Mercurial > octave
annotate libinterp/corefcn/schur.cc @ 21266:e69eaee28737
make better use of templates for Schur decomposition
* liboctave/numeric/schur.h, liboctave/numeric/schur.cc:
New files generated from SCHUR.h, SCHUR.cc, CmplxSCHUR.h,
CmplxSCHUR.cc, dbleSCHUR.h, dbleSCHUR.cc, fCmplxSCHUR.h,
fCmplxSCHUR.cc, floatSCHUR.h, and floatSCHUR.cc and making them
templates.
* liboctave/numeric/module.mk: Update.
* libinterp/corefcn/schur.cc, sqrtm.cc, CMatrix.cc, dMatrix.cc,
fCMatrix.cc, fMatrix.cc, mx-defs.h, mx-ext.h: Use new template classes
and header file.
author | John W. Eaton <jwe@octave.org> |
---|---|
date | Mon, 15 Feb 2016 20:06:12 -0500 |
parents | fcac5dbbf9ed |
children | 40de9f8f23a6 |
rev | line source |
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2928 | 1 /* |
2 | |
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3 Copyright (C) 1996-2015 John W. Eaton |
2928 | 4 |
5 This file is part of Octave. | |
6 | |
7 Octave is free software; you can redistribute it and/or modify it | |
8 under the terms of the GNU General Public License as published by the | |
7016 | 9 Free Software Foundation; either version 3 of the License, or (at your |
10 option) any later version. | |
2928 | 11 |
12 Octave is distributed in the hope that it will be useful, but WITHOUT | |
13 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
14 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
15 for more details. | |
16 | |
17 You should have received a copy of the GNU General Public License | |
7016 | 18 along with Octave; see the file COPYING. If not, see |
19 <http://www.gnu.org/licenses/>. | |
2928 | 20 |
21 */ | |
22 | |
23 #ifdef HAVE_CONFIG_H | |
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24 # include <config.h> |
2928 | 25 #endif |
26 | |
27 #include <string> | |
28 | |
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29 #include "schur.h" |
2928 | 30 |
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31 #include "defun.h" |
2928 | 32 #include "error.h" |
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33 #include "errwarn.h" |
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34 #include "ovl.h" |
2928 | 35 #include "utils.h" |
36 | |
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37 template <typename Matrix> |
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38 static octave_value |
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39 mark_upper_triangular (const Matrix& a) |
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40 { |
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41 octave_value retval = a; |
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42 |
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43 octave_idx_type n = a.rows (); |
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44 assert (a.columns () == n); |
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45 |
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46 const typename Matrix::element_type zero = typename Matrix::element_type (); |
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47 |
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48 for (octave_idx_type i = 0; i < n; i++) |
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49 if (a(i,i) == zero) |
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50 return retval; |
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51 |
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52 retval.matrix_type (MatrixType::Upper); |
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53 |
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54 return retval; |
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55 } |
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56 |
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57 DEFUN (schur, args, nargout, |
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58 "-*- texinfo -*-\n\ |
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59 @deftypefn {} {@var{S} =} schur (@var{A})\n\ |
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60 @deftypefnx {} {@var{S} =} schur (@var{A}, \"real\")\n\ |
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61 @deftypefnx {} {@var{S} =} schur (@var{A}, \"complex\")\n\ |
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62 @deftypefnx {} {@var{S} =} schur (@var{A}, @var{opt})\n\ |
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63 @deftypefnx {} {[@var{U}, @var{S}] =} schur (@dots{})\n\ |
3372 | 64 @cindex Schur decomposition\n\ |
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65 Compute the Schur@tie{}decomposition of @var{A}.\n\ |
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66 \n\ |
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67 The Schur@tie{}decomposition is defined as\n\ |
3372 | 68 @tex\n\ |
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69 $$\n\ |
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70 S = U^T A U\n\ |
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71 $$\n\ |
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73 @ifnottex\n\ |
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74 \n\ |
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75 @example\n\ |
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76 @code{@var{S} = @var{U}' * @var{A} * @var{U}}\n\ |
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77 @end example\n\ |
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78 \n\ |
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79 @end ifnottex\n\ |
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80 where @var{U} is a unitary matrix\n\ |
3372 | 81 @tex\n\ |
82 ($U^T U$ is identity)\n\ | |
83 @end tex\n\ | |
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84 @ifnottex\n\ |
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85 (@code{@var{U}'* @var{U}} is identity)\n\ |
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86 @end ifnottex\n\ |
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87 and @var{S} is upper triangular. The eigenvalues of @var{A} (and @var{S})\n\ |
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88 are the diagonal elements of @var{S}. If the matrix @var{A} is real, then\n\ |
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89 the real Schur@tie{}decomposition is computed, in which the matrix @var{U}\n\ |
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90 is orthogonal and @var{S} is block upper triangular with blocks of size at\n\ |
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91 most\n\ |
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93 $2 \\times 2$\n\ |
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95 @ifnottex\n\ |
3372 | 96 @code{2 x 2}\n\ |
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97 @end ifnottex\n\ |
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98 along the diagonal. The diagonal elements of @var{S}\n\ |
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100 @tex\n\ | |
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101 $2 \\times 2$\n\ |
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103 @ifnottex\n\ |
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105 @end ifnottex\n\ |
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106 blocks, when appropriate) are the eigenvalues of @var{A} and @var{S}.\n\ |
2928 | 107 \n\ |
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108 The default for real matrices is a real Schur@tie{}decomposition.\n\ |
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109 A complex decomposition may be forced by passing the flag\n\ |
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110 @qcode{\"complex\"}.\n\ |
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111 \n\ |
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112 The eigenvalues are optionally ordered along the diagonal according to the\n\ |
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113 value of @var{opt}. @code{@var{opt} = \"a\"} indicates that all eigenvalues\n\ |
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114 with negative real parts should be moved to the leading block of @var{S}\n\ |
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115 (used in @code{are}), @code{@var{opt} = \"d\"} indicates that all\n\ |
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116 eigenvalues with magnitude less than one should be moved to the leading\n\ |
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117 block of @var{S} (used in @code{dare}), and @code{@var{opt} = \"u\"}, the\n\ |
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118 default, indicates that no ordering of eigenvalues should occur. The\n\ |
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119 leading @var{k} columns of @var{U} always span the @var{A}-invariant\n\ |
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120 subspace corresponding to the @var{k} leading eigenvalues of @var{S}.\n\ |
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121 \n\ |
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122 The Schur@tie{}decomposition is used to compute eigenvalues of a square\n\ |
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123 matrix, and has applications in the solution of algebraic Riccati equations\n\ |
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124 in control (see @code{are} and @code{dare}).\n\ |
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125 @seealso{rsf2csf, ordschur, lu, chol, hess, qr, qz, svd}\n\ |
3372 | 126 @end deftypefn") |
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128 int nargin = args.length (); | |
129 | |
130 if (nargin < 1 || nargin > 2 || nargout > 2) | |
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131 print_usage (); |
2928 | 132 |
133 octave_value arg = args(0); | |
134 | |
3523 | 135 std::string ord; |
2928 | 136 if (nargin == 2) |
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137 ord = args(1).xstring_value ("schur: second argument must be a string"); |
2928 | 138 |
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139 bool force_complex = false; |
2928 | 140 |
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141 if (ord == "real") |
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142 { |
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143 ord = ""; |
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144 } |
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145 else if (ord == "complex") |
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146 { |
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147 force_complex = true; |
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148 ord = ""; |
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149 } |
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150 else |
2928 | 151 { |
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152 char ord_char = ord.empty () ? 'U' : ord[0]; |
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153 |
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154 if (ord_char != 'U' && ord_char != 'A' && ord_char != 'D' |
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155 && ord_char != 'u' && ord_char != 'a' && ord_char != 'd') |
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156 { |
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157 warning ("schur: incorrect ordered schur argument '%s'", |
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158 ord.c_str ()); |
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159 return ovl (); |
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160 } |
2928 | 161 } |
162 | |
5275 | 163 octave_idx_type nr = arg.rows (); |
164 octave_idx_type nc = arg.columns (); | |
2928 | 165 |
166 if (nr != nc) | |
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167 err_square_matrix_required ("schur", "A"); |
2928 | 168 |
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169 if (! arg.is_numeric_type ()) |
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170 err_wrong_type_arg ("schur", arg); |
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171 |
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172 octave_value_list retval; |
20892 | 173 |
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174 if (arg.is_single_type ()) |
2928 | 175 { |
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176 if (! force_complex && arg.is_real_type ()) |
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177 { |
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178 FloatMatrix tmp = arg.float_matrix_value (); |
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181 { |
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182 schur<FloatMatrix> result (tmp, ord, false); |
20892 | 183 retval = ovl (result.schur_matrix ()); |
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184 } |
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185 else |
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186 { |
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187 schur<FloatMatrix> result (tmp, ord, true); |
20892 | 188 retval = ovl (result.unitary_matrix (), |
189 result.schur_matrix ()); | |
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190 } |
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191 } |
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192 else |
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193 { |
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194 FloatComplexMatrix ctmp = arg.float_complex_matrix_value (); |
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195 |
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197 { |
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198 schur<FloatComplexMatrix> result (ctmp, ord, false); |
20892 | 199 retval = ovl (mark_upper_triangular (result.schur_matrix ())); |
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200 } |
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201 else |
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202 { |
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203 schur<FloatComplexMatrix> result (ctmp, ord, true); |
20892 | 204 retval = ovl (result.unitary_matrix (), |
205 mark_upper_triangular (result.schur_matrix ())); | |
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206 } |
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207 } |
2928 | 208 } |
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209 else |
2928 | 210 { |
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211 if (! force_complex && arg.is_real_type ()) |
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212 { |
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213 Matrix tmp = arg.matrix_value (); |
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216 { |
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217 schur<Matrix> result (tmp, ord, false); |
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219 } |
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220 else |
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221 { |
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222 schur<Matrix> result (tmp, ord, true); |
20892 | 223 retval = ovl (result.unitary_matrix (), |
224 result.schur_matrix ()); | |
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225 } |
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226 } |
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227 else |
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228 { |
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229 ComplexMatrix ctmp = arg.complex_matrix_value (); |
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230 |
20892 | 231 if (nargout <= 1) |
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232 { |
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233 schur<ComplexMatrix> result (ctmp, ord, false); |
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235 } |
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236 else |
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237 { |
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238 schur<ComplexMatrix> result (ctmp, ord, true); |
20892 | 239 retval = ovl (result.unitary_matrix (), |
240 mark_upper_triangular (result.schur_matrix ())); | |
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241 } |
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242 } |
2928 | 243 } |
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244 |
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245 return retval; |
2928 | 246 } |
247 | |
248 /* | |
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249 %!test |
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250 %! a = [1, 2, 3; 4, 5, 9; 7, 8, 6]; |
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251 %! [u, s] = schur (a); |
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252 %! assert (u' * a * u, s, sqrt (eps)); |
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253 |
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254 %!test |
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255 %! a = single ([1, 2, 3; 4, 5, 9; 7, 8, 6]); |
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256 %! [u, s] = schur (a); |
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257 %! assert (u' * a * u, s, sqrt (eps ("single"))); |
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258 |
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259 %!error schur () |
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260 %!error schur (1,2,3) |
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261 %!error [a,b,c] = schur (1) |
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262 %!error <must be a square matrix> schur ([1, 2, 3; 4, 5, 6]) |
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263 %!error <wrong type argument 'cell'> schur ({1}) |
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264 %!warning <incorrect ordered schur argument> schur ([1, 2; 3, 4], "bad_opt"); |
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265 |
2928 | 266 */ |
10822 | 267 |
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268 DEFUN (rsf2csf, args, nargout, |
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269 "-*- texinfo -*-\n\ |
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270 @deftypefn {} {[@var{U}, @var{T}] =} rsf2csf (@var{UR}, @var{TR})\n\ |
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271 Convert a real, upper quasi-triangular Schur@tie{}form @var{TR} to a complex,\n\ |
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272 upper triangular Schur@tie{}form @var{T}.\n\ |
10822 | 273 \n\ |
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274 Note that the following relations hold:\n\ |
10822 | 275 \n\ |
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276 @tex\n\ |
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277 $UR \\cdot TR \\cdot {UR}^T = U T U^{\\dagger}$ and\n\ |
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278 $U^{\\dagger} U$ is the identity matrix I.\n\ |
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279 @end tex\n\ |
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280 @ifnottex\n\ |
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281 @tcode{@var{UR} * @var{TR} * @var{UR}' = @var{U} * @var{T} * @var{U}'} and\n\ |
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282 @code{@var{U}' * @var{U}} is the identity matrix I.\n\ |
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283 @end ifnottex\n\ |
10822 | 284 \n\ |
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285 Note also that @var{U} and @var{T} are not unique.\n\ |
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286 @seealso{schur}\n\ |
10822 | 287 @end deftypefn") |
288 { | |
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289 if (args.length () != 2 || nargout > 2) |
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290 print_usage (); |
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291 |
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292 if (! args(0).is_numeric_type ()) |
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293 err_wrong_type_arg ("rsf2csf", args(0)); |
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294 if (! args(1).is_numeric_type ()) |
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295 err_wrong_type_arg ("rsf2csf", args(1)); |
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296 if (args(0).is_complex_type () || args(1).is_complex_type ()) |
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297 error ("rsf2csf: UR and TR must be real matrices"); |
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298 |
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299 if (args(0).is_single_type () || args(1).is_single_type ()) |
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300 { |
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301 FloatMatrix u = args(0).float_matrix_value (); |
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302 FloatMatrix t = args(1).float_matrix_value (); |
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303 |
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304 schur<FloatComplexMatrix> cs |
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305 = rsf2csf<FloatComplexMatrix, FloatMatrix> (t, u); |
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306 |
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307 return ovl (cs.unitary_matrix (), cs.schur_matrix ()); |
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308 } |
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309 else |
10822 | 310 { |
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311 Matrix u = args(0).matrix_value (); |
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312 Matrix t = args(1).matrix_value (); |
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313 |
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314 schur<ComplexMatrix> cs = rsf2csf<ComplexMatrix, Matrix> (t, u); |
10822 | 315 |
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316 return ovl (cs.unitary_matrix (), cs.schur_matrix ()); |
10822 | 317 } |
318 } | |
319 | |
320 /* | |
321 %!test | |
322 %! A = [1, 1, 1, 2; 1, 2, 1, 1; 1, 1, 3, 1; -2, 1, 1, 1]; | |
323 %! [u, t] = schur (A); | |
324 %! [U, T] = rsf2csf (u, t); | |
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325 %! assert (norm (u * t * u' - U * T * U'), 0, 1e-12); |
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326 %! assert (norm (A - U * T * U'), 0, 1e-12); |
10822 | 327 |
328 %!test | |
329 %! A = rand (10); | |
330 %! [u, t] = schur (A); | |
331 %! [U, T] = rsf2csf (u, t); | |
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332 %! assert (norm (tril (T, -1)), 0); |
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333 %! assert (norm (U * U'), 1, 1e-14); |
10822 | 334 |
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335 %!test |
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336 %! A = [0, 1;-1, 0]; |
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337 %! [u, t] = schur (A); |
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338 %! [U, T] = rsf2csf (u,t); |
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339 %! assert (U * T * U', A, 1e-14); |
10822 | 340 */ |