Mercurial > hg > orthanc-stone
annotate Framework/Toolbox/LinearAlgebra.cpp @ 871:4bc8d9609447
Added support for measuring tool edition in TrackerSampleApp
author | Benjamin Golinvaux <bgo@osimis.io> |
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date | Tue, 25 Jun 2019 18:17:33 +0200 |
parents | 61ba4b504e9a |
children | 32eaf4929b08 |
rev | line source |
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158 | 1 /** |
2 * Stone of Orthanc | |
3 * Copyright (C) 2012-2016 Sebastien Jodogne, Medical Physics | |
4 * Department, University Hospital of Liege, Belgium | |
439 | 5 * Copyright (C) 2017-2019 Osimis S.A., Belgium |
158 | 6 * |
7 * This program is free software: you can redistribute it and/or | |
8 * modify it under the terms of the GNU Affero General Public License | |
9 * as published by the Free Software Foundation, either version 3 of | |
10 * the License, or (at your option) any later version. | |
11 * | |
12 * This program is distributed in the hope that it will be useful, but | |
13 * WITHOUT ANY WARRANTY; without even the implied warranty of | |
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU | |
15 * Affero General Public License for more details. | |
16 * | |
17 * You should have received a copy of the GNU Affero General Public License | |
18 * along with this program. If not, see <http://www.gnu.org/licenses/>. | |
19 **/ | |
20 | |
21 | |
22 #include "LinearAlgebra.h" | |
23 | |
212
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24 #include <Core/Logging.h> |
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25 #include <Core/OrthancException.h> |
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26 #include <Core/Toolbox.h> |
158 | 27 |
28 #include <stdio.h> | |
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29 #include <boost/lexical_cast.hpp> |
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30 #include <boost/numeric/ublas/lu.hpp> |
158 | 31 |
32 namespace OrthancStone | |
33 { | |
34 namespace LinearAlgebra | |
35 { | |
36 void Print(const Vector& v) | |
37 { | |
38 for (size_t i = 0; i < v.size(); i++) | |
39 { | |
40 printf("%g\n", v[i]); | |
41 //printf("%8.2f\n", v[i]); | |
42 } | |
43 printf("\n"); | |
44 } | |
45 | |
46 | |
47 void Print(const Matrix& m) | |
48 { | |
49 for (size_t i = 0; i < m.size1(); i++) | |
50 { | |
51 for (size_t j = 0; j < m.size2(); j++) | |
52 { | |
53 printf("%g ", m(i,j)); | |
54 //printf("%8.2f ", m(i,j)); | |
55 } | |
56 printf("\n"); | |
57 } | |
58 printf("\n"); | |
59 } | |
60 | |
61 | |
62 bool ParseVector(Vector& target, | |
63 const std::string& value) | |
64 { | |
65 std::vector<std::string> items; | |
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66 Orthanc::Toolbox::TokenizeString(items, Orthanc::Toolbox::StripSpaces(value), '\\'); |
158 | 67 |
68 target.resize(items.size()); | |
69 | |
70 for (size_t i = 0; i < items.size(); i++) | |
71 { | |
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72 /** |
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73 * We try and avoid the use of "boost::lexical_cast<>" here, |
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74 * as it is very slow. As we are parsing many doubles, we |
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75 * prefer to use the standard "std::stod" function if |
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76 * available: http://www.cplusplus.com/reference/string/stod/ |
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77 **/ |
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78 |
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79 #if __cplusplus >= 201103L // Is C++11 enabled? |
158 | 80 try |
81 { | |
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82 target[i] = std::stod(items[i]); |
158 | 83 } |
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84 catch (std::exception&) |
158 | 85 { |
86 target.clear(); | |
87 return false; | |
88 } | |
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89 #else // Fallback implementation using Boost |
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90 try |
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91 { |
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92 target[i] = boost::lexical_cast<double>(items[i]); |
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93 } |
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94 catch (boost::bad_lexical_cast&) |
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95 { |
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96 target.clear(); |
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97 return false; |
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98 } |
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99 #endif |
158 | 100 } |
101 | |
102 return true; | |
103 } | |
104 | |
105 | |
106 bool ParseVector(Vector& target, | |
107 const Orthanc::DicomMap& dataset, | |
108 const Orthanc::DicomTag& tag) | |
109 { | |
110 std::string value; | |
111 return (dataset.CopyToString(value, tag, false) && | |
112 ParseVector(target, value)); | |
113 } | |
114 | |
115 | |
116 void NormalizeVector(Vector& u) | |
117 { | |
118 double norm = boost::numeric::ublas::norm_2(u); | |
119 if (!IsCloseToZero(norm)) | |
120 { | |
121 u = u / norm; | |
122 } | |
123 } | |
124 | |
125 | |
126 void CrossProduct(Vector& result, | |
127 const Vector& u, | |
128 const Vector& v) | |
129 { | |
130 if (u.size() != 3 || | |
131 v.size() != 3) | |
132 { | |
133 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); | |
134 } | |
135 | |
136 result.resize(3); | |
137 | |
138 result[0] = u[1] * v[2] - u[2] * v[1]; | |
139 result[1] = u[2] * v[0] - u[0] * v[2]; | |
140 result[2] = u[0] * v[1] - u[1] * v[0]; | |
141 } | |
142 | |
143 | |
144 void FillMatrix(Matrix& target, | |
145 size_t rows, | |
146 size_t columns, | |
147 const double values[]) | |
148 { | |
149 target.resize(rows, columns); | |
150 | |
151 size_t index = 0; | |
152 | |
153 for (size_t y = 0; y < rows; y++) | |
154 { | |
155 for (size_t x = 0; x < columns; x++, index++) | |
156 { | |
157 target(y, x) = values[index]; | |
158 } | |
159 } | |
160 } | |
161 | |
162 | |
163 void FillVector(Vector& target, | |
164 size_t size, | |
165 const double values[]) | |
166 { | |
167 target.resize(size); | |
168 | |
169 for (size_t i = 0; i < size; i++) | |
170 { | |
171 target[i] = values[i]; | |
172 } | |
173 } | |
174 | |
175 | |
176 void Convert(Matrix& target, | |
177 const Vector& source) | |
178 { | |
179 const size_t n = source.size(); | |
180 | |
181 target.resize(n, 1); | |
182 | |
183 for (size_t i = 0; i < n; i++) | |
184 { | |
185 target(i, 0) = source[i]; | |
186 } | |
187 } | |
159
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188 |
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189 |
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190 double ComputeDeterminant(const Matrix& a) |
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191 { |
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192 if (a.size1() != a.size2()) |
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193 { |
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194 LOG(ERROR) << "Determinant only exists for square matrices"; |
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195 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); |
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196 } |
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197 |
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198 // https://en.wikipedia.org/wiki/Rule_of_Sarrus |
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199 if (a.size1() == 1) |
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200 { |
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201 return a(0,0); |
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202 } |
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203 else if (a.size1() == 2) |
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204 { |
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205 return a(0,0) * a(1,1) - a(0,1) * a(1,0); |
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206 } |
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207 else if (a.size1() == 3) |
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208 { |
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209 return (a(0,0) * a(1,1) * a(2,2) + |
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210 a(0,1) * a(1,2) * a(2,0) + |
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211 a(0,2) * a(1,0) * a(2,1) - |
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212 a(2,0) * a(1,1) * a(0,2) - |
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213 a(2,1) * a(1,2) * a(0,0) - |
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214 a(2,2) * a(1,0) * a(0,1)); |
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215 } |
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216 else |
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217 { |
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218 throw Orthanc::OrthancException(Orthanc::ErrorCode_NotImplemented); |
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219 } |
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220 } |
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221 |
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222 |
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223 bool IsOrthogonalMatrix(const Matrix& q, |
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224 double threshold) |
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225 { |
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226 // https://en.wikipedia.org/wiki/Orthogonal_matrix |
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227 |
392 | 228 if (q.size1() != q.size2()) |
229 { | |
230 LOG(ERROR) << "An orthogonal matrix must be squared"; | |
231 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); | |
232 } | |
233 | |
159
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234 using namespace boost::numeric::ublas; |
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235 |
392 | 236 const Matrix check = prod(trans(q), q) - identity_matrix<double>(q.size1()); |
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237 |
160 | 238 type_traits<double>::real_type norm = norm_inf(check); |
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239 |
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240 return (norm <= threshold); |
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241 } |
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242 |
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243 |
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244 bool IsOrthogonalMatrix(const Matrix& q) |
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245 { |
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246 return IsOrthogonalMatrix(q, 10.0 * std::numeric_limits<float>::epsilon()); |
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247 } |
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248 |
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249 |
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250 bool IsRotationMatrix(const Matrix& r, |
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251 double threshold) |
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252 { |
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253 return (IsOrthogonalMatrix(r, threshold) && |
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254 IsNear(ComputeDeterminant(r), 1.0, threshold)); |
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255 } |
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256 |
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257 |
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258 bool IsRotationMatrix(const Matrix& r) |
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259 { |
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260 return IsRotationMatrix(r, 10.0 * std::numeric_limits<float>::epsilon()); |
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261 } |
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262 |
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263 |
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264 void InvertUpperTriangularMatrix(Matrix& output, |
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265 const Matrix& k) |
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266 { |
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267 if (k.size1() != k.size2()) |
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268 { |
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269 LOG(ERROR) << "Determinant only exists for square matrices"; |
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270 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); |
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271 } |
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272 |
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273 output.resize(k.size1(), k.size2()); |
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274 |
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275 for (size_t i = 1; i < k.size1(); i++) |
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276 { |
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277 for (size_t j = 0; j < i; j++) |
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278 { |
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279 if (!IsCloseToZero(k(i, j))) |
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280 { |
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281 LOG(ERROR) << "Not an upper triangular matrix"; |
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282 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); |
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283 } |
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284 |
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285 output(i, j) = 0; // The output is also upper triangular |
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286 } |
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287 } |
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288 |
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289 if (k.size1() == 3) |
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290 { |
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291 // https://math.stackexchange.com/a/1004181 |
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292 double a = k(0, 0); |
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293 double b = k(0, 1); |
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294 double c = k(0, 2); |
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295 double d = k(1, 1); |
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296 double e = k(1, 2); |
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297 double f = k(2, 2); |
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298 |
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299 if (IsCloseToZero(a) || |
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300 IsCloseToZero(d) || |
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301 IsCloseToZero(f)) |
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302 { |
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303 LOG(ERROR) << "Singular upper triangular matrix"; |
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304 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); |
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305 } |
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306 else |
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307 { |
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308 output(0, 0) = 1.0 / a; |
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309 output(0, 1) = -b / (a * d); |
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310 output(0, 2) = (b * e - c * d) / (a * f * d); |
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311 output(1, 1) = 1.0 / d; |
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312 output(1, 2) = -e / (f * d); |
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313 output(2, 2) = 1.0 / f; |
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314 } |
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315 } |
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316 else |
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317 { |
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318 throw Orthanc::OrthancException(Orthanc::ErrorCode_NotImplemented); |
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319 } |
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320 } |
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321 |
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322 |
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323 static void GetGivensComponent(double& c, |
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324 double& s, |
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325 const Matrix& a, |
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326 size_t i, |
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327 size_t j) |
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328 { |
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329 assert(i < 3 && j < 3); |
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330 |
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331 double x = a(i, i); |
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332 double y = a(i, j); |
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333 double n = sqrt(x * x + y * y); |
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334 |
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335 if (IsCloseToZero(n)) |
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336 { |
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337 c = 1; |
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338 s = 0; |
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339 } |
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340 else |
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341 { |
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342 c = x / n; |
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343 s = -y / n; |
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344 } |
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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 * This function computes the RQ decomposition of a 3x3 matrix, |
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350 * using Givens rotations. Reference: Algorithm A4.1 (page 579) of |
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351 * "Multiple View Geometry in Computer Vision" (2nd edition). The |
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352 * output matrix "Q" is a rotation matrix, and "R" is upper |
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353 * triangular. |
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354 **/ |
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355 void RQDecomposition3x3(Matrix& r, |
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356 Matrix& q, |
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357 const Matrix& a) |
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358 { |
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359 using namespace boost::numeric::ublas; |
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360 |
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361 if (a.size1() != 3 || |
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362 a.size2() != 3) |
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363 { |
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364 LOG(ERROR) << "Only applicable to a 3x3 matrix"; |
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365 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); |
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366 } |
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367 |
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368 r.resize(3, 3); |
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369 q.resize(3, 3); |
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370 |
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371 r = a; |
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372 q = identity_matrix<double>(3); |
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373 |
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374 { |
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375 // Set A(2,1) to zero |
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376 double c, s; |
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377 GetGivensComponent(c, s, r, 2, 1); |
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378 |
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379 double v[9] = { 1, 0, 0, |
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380 0, c, -s, |
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381 0, s, c }; |
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382 |
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383 Matrix g; |
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384 FillMatrix(g, 3, 3, v); |
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385 |
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386 r = prod(r, g); |
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387 q = prod(trans(g), q); |
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388 } |
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389 |
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390 |
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391 { |
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392 // Set A(2,0) to zero |
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393 double c, s; |
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394 GetGivensComponent(c, s, r, 2, 0); |
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395 |
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396 double v[9] = { c, 0, -s, |
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397 0, 1, 0, |
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398 s, 0, c }; |
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399 |
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400 Matrix g; |
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401 FillMatrix(g, 3, 3, v); |
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402 |
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403 r = prod(r, g); |
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404 q = prod(trans(g), q); |
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405 } |
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406 |
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407 |
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408 { |
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409 // Set A(1,0) to zero |
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410 double c, s; |
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411 GetGivensComponent(c, s, r, 1, 0); |
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412 |
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413 double v[9] = { c, -s, 0, |
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414 s, c, 0, |
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415 0, 0, 1 }; |
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416 |
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417 Matrix g; |
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418 FillMatrix(g, 3, 3, v); |
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419 |
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420 r = prod(r, g); |
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421 q = prod(trans(g), q); |
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422 } |
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423 |
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424 if (!IsCloseToZero(norm_inf(prod(r, q) - a)) || |
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425 !IsRotationMatrix(q) || |
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426 !IsCloseToZero(r(1, 0)) || |
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427 !IsCloseToZero(r(2, 0)) || |
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428 !IsCloseToZero(r(2, 1))) |
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429 { |
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430 throw Orthanc::OrthancException(Orthanc::ErrorCode_InternalError); |
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431 } |
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432 } |
163
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433 |
169 | 434 |
435 bool InvertMatrixUnsafe(Matrix& target, | |
436 const Matrix& source) | |
163
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437 { |
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438 if (source.size1() != source.size2()) |
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439 { |
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440 LOG(ERROR) << "Inverse only exists for square matrices"; |
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441 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); |
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442 } |
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443 |
164
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444 if (source.size1() < 4) |
163
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445 { |
164
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446 // For matrices with size below 4, use direct computations |
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447 // instead of LU decomposition |
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448 |
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449 if (source.size1() == 0) |
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450 { |
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451 // By convention, the inverse of the empty matrix, is itself the empty matrix |
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452 target.resize(0, 0); |
169 | 453 return true; |
164
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454 } |
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455 |
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456 double determinant = ComputeDeterminant(source); |
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457 |
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458 if (IsCloseToZero(determinant)) |
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459 { |
169 | 460 return false; |
164
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461 } |
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462 |
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463 double denominator = 1.0 / determinant; |
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464 |
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465 target.resize(source.size1(), source.size2()); |
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466 |
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467 if (source.size1() == 1) |
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468 { |
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469 target(0, 0) = denominator; |
169 | 470 |
471 return true; | |
164
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472 } |
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473 else if (source.size1() == 2) |
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474 { |
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475 // https://en.wikipedia.org/wiki/Invertible_matrix#Inversion_of_2_%C3%97_2_matrices |
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476 target(0, 0) = source(1, 1) * denominator; |
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477 target(0, 1) = -source(0, 1) * denominator; |
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478 target(1, 0) = -source(1, 0) * denominator; |
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479 target(1, 1) = source(0, 0) * denominator; |
169 | 480 |
481 return true; | |
164
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482 } |
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483 else if (source.size1() == 3) |
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484 { |
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485 // https://en.wikipedia.org/wiki/Invertible_matrix#Inversion_of_3_%C3%97_3_matrices |
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486 const double a = source(0, 0); |
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487 const double b = source(0, 1); |
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488 const double c = source(0, 2); |
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489 const double d = source(1, 0); |
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490 const double e = source(1, 1); |
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491 const double f = source(1, 2); |
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492 const double g = source(2, 0); |
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493 const double h = source(2, 1); |
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494 const double i = source(2, 2); |
163
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495 |
164
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496 target(0, 0) = (e * i - f * h) * denominator; |
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497 target(0, 1) = -(b * i - c * h) * denominator; |
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498 target(0, 2) = (b * f - c * e) * denominator; |
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499 target(1, 0) = -(d * i - f * g) * denominator; |
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500 target(1, 1) = (a * i - c * g) * denominator; |
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501 target(1, 2) = -(a * f - c * d) * denominator; |
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502 target(2, 0) = (d * h - e * g) * denominator; |
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503 target(2, 1) = -(a * h - b * g) * denominator; |
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504 target(2, 2) = (a * e - b * d) * denominator; |
169 | 505 |
506 return true; | |
164
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|
507 } |
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|
508 else |
432b1f812d14
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|
509 { |
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510 throw Orthanc::OrthancException(Orthanc::ErrorCode_InternalError); |
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511 } |
163
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LinearAlgebra::InvertMatrix
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512 } |
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LinearAlgebra::InvertMatrix
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|
513 else |
8c5b24892ed2
LinearAlgebra::InvertMatrix
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changeset
|
514 { |
164
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515 // General case, using LU decomposition |
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516 |
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517 Matrix a = source; // Copy the source matrix, as "lu_factorize()" modifies it |
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518 |
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519 boost::numeric::ublas::permutation_matrix<size_t> permutation(source.size1()); |
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520 |
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521 if (boost::numeric::ublas::lu_factorize(a, permutation) != 0) |
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522 { |
169 | 523 return false; |
524 } | |
525 else | |
526 { | |
527 target = boost::numeric::ublas::identity_matrix<double>(source.size1()); | |
528 lu_substitute(a, permutation, target); | |
529 return true; | |
164
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530 } |
169 | 531 } |
532 } | |
533 | |
164
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534 |
169 | 535 |
536 void InvertMatrix(Matrix& target, | |
537 const Matrix& source) | |
538 { | |
539 if (!InvertMatrixUnsafe(target, source)) | |
540 { | |
541 LOG(ERROR) << "Cannot invert singular matrix"; | |
542 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); | |
163
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543 } |
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544 } |
165
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545 |
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546 |
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547 void CreateSkewSymmetric(Matrix& s, |
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548 const Vector& v) |
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549 { |
392 | 550 if (v.size() != 3) |
551 { | |
552 throw Orthanc::OrthancException(Orthanc::ErrorCode_ParameterOutOfRange); | |
553 } | |
165
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554 |
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555 s.resize(3, 3); |
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556 s(0,0) = 0; |
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557 s(0,1) = -v[2]; |
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558 s(0,2) = v[1]; |
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559 s(1,0) = v[2]; |
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560 s(1,1) = 0; |
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561 s(1,2) = -v[0]; |
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562 s(2,0) = -v[1]; |
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563 s(2,1) = v[0]; |
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564 s(2,2) = 0; |
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565 } |
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566 |
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567 |
166 | 568 Matrix InvertScalingTranslationMatrix(const Matrix& t) |
165
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569 { |
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570 if (t.size1() != 4 || |
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571 t.size2() != 4 || |
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572 !LinearAlgebra::IsCloseToZero(t(0,1)) || |
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573 !LinearAlgebra::IsCloseToZero(t(0,2)) || |
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574 !LinearAlgebra::IsCloseToZero(t(1,0)) || |
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575 !LinearAlgebra::IsCloseToZero(t(1,2)) || |
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576 !LinearAlgebra::IsCloseToZero(t(2,0)) || |
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577 !LinearAlgebra::IsCloseToZero(t(2,1)) || |
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578 !LinearAlgebra::IsCloseToZero(t(3,0)) || |
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579 !LinearAlgebra::IsCloseToZero(t(3,1)) || |
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580 !LinearAlgebra::IsCloseToZero(t(3,2))) |
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581 { |
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582 LOG(ERROR) << "This matrix is more than a zoom/translate transform"; |
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583 throw Orthanc::OrthancException(Orthanc::ErrorCode_InternalError); |
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584 } |
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585 |
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586 const double sx = t(0,0); |
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587 const double sy = t(1,1); |
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588 const double sz = t(2,2); |
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589 const double w = t(3,3); |
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590 |
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591 if (LinearAlgebra::IsCloseToZero(sx) || |
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592 LinearAlgebra::IsCloseToZero(sy) || |
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593 LinearAlgebra::IsCloseToZero(sz) || |
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594 LinearAlgebra::IsCloseToZero(w)) |
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595 { |
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596 LOG(ERROR) << "Singular transform"; |
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597 throw Orthanc::OrthancException(Orthanc::ErrorCode_InternalError); |
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598 } |
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599 |
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600 const double tx = t(0,3); |
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601 const double ty = t(1,3); |
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602 const double tz = t(2,3); |
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603 |
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604 Matrix m = IdentityMatrix(4); |
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605 |
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606 m(0,0) = 1.0 / sx; |
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607 m(1,1) = 1.0 / sy; |
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608 m(2,2) = 1.0 / sz; |
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609 m(3,3) = 1.0 / w; |
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610 |
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611 m(0,3) = -tx / (sx * w); |
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612 m(1,3) = -ty / (sy * w); |
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613 m(2,3) = -tz / (sz * w); |
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614 |
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615 return m; |
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616 } |
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617 |
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618 |
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619 bool IsShearMatrix(const Matrix& shear) |
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620 { |
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621 return (shear.size1() == 4 && |
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622 shear.size2() == 4 && |
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623 LinearAlgebra::IsNear(1.0, shear(0,0)) && |
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624 LinearAlgebra::IsNear(0.0, shear(0,1)) && |
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625 LinearAlgebra::IsNear(0.0, shear(0,3)) && |
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626 LinearAlgebra::IsNear(0.0, shear(1,0)) && |
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627 LinearAlgebra::IsNear(1.0, shear(1,1)) && |
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628 LinearAlgebra::IsNear(0.0, shear(1,3)) && |
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629 LinearAlgebra::IsNear(0.0, shear(2,0)) && |
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630 LinearAlgebra::IsNear(0.0, shear(2,1)) && |
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631 LinearAlgebra::IsNear(1.0, shear(2,2)) && |
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632 LinearAlgebra::IsNear(0.0, shear(2,3)) && |
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633 LinearAlgebra::IsNear(0.0, shear(3,0)) && |
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634 LinearAlgebra::IsNear(0.0, shear(3,1)) && |
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635 LinearAlgebra::IsNear(1.0, shear(3,3))); |
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636 } |
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637 |
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638 |
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639 Matrix InvertShearMatrix(const Matrix& shear) |
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640 { |
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641 if (!IsShearMatrix(shear)) |
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642 { |
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643 LOG(ERROR) << "Not a valid shear matrix"; |
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644 throw Orthanc::OrthancException(Orthanc::ErrorCode_InternalError); |
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645 } |
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646 |
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647 Matrix m = IdentityMatrix(4); |
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648 m(0,2) = -shear(0,2); |
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649 m(1,2) = -shear(1,2); |
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650 m(3,2) = -shear(3,2); |
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651 |
8d50e6be565d
LinearAlgebra toolbox
Sebastien Jodogne <s.jodogne@gmail.com>
parents:
164
diff
changeset
|
652 return m; |
8d50e6be565d
LinearAlgebra toolbox
Sebastien Jodogne <s.jodogne@gmail.com>
parents:
164
diff
changeset
|
653 } |
158 | 654 } |
655 } |