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root/group/trunk/OOPSE-3.0/src/math/SquareMatrix3.hpp
Revision: 1616
Committed: Wed Oct 20 18:07:08 2004 UTC (19 years, 8 months ago) by tim
File size: 16349 byte(s)
Log Message:
Math library pass the unit test

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# Content
1 /*
2 * Copyright (C) 2000-2004 Object Oriented Parallel Simulation Engine (OOPSE) project
3 *
4 * Contact: oopse@oopse.org
5 *
6 * This program is free software; you can redistribute it and/or
7 * modify it under the terms of the GNU Lesser General Public License
8 * as published by the Free Software Foundation; either version 2.1
9 * of the License, or (at your option) any later version.
10 * All we ask is that proper credit is given for our work, which includes
11 * - but is not limited to - adding the above copyright notice to the beginning
12 * of your source code files, and to any copyright notice that you may distribute
13 * with programs based on this work.
14 *
15 * This program is distributed in the hope that it will be useful,
16 * but WITHOUT ANY WARRANTY; without even the implied warranty of
17 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
18 * GNU Lesser General Public License for more details.
19 *
20 * You should have received a copy of the GNU Lesser General Public License
21 * along with this program; if not, write to the Free Software
22 * Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
23 *
24 */
25
26 /**
27 * @file SquareMatrix3.hpp
28 * @author Teng Lin
29 * @date 10/11/2004
30 * @version 1.0
31 */
32 #ifndef MATH_SQUAREMATRIX3_HPP
33 #define MATH_SQUAREMATRIX3_HPP
34
35 #include "Quaternion.hpp"
36 #include "SquareMatrix.hpp"
37 #include "Vector3.hpp"
38
39 namespace oopse {
40
41 template<typename Real>
42 class SquareMatrix3 : public SquareMatrix<Real, 3> {
43 public:
44
45 /** default constructor */
46 SquareMatrix3() : SquareMatrix<Real, 3>() {
47 }
48
49 /** copy constructor */
50 SquareMatrix3(const SquareMatrix<Real, 3>& m) : SquareMatrix<Real, 3>(m) {
51 }
52
53 SquareMatrix3( const Vector3<Real>& eulerAngles) {
54 setupRotMat(eulerAngles);
55 }
56
57 SquareMatrix3(Real phi, Real theta, Real psi) {
58 setupRotMat(phi, theta, psi);
59 }
60
61 SquareMatrix3(const Quaternion<Real>& q) {
62 setupRotMat(q);
63
64 }
65
66 SquareMatrix3(Real w, Real x, Real y, Real z) {
67 setupRotMat(w, x, y, z);
68 }
69
70 /** copy assignment operator */
71 SquareMatrix3<Real>& operator =(const SquareMatrix<Real, 3>& m) {
72 if (this == &m)
73 return *this;
74 SquareMatrix<Real, 3>::operator=(m);
75 return *this;
76 }
77
78 /**
79 * Sets this matrix to a rotation matrix by three euler angles
80 * @ param euler
81 */
82 void setupRotMat(const Vector3<Real>& eulerAngles) {
83 setupRotMat(eulerAngles[0], eulerAngles[1], eulerAngles[2]);
84 }
85
86 /**
87 * Sets this matrix to a rotation matrix by three euler angles
88 * @param phi
89 * @param theta
90 * @psi theta
91 */
92 void setupRotMat(Real phi, Real theta, Real psi) {
93 Real sphi, stheta, spsi;
94 Real cphi, ctheta, cpsi;
95
96 sphi = sin(phi);
97 stheta = sin(theta);
98 spsi = sin(psi);
99 cphi = cos(phi);
100 ctheta = cos(theta);
101 cpsi = cos(psi);
102
103 data_[0][0] = cpsi * cphi - ctheta * sphi * spsi;
104 data_[0][1] = cpsi * sphi + ctheta * cphi * spsi;
105 data_[0][2] = spsi * stheta;
106
107 data_[1][0] = -spsi * ctheta - ctheta * sphi * cpsi;
108 data_[1][1] = -spsi * stheta + ctheta * cphi * cpsi;
109 data_[1][2] = cpsi * stheta;
110
111 data_[2][0] = stheta * sphi;
112 data_[2][1] = -stheta * cphi;
113 data_[2][2] = ctheta;
114 }
115
116
117 /**
118 * Sets this matrix to a rotation matrix by quaternion
119 * @param quat
120 */
121 void setupRotMat(const Quaternion<Real>& quat) {
122 setupRotMat(quat.w(), quat.x(), quat.y(), quat.z());
123 }
124
125 /**
126 * Sets this matrix to a rotation matrix by quaternion
127 * @param w the first element
128 * @param x the second element
129 * @param y the third element
130 * @param z the fourth element
131 */
132 void setupRotMat(Real w, Real x, Real y, Real z) {
133 Quaternion<Real> q(w, x, y, z);
134 *this = q.toRotationMatrix3();
135 }
136
137 /**
138 * Returns the quaternion from this rotation matrix
139 * @return the quaternion from this rotation matrix
140 * @exception invalid rotation matrix
141 */
142 Quaternion<Real> toQuaternion() {
143 Quaternion<Real> q;
144 Real t, s;
145 Real ad1, ad2, ad3;
146 t = data_[0][0] + data_[1][1] + data_[2][2] + 1.0;
147
148 if( t > 0.0 ){
149
150 s = 0.5 / sqrt( t );
151 q[0] = 0.25 / s;
152 q[1] = (data_[1][2] - data_[2][1]) * s;
153 q[2] = (data_[2][0] - data_[0][2]) * s;
154 q[3] = (data_[0][1] - data_[1][0]) * s;
155 } else {
156
157 ad1 = fabs( data_[0][0] );
158 ad2 = fabs( data_[1][1] );
159 ad3 = fabs( data_[2][2] );
160
161 if( ad1 >= ad2 && ad1 >= ad3 ){
162
163 s = 2.0 * sqrt( 1.0 + data_[0][0] - data_[1][1] - data_[2][2] );
164 q[0] = (data_[1][2] + data_[2][1]) / s;
165 q[1] = 0.5 / s;
166 q[2] = (data_[0][1] + data_[1][0]) / s;
167 q[3] = (data_[0][2] + data_[2][0]) / s;
168 } else if ( ad2 >= ad1 && ad2 >= ad3 ) {
169 s = sqrt( 1.0 + data_[1][1] - data_[0][0] - data_[2][2] ) * 2.0;
170 q[0] = (data_[0][2] + data_[2][0]) / s;
171 q[1] = (data_[0][1] + data_[1][0]) / s;
172 q[2] = 0.5 / s;
173 q[3] = (data_[1][2] + data_[2][1]) / s;
174 } else {
175
176 s = sqrt( 1.0 + data_[2][2] - data_[0][0] - data_[1][1] ) * 2.0;
177 q[0] = (data_[0][1] + data_[1][0]) / s;
178 q[1] = (data_[0][2] + data_[2][0]) / s;
179 q[2] = (data_[1][2] + data_[2][1]) / s;
180 q[3] = 0.5 / s;
181 }
182 }
183
184 return q;
185
186 }
187
188 /**
189 * Returns the euler angles from this rotation matrix
190 * @return the euler angles in a vector
191 * @exception invalid rotation matrix
192 * We use so-called "x-convention", which is the most common definition.
193 * In this convention, the rotation given by Euler angles (phi, theta, psi), where the first
194 * rotation is by an angle phi about the z-axis, the second is by an angle
195 * theta (0 <= theta <= 180)about the x-axis, and thethird is by an angle psi about the
196 * z-axis (again).
197 */
198 Vector3<Real> toEulerAngles() {
199 Vector3<Real> myEuler;
200 Real phi,theta,psi,eps;
201 Real ctheta,stheta;
202
203 // set the tolerance for Euler angles and rotation elements
204
205 theta = acos(std::min(1.0, std::max(-1.0,data_[2][2])));
206 ctheta = data_[2][2];
207 stheta = sqrt(1.0 - ctheta * ctheta);
208
209 // when sin(theta) is close to 0, we need to consider singularity
210 // In this case, we can assign an arbitary value to phi (or psi), and then determine
211 // the psi (or phi) or vice-versa. We'll assume that phi always gets the rotation, and psi is 0
212 // in cases of singularity.
213 // we use atan2 instead of atan, since atan2 will give us -Pi to Pi.
214 // Since 0 <= theta <= 180, sin(theta) will be always non-negative. Therefore, it never
215 // change the sign of both of the parameters passed to atan2.
216
217 if (fabs(stheta) <= oopse::epsilon){
218 psi = 0.0;
219 phi = atan2(-data_[1][0], data_[0][0]);
220 }
221 // we only have one unique solution
222 else{
223 phi = atan2(data_[2][0], -data_[2][1]);
224 psi = atan2(data_[0][2], data_[1][2]);
225 }
226
227 //wrap phi and psi, make sure they are in the range from 0 to 2*Pi
228 if (phi < 0)
229 phi += M_PI;
230
231 if (psi < 0)
232 psi += M_PI;
233
234 myEuler[0] = phi;
235 myEuler[1] = theta;
236 myEuler[2] = psi;
237
238 return myEuler;
239 }
240
241 /** Returns the determinant of this matrix. */
242 Real determinant() const {
243 Real x,y,z;
244
245 x = data_[0][0] * (data_[1][1] * data_[2][2] - data_[1][2] * data_[2][1]);
246 y = data_[0][1] * (data_[1][2] * data_[2][0] - data_[1][0] * data_[2][2]);
247 z = data_[0][2] * (data_[1][0] * data_[2][1] - data_[1][1] * data_[2][0]);
248
249 return(x + y + z);
250 }
251
252 /**
253 * Sets the value of this matrix to the inversion of itself.
254 * @note since simple algorithm can be applied to inverse the 3 by 3 matrix, we hide the
255 * implementation of inverse in SquareMatrix class
256 */
257 SquareMatrix3<Real> inverse() {
258 SquareMatrix3<Real> m;
259 double det = determinant();
260 if (fabs(det) <= oopse::epsilon) {
261 //"The method was called on a matrix with |determinant| <= 1e-6.",
262 //"This is a runtime or a programming error in your application.");
263 }
264
265 m(0, 0) = data_[1][1]*data_[2][2] - data_[1][2]*data_[2][1];
266 m(1, 0) = data_[1][2]*data_[2][0] - data_[1][0]*data_[2][2];
267 m(2, 0) = data_[1][0]*data_[2][1] - data_[1][1]*data_[2][0];
268 m(0, 1) = data_[2][1]*data_[0][2] - data_[2][2]*data_[0][1];
269 m(1, 1) = data_[2][2]*data_[0][0] - data_[2][0]*data_[0][2];
270 m(2, 1) = data_[2][0]*data_[0][1] - data_[2][1]*data_[0][0];
271 m(0, 2) = data_[0][1]*data_[1][2] - data_[0][2]*data_[1][1];
272 m(1, 2) = data_[0][2]*data_[1][0] - data_[0][0]*data_[1][2];
273 m(2, 2) = data_[0][0]*data_[1][1] - data_[0][1]*data_[1][0];
274
275 m /= det;
276 return m;
277 }
278 /**
279 * Extract the eigenvalues and eigenvectors from a 3x3 matrix.
280 * The eigenvectors (the columns of V) will be normalized.
281 * The eigenvectors are aligned optimally with the x, y, and z
282 * axes respectively.
283 * @param a symmetric matrix whose eigenvectors are to be computed. On return, the matrix is
284 * overwritten
285 * @param w will contain the eigenvalues of the matrix On return of this function
286 * @param v the columns of this matrix will contain the eigenvectors. The eigenvectors are
287 * normalized and mutually orthogonal.
288 * @warning a will be overwritten
289 */
290 static void diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, SquareMatrix3<Real>& v);
291 };
292 /*=========================================================================
293
294 Program: Visualization Toolkit
295 Module: $RCSfile: SquareMatrix3.hpp,v $
296
297 Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
298 All rights reserved.
299 See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
300
301 This software is distributed WITHOUT ANY WARRANTY; without even
302 the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
303 PURPOSE. See the above copyright notice for more information.
304
305 =========================================================================*/
306 template<typename Real>
307 void SquareMatrix3<Real>::diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w,
308 SquareMatrix3<Real>& v) {
309 int i,j,k,maxI;
310 Real tmp, maxVal;
311 Vector3<Real> v_maxI, v_k, v_j;
312
313 // diagonalize using Jacobi
314 jacobi(a, w, v);
315 // if all the eigenvalues are the same, return identity matrix
316 if (w[0] == w[1] && w[0] == w[2] ) {
317 v = SquareMatrix3<Real>::identity();
318 return;
319 }
320
321 // transpose temporarily, it makes it easier to sort the eigenvectors
322 v = v.transpose();
323
324 // if two eigenvalues are the same, re-orthogonalize to optimally line
325 // up the eigenvectors with the x, y, and z axes
326 for (i = 0; i < 3; i++) {
327 if (w((i+1)%3) == w((i+2)%3)) {// two eigenvalues are the same
328 // find maximum element of the independant eigenvector
329 maxVal = fabs(v(i, 0));
330 maxI = 0;
331 for (j = 1; j < 3; j++) {
332 if (maxVal < (tmp = fabs(v(i, j)))){
333 maxVal = tmp;
334 maxI = j;
335 }
336 }
337
338 // swap the eigenvector into its proper position
339 if (maxI != i) {
340 tmp = w(maxI);
341 w(maxI) = w(i);
342 w(i) = tmp;
343
344 v.swapRow(i, maxI);
345 }
346 // maximum element of eigenvector should be positive
347 if (v(maxI, maxI) < 0) {
348 v(maxI, 0) = -v(maxI, 0);
349 v(maxI, 1) = -v(maxI, 1);
350 v(maxI, 2) = -v(maxI, 2);
351 }
352
353 // re-orthogonalize the other two eigenvectors
354 j = (maxI+1)%3;
355 k = (maxI+2)%3;
356
357 v(j, 0) = 0.0;
358 v(j, 1) = 0.0;
359 v(j, 2) = 0.0;
360 v(j, j) = 1.0;
361
362 /** @todo */
363 v_maxI = v.getRow(maxI);
364 v_j = v.getRow(j);
365 v_k = cross(v_maxI, v_j);
366 v_k.normalize();
367 v_j = cross(v_k, v_maxI);
368 v.setRow(j, v_j);
369 v.setRow(k, v_k);
370
371
372 // transpose vectors back to columns
373 v = v.transpose();
374 return;
375 }
376 }
377
378 // the three eigenvalues are different, just sort the eigenvectors
379 // to align them with the x, y, and z axes
380
381 // find the vector with the largest x element, make that vector
382 // the first vector
383 maxVal = fabs(v(0, 0));
384 maxI = 0;
385 for (i = 1; i < 3; i++) {
386 if (maxVal < (tmp = fabs(v(i, 0)))) {
387 maxVal = tmp;
388 maxI = i;
389 }
390 }
391
392 // swap eigenvalue and eigenvector
393 if (maxI != 0) {
394 tmp = w(maxI);
395 w(maxI) = w(0);
396 w(0) = tmp;
397 v.swapRow(maxI, 0);
398 }
399 // do the same for the y element
400 if (fabs(v(1, 1)) < fabs(v(2, 1))) {
401 tmp = w(2);
402 w(2) = w(1);
403 w(1) = tmp;
404 v.swapRow(2, 1);
405 }
406
407 // ensure that the sign of the eigenvectors is correct
408 for (i = 0; i < 2; i++) {
409 if (v(i, i) < 0) {
410 v(i, 0) = -v(i, 0);
411 v(i, 1) = -v(i, 1);
412 v(i, 2) = -v(i, 2);
413 }
414 }
415
416 // set sign of final eigenvector to ensure that determinant is positive
417 if (v.determinant() < 0) {
418 v(2, 0) = -v(2, 0);
419 v(2, 1) = -v(2, 1);
420 v(2, 2) = -v(2, 2);
421 }
422
423 // transpose the eigenvectors back again
424 v = v.transpose();
425 return ;
426 }
427 typedef SquareMatrix3<double> Mat3x3d;
428 typedef SquareMatrix3<double> RotMat3x3d;
429
430 } //namespace oopse
431 #endif // MATH_SQUAREMATRIX_HPP
432