Mercurial > hg > octave-lyh
annotate src/DLD-FUNCTIONS/svd.cc @ 10185:455759a5fcbe
fix norm and svd on empty matrices
author | Jaroslav Hajek <highegg@gmail.com> |
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date | Fri, 22 Jan 2010 12:37:03 +0100 |
parents | d0ce5e973937 |
children | 3ce0c530a9c9 |
rev | line source |
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2928 | 1 /* |
2 | |
8920 | 3 Copyright (C) 1996, 1997, 1999, 2000, 2003, 2005, 2006, 2007, 2008, 2009 |
7017 | 4 John W. Eaton |
2928 | 5 |
6 This file is part of Octave. | |
7 | |
8 Octave is free software; you can redistribute it and/or modify it | |
9 under the terms of the GNU General Public License as published by the | |
7016 | 10 Free Software Foundation; either version 3 of the License, or (at your |
11 option) any later version. | |
2928 | 12 |
13 Octave is distributed in the hope that it will be useful, but WITHOUT | |
14 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
15 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
16 for more details. | |
17 | |
18 You should have received a copy of the GNU General Public License | |
7016 | 19 along with Octave; see the file COPYING. If not, see |
20 <http://www.gnu.org/licenses/>. | |
2928 | 21 |
22 */ | |
23 | |
24 #ifdef HAVE_CONFIG_H | |
25 #include <config.h> | |
26 #endif | |
27 | |
28 #include "CmplxSVD.h" | |
29 #include "dbleSVD.h" | |
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30 #include "fCmplxSVD.h" |
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31 #include "floatSVD.h" |
2928 | 32 |
33 #include "defun-dld.h" | |
34 #include "error.h" | |
35 #include "gripes.h" | |
36 #include "oct-obj.h" | |
37 #include "pr-output.h" | |
38 #include "utils.h" | |
39 | |
40 DEFUN_DLD (svd, args, nargout, | |
3548 | 41 "-*- texinfo -*-\n\ |
3372 | 42 @deftypefn {Loadable Function} {@var{s} =} svd (@var{a})\n\ |
43 @deftypefnx {Loadable Function} {[@var{u}, @var{s}, @var{v}] =} svd (@var{a})\n\ | |
44 @cindex singular value decomposition\n\ | |
45 Compute the singular value decomposition of @var{a}\n\ | |
46 @tex\n\ | |
47 $$\n\ | |
6620 | 48 A = U S V^H\n\ |
3372 | 49 $$\n\ |
50 @end tex\n\ | |
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51 @ifnottex\n\ |
3372 | 52 \n\ |
53 @example\n\ | |
6620 | 54 A = U*S*V'\n\ |
3372 | 55 @end example\n\ |
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56 @end ifnottex\n\ |
3372 | 57 \n\ |
58 The function @code{svd} normally returns the vector of singular values.\n\ | |
59 If asked for three return values, it computes\n\ | |
60 @tex\n\ | |
61 $U$, $S$, and $V$.\n\ | |
62 @end tex\n\ | |
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63 @ifnottex\n\ |
3372 | 64 U, S, and V.\n\ |
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65 @end ifnottex\n\ |
3372 | 66 For example,\n\ |
67 \n\ | |
68 @example\n\ | |
69 svd (hilb (3))\n\ | |
70 @end example\n\ | |
71 \n\ | |
72 @noindent\n\ | |
73 returns\n\ | |
2928 | 74 \n\ |
3372 | 75 @example\n\ |
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76 @group\n\ |
3372 | 77 ans =\n\ |
78 \n\ | |
79 1.4083189\n\ | |
80 0.1223271\n\ | |
81 0.0026873\n\ | |
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82 @end group\n\ |
3372 | 83 @end example\n\ |
84 \n\ | |
85 @noindent\n\ | |
86 and\n\ | |
87 \n\ | |
88 @example\n\ | |
89 [u, s, v] = svd (hilb (3))\n\ | |
90 @end example\n\ | |
91 \n\ | |
92 @noindent\n\ | |
93 returns\n\ | |
94 \n\ | |
95 @example\n\ | |
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96 @group\n\ |
3372 | 97 u =\n\ |
2928 | 98 \n\ |
3372 | 99 -0.82704 0.54745 0.12766\n\ |
100 -0.45986 -0.52829 -0.71375\n\ | |
101 -0.32330 -0.64901 0.68867\n\ | |
102 \n\ | |
103 s =\n\ | |
104 \n\ | |
105 1.40832 0.00000 0.00000\n\ | |
106 0.00000 0.12233 0.00000\n\ | |
107 0.00000 0.00000 0.00269\n\ | |
108 \n\ | |
109 v =\n\ | |
110 \n\ | |
111 -0.82704 0.54745 0.12766\n\ | |
112 -0.45986 -0.52829 -0.71375\n\ | |
113 -0.32330 -0.64901 0.68867\n\ | |
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114 @end group\n\ |
3372 | 115 @end example\n\ |
116 \n\ | |
117 If given a second argument, @code{svd} returns an economy-sized\n\ | |
118 decomposition, eliminating the unnecessary rows or columns of @var{u} or\n\ | |
119 @var{v}.\n\ | |
120 @end deftypefn") | |
2928 | 121 { |
122 octave_value_list retval; | |
123 | |
124 int nargin = args.length (); | |
125 | |
126 if (nargin < 1 || nargin > 2 || nargout == 2 || nargout > 3) | |
127 { | |
5823 | 128 print_usage (); |
2928 | 129 return retval; |
130 } | |
131 | |
132 octave_value arg = args(0); | |
133 | |
5275 | 134 octave_idx_type nr = arg.rows (); |
135 octave_idx_type nc = arg.columns (); | |
2928 | 136 |
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137 if (arg.ndims () != 2) |
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138 { |
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139 error ("svd: only valid for matrices"); |
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140 return retval; |
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141 } |
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142 |
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143 bool isfloat = arg.is_single_type (); |
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144 |
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145 SVD::type type = ((nargout == 0 || nargout == 1) |
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146 ? SVD::sigma_only |
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147 : (nargin == 2) ? SVD::economy : SVD::std); |
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148 |
4478 | 149 if (nr == 0 || nc == 0) |
2928 | 150 { |
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151 if (isfloat) |
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152 { |
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153 switch (type) |
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154 { |
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155 case SVD::std: |
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156 retval(2) = FloatDiagMatrix (nc, nc, 1.0f); |
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157 retval(1) = FloatMatrix (nr, nc); |
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158 retval(0) = FloatDiagMatrix (nr, nr, 1.0f); |
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159 break; |
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160 case SVD::economy: |
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161 retval(2) = FloatDiagMatrix (0, nc, 1.0f); |
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162 retval(1) = FloatMatrix (0, 0); |
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163 retval(0) = FloatDiagMatrix (nr, 0, 1.0f); |
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164 break; |
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165 case SVD::sigma_only: default: |
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166 retval(0) = FloatMatrix (0, 1); |
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167 break; |
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168 } |
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169 } |
4478 | 170 else |
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171 { |
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172 switch (type) |
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173 { |
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174 case SVD::std: |
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175 retval(2) = DiagMatrix (nc, nc, 1.0); |
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176 retval(1) = Matrix (nr, nc); |
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177 retval(0) = DiagMatrix (nr, nr, 1.0); |
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178 break; |
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179 case SVD::economy: |
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180 retval(2) = DiagMatrix (0, nc, 1.0); |
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181 retval(1) = Matrix (0, 0); |
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182 retval(0) = DiagMatrix (nr, 0, 1.0); |
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183 break; |
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184 case SVD::sigma_only: default: |
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185 retval(0) = Matrix (0, 1); |
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186 break; |
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187 } |
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188 } |
2928 | 189 } |
190 else | |
191 { | |
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192 if (isfloat) |
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193 { |
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194 if (arg.is_real_type ()) |
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195 { |
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196 FloatMatrix tmp = arg.float_matrix_value (); |
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197 |
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198 if (! error_state) |
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199 { |
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200 if (tmp.any_element_is_inf_or_nan ()) |
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201 { |
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202 error ("svd: cannot take SVD of matrix containing Inf or NaN values"); |
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203 return retval; |
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204 } |
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206 FloatSVD result (tmp, type); |
4478 | 207 |
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208 FloatDiagMatrix sigma = result.singular_values (); |
4478 | 209 |
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210 if (nargout == 0 || nargout == 1) |
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211 { |
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212 retval(0) = sigma.diag (); |
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213 } |
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214 else |
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215 { |
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216 retval(2) = result.right_singular_matrix (); |
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217 retval(1) = sigma; |
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218 retval(0) = result.left_singular_matrix (); |
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219 } |
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220 } |
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221 } |
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222 else if (arg.is_complex_type ()) |
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223 { |
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224 FloatComplexMatrix ctmp = arg.float_complex_matrix_value (); |
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226 if (! error_state) |
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227 { |
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228 if (ctmp.any_element_is_inf_or_nan ()) |
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229 { |
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230 error ("svd: cannot take SVD of matrix containing Inf or NaN values"); |
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231 return retval; |
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232 } |
4478 | 233 |
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234 FloatComplexSVD result (ctmp, type); |
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236 FloatDiagMatrix sigma = result.singular_values (); |
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238 if (nargout == 0 || nargout == 1) |
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239 { |
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240 retval(0) = sigma.diag (); |
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241 } |
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242 else |
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243 { |
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244 retval(2) = result.right_singular_matrix (); |
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245 retval(1) = sigma; |
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246 retval(0) = result.left_singular_matrix (); |
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247 } |
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248 } |
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249 } |
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250 } |
4478 | 251 else |
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252 { |
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253 if (arg.is_real_type ()) |
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254 { |
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255 Matrix tmp = arg.matrix_value (); |
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256 |
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257 if (! error_state) |
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258 { |
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259 if (tmp.any_element_is_inf_or_nan ()) |
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260 { |
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261 error ("svd: cannot take SVD of matrix containing Inf or NaN values"); |
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262 return retval; |
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263 } |
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264 |
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265 SVD result (tmp, type); |
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266 |
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267 DiagMatrix sigma = result.singular_values (); |
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268 |
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269 if (nargout == 0 || nargout == 1) |
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270 { |
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271 retval(0) = sigma.diag (); |
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272 } |
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273 else |
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274 { |
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275 retval(2) = result.right_singular_matrix (); |
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276 retval(1) = sigma; |
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277 retval(0) = result.left_singular_matrix (); |
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278 } |
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279 } |
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280 } |
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281 else if (arg.is_complex_type ()) |
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282 { |
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283 ComplexMatrix ctmp = arg.complex_matrix_value (); |
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284 |
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285 if (! error_state) |
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286 { |
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287 if (ctmp.any_element_is_inf_or_nan ()) |
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288 { |
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289 error ("svd: cannot take SVD of matrix containing Inf or NaN values"); |
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290 return retval; |
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291 } |
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292 |
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293 ComplexSVD result (ctmp, type); |
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294 |
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295 DiagMatrix sigma = result.singular_values (); |
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296 |
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297 if (nargout == 0 || nargout == 1) |
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298 { |
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299 retval(0) = sigma.diag (); |
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300 } |
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301 else |
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302 { |
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303 retval(2) = result.right_singular_matrix (); |
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304 retval(1) = sigma; |
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305 retval(0) = result.left_singular_matrix (); |
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306 } |
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307 } |
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308 } |
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309 else |
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310 { |
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311 gripe_wrong_type_arg ("svd", arg); |
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312 return retval; |
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313 } |
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314 } |
2928 | 315 } |
316 | |
317 return retval; | |
318 } | |
319 | |
320 /* | |
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321 |
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322 %!assert(svd ([1, 2; 2, 1]), [3; 1], sqrt (eps)); |
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323 |
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324 %!test |
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325 %! [u, s, v] = svd ([1, 2; 2, 1]); |
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326 %! x = 1 / sqrt (2); |
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327 %! assert (u, [-x, -x; -x, x], sqrt (eps)); |
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328 %! assert (s, [3, 0; 0, 1], sqrt (eps)); |
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329 %! assert (v, [-x, x; -x, -x], sqrt (eps)); |
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330 |
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331 %!test |
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332 %! a = [1, 2, 3; 4, 5, 6]; |
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333 %! [u, s, v] = svd (a); |
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334 %! assert (u * s * v', a, sqrt (eps)); |
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335 |
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336 %!test |
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337 %! a = [1, 2; 3, 4; 5, 6]; |
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338 %! [u, s, v] = svd (a); |
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339 %! assert (u * s * v', a, sqrt (eps)); |
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340 |
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341 %!test |
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342 %! a = [1, 2, 3; 4, 5, 6]; |
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343 %! [u, s, v] = svd (a, 1); |
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344 %! assert (u * s * v', a, sqrt (eps)); |
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345 |
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346 %!test |
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347 %! a = [1, 2; 3, 4; 5, 6]; |
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348 %! [u, s, v] = svd (a, 1); |
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349 %! assert (u * s * v', a, sqrt (eps)); |
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350 |
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351 %!assert(svd (single([1, 2; 2, 1])), single([3; 1]), sqrt (eps('single'))); |
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352 |
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353 %!test |
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354 %! [u, s, v] = svd (single([1, 2; 2, 1])); |
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355 %! x = single (1 / sqrt (2)); |
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356 %! assert (u, [-x, -x; -x, x], sqrt (eps('single'))); |
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357 %! assert (s, single([3, 0; 0, 1]), sqrt (eps('single'))); |
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358 %! assert (v, [-x, x; -x, -x], sqrt (eps('single'))); |
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359 |
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360 %!test |
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361 %! a = single([1, 2, 3; 4, 5, 6]); |
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362 %! [u, s, v] = svd (a); |
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363 %! assert (u * s * v', a, sqrt (eps('single'))); |
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364 |
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365 %!test |
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366 %! a = single([1, 2; 3, 4; 5, 6]); |
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367 %! [u, s, v] = svd (a); |
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368 %! assert (u * s * v', a, sqrt (eps('single'))); |
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369 |
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370 %!test |
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371 %! a = single([1, 2, 3; 4, 5, 6]); |
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372 %! [u, s, v] = svd (a, 1); |
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373 %! assert (u * s * v', a, sqrt (eps('single'))); |
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374 |
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375 %!test |
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376 %! a = single([1, 2; 3, 4; 5, 6]); |
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Second set of single precision test code and fix of resulting bugs
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377 %! [u, s, v] = svd (a, 1); |
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378 %! assert (u * s * v', a, sqrt (eps('single'))); |
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379 |
10185
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Jaroslav Hajek <highegg@gmail.com>
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380 %!test |
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381 %! a = zeros (0, 5); |
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382 %! [u, s, v] = svd (a); |
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383 %! assert (size (u), [0, 0]); |
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384 %! assert (size (s), [0, 5]); |
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385 %! assert (size (v), [5, 5]); |
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386 |
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387 %!test |
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388 %! a = zeros (5, 0); |
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389 %! [u, s, v] = svd (a, 1); |
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390 %! assert (size (u), [5, 0]); |
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parents:
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391 %! assert (size (s), [0, 0]); |
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parents:
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392 %! assert (size (v), [0, 0]); |
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393 |
7814
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394 %!error <Invalid call to svd.*> svd (); |
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395 %!error <Invalid call to svd.*> svd ([1, 2; 4, 5], 2, 3); |
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396 %!error <Invalid call to svd.*> [u, v] = svd ([1, 2; 3, 4]); |
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397 |
2928 | 398 */ |