 | ap::vmove(t.getvector(1, mmip1), a.getcolumn(i, i, m)); |
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334 | reflections::generatereflection<Precision>(t, mmip1, tmp); |
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335 | tau(i) = tmp; |
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336 | ap::vmove(a.getcolumn(i, i, m), t.getvector(1, mmip1)); |
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337 | t(1) = 1; |
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338 | if( i<n ) |
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339 | { |
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340 | |
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341 | // |
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342 | // Apply H(i) to A(i:m,i+1:n) from the left |
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343 | // |
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344 | reflections::applyreflectionfromtheleft<Precision>(a, tau(i), t, i, m, i+1, n, work); |
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345 | } |
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346 | } |
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347 | } |
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348 | |
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349 | |
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350 | /************************************************************************* |
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351 | Obsolete 1-based subroutine. See RMatrixQRUnpackQ for 0-based replacement. |
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352 | *************************************************************************/ |
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353 | template<unsigned int Precision> |
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354 | void unpackqfromqr(const ap::template_2d_array< amp::ampf<Precision> >& a, |
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355 | int m, |
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356 | int n, |
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357 | const ap::template_1d_array< amp::ampf<Precision> >& tau, |
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358 | int qcolumns, |
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359 | ap::template_2d_array< amp::ampf<Precision> >& q) |
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360 | { |
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361 | int i; |
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362 | int j; |
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363 | int k; |
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364 | int minmn; |
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365 | ap::template_1d_array< amp::ampf<Precision> > v; |
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366 | ap::template_1d_array< amp::ampf<Precision> > work; |
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367 | int vm; |
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368 | |
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369 | |
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370 | ap::ap_error::make_assertion(qcolumns<=m); |
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371 | if( m==0 || n==0 || qcolumns==0 ) |
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372 | { |
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373 | return; |
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374 | } |
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375 | |
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376 | // |
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377 | // init |
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378 | // |
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379 | minmn = ap::minint(m, n); |
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380 | k = ap::minint(minmn, qcolumns); |
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381 | q.setbounds(1, m, 1, qcolumns); |
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382 | v.setbounds(1, m); |
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383 | work.setbounds(1, qcolumns); |
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384 | for(i=1; i<=m; i++) |
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385 | { |
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386 | for(j=1; j<=qcolumns; j++) |
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387 | { |
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388 | if( i==j ) |
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389 | { |
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390 | q(i,j) = 1; |
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391 | } |
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392 | else |
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393 | { |
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394 | q(i,j) = 0; |
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395 | } |
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396 | } |
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397 | } |
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398 | |
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399 | // |
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400 | // unpack Q |
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401 | // |
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402 | for(i=k; i>=1; i--) |
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403 | { |
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404 | |
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405 | // |
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406 | // Apply H(i) |
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407 | // |
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408 | vm = m-i+1; |
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409 | ap::vmove(v.getvector(1, vm), a.getcolumn(i, i, m)); |
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410 | v(1) = 1; |
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411 | reflections::applyreflectionfromtheleft<Precision>(q, tau(i), v, i, m, 1, qcolumns, work); |
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412 | } |
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413 | } |
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414 | |
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415 | |
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416 | /************************************************************************* |
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417 | Obsolete 1-based subroutine. See RMatrixQR for 0-based replacement. |
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418 | *************************************************************************/ |
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419 | template<unsigned int Precision> |
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420 | void qrdecompositionunpacked(ap::template_2d_array< amp::ampf<Precision> > a, |
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421 | int m, |
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422 | int n, |
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423 | ap::template_2d_array< amp::ampf<Precision> >& q, |
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424 | ap::template_2d_array< amp::ampf<Precision> >& r) |
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425 | { |
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426 | int i; |
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427 | int k; |
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428 | ap::template_1d_array< amp::ampf<Precision> > tau; |
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429 | ap::template_1d_array< amp::ampf<Precision> > work; |
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430 | ap::template_1d_array< amp::ampf<Precision> > v; |
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431 | |
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432 | |
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433 | k = ap::minint(m, n); |
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434 | if( n<=0 ) |
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435 | { |
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436 | return; |
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437 | } |
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438 | work.setbounds(1, m); |
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439 | v.setbounds(1, m); |
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440 | q.setbounds(1, m, 1, m); |
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441 | r.setbounds(1, m, 1, n); |
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442 | |
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443 | // |
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444 | // QRDecomposition |
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445 | // |
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446 | qrdecomposition<Precision>(a, m, n, tau); |
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447 | |
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448 | // |
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449 | // R |
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450 | // |
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451 | for(i=1; i<=n; i++) |
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452 | { |
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453 | r(1,i) = 0; |
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454 | } |
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455 | for(i=2; i<=m; i++) |
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456 | { |
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457 | ap::vmove(r.getrow(i, 1, n), r.getrow(1, 1, n)); |
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458 | } |
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459 | for(i=1; i<=k; i++) |
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460 | { |
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461 | ap::vmove(r.getrow(i, i, n), a.getrow(i, i, n)); |
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462 | } |
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463 | |
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464 | // |
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465 | // Q |
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466 | // |
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467 | unpackqfromqr<Precision>(a, m, n, tau, m, q); |
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468 | } |
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469 | } // namespace |
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470 | |
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471 | #endif |
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