# | Line 29 | Line 29 | |
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29 | * @date 10/11/2004 | |
30 | * @version 1.0 | |
31 | */ | |
32 | < | #ifndef MATH_SQUAREMATRIX_HPP |
33 | < | #define MATH_SQUAREMATRIX_HPP |
32 | > | #ifndef MATH_SQUAREMATRIX3_HPP |
33 | > | #define MATH_SQUAREMATRIX3_HPP |
34 | ||
35 | #include "Quaternion.hpp" | |
36 | #include "SquareMatrix.hpp" | |
# | Line 41 | Line 41 | namespace oopse { | |
41 | template<typename Real> | |
42 | class SquareMatrix3 : public SquareMatrix<Real, 3> { | |
43 | public: | |
44 | + | |
45 | + | typedef Real ElemType; |
46 | + | typedef Real* ElemPoinerType; |
47 | ||
48 | /** default constructor */ | |
49 | SquareMatrix3() : SquareMatrix<Real, 3>() { | |
# | Line 59 | Line 62 | namespace oopse { | |
62 | } | |
63 | ||
64 | SquareMatrix3(const Quaternion<Real>& q) { | |
65 | < | *this = q.toRotationMatrix3(); |
65 | > | setupRotMat(q); |
66 | > | |
67 | } | |
68 | ||
69 | SquareMatrix3(Real w, Real x, Real y, Real z) { | |
70 | < | Quaternion<Real> q(w, x, y, z); |
67 | < | *this = q.toRotationMatrix3(); |
70 | > | setupRotMat(w, x, y, z); |
71 | } | |
72 | ||
73 | /** copy assignment operator */ | |
# | Line 72 | Line 75 | namespace oopse { | |
75 | if (this == &m) | |
76 | return *this; | |
77 | SquareMatrix<Real, 3>::operator=(m); | |
78 | + | return *this; |
79 | } | |
80 | ||
81 | /** | |
# | Line 118 | Line 122 | namespace oopse { | |
122 | * @param quat | |
123 | */ | |
124 | void setupRotMat(const Quaternion<Real>& quat) { | |
125 | < | *this = quat.toRotationMatrix3(); |
125 | > | setupRotMat(quat.w(), quat.x(), quat.y(), quat.z()); |
126 | } | |
127 | ||
128 | /** | |
# | Line 126 | Line 130 | namespace oopse { | |
130 | * @param w the first element | |
131 | * @param x the second element | |
132 | * @param y the third element | |
133 | < | * @parma z the fourth element |
133 | > | * @param z the fourth element |
134 | */ | |
135 | void setupRotMat(Real w, Real x, Real y, Real z) { | |
136 | Quaternion<Real> q(w, x, y, z); | |
# | Line 195 | Line 199 | namespace oopse { | |
199 | * z-axis (again). | |
200 | */ | |
201 | Vector3<Real> toEulerAngles() { | |
202 | < | Vector<Real> myEuler; |
202 | > | Vector3<Real> myEuler; |
203 | Real phi,theta,psi,eps; | |
204 | Real ctheta,stheta; | |
205 | ||
206 | // set the tolerance for Euler angles and rotation elements | |
207 | ||
208 | < | theta = acos(min(1.0,max(-1.0,data_[2][2]))); |
208 | > | theta = acos(std::min(1.0, std::max(-1.0,data_[2][2]))); |
209 | ctheta = data_[2][2]; | |
210 | stheta = sqrt(1.0 - ctheta * ctheta); | |
211 | ||
# | Line 237 | Line 241 | namespace oopse { | |
241 | return myEuler; | |
242 | } | |
243 | ||
244 | + | /** Returns the determinant of this matrix. */ |
245 | + | Real determinant() const { |
246 | + | Real x,y,z; |
247 | + | |
248 | + | x = data_[0][0] * (data_[1][1] * data_[2][2] - data_[1][2] * data_[2][1]); |
249 | + | y = data_[0][1] * (data_[1][2] * data_[2][0] - data_[1][0] * data_[2][2]); |
250 | + | z = data_[0][2] * (data_[1][0] * data_[2][1] - data_[1][1] * data_[2][0]); |
251 | + | |
252 | + | return(x + y + z); |
253 | + | } |
254 | + | |
255 | /** | |
256 | * Sets the value of this matrix to the inversion of itself. | |
257 | * @note since simple algorithm can be applied to inverse the 3 by 3 matrix, we hide the | |
258 | * implementation of inverse in SquareMatrix class | |
259 | */ | |
260 | < | void inverse(); |
260 | > | SquareMatrix3<Real> inverse() { |
261 | > | SquareMatrix3<Real> m; |
262 | > | double det = determinant(); |
263 | > | if (fabs(det) <= oopse::epsilon) { |
264 | > | //"The method was called on a matrix with |determinant| <= 1e-6.", |
265 | > | //"This is a runtime or a programming error in your application."); |
266 | > | } |
267 | ||
268 | < | void diagonalize(); |
268 | > | m(0, 0) = data_[1][1]*data_[2][2] - data_[1][2]*data_[2][1]; |
269 | > | m(1, 0) = data_[1][2]*data_[2][0] - data_[1][0]*data_[2][2]; |
270 | > | m(2, 0) = data_[1][0]*data_[2][1] - data_[1][1]*data_[2][0]; |
271 | > | m(0, 1) = data_[2][1]*data_[0][2] - data_[2][2]*data_[0][1]; |
272 | > | m(1, 1) = data_[2][2]*data_[0][0] - data_[2][0]*data_[0][2]; |
273 | > | m(2, 1) = data_[2][0]*data_[0][1] - data_[2][1]*data_[0][0]; |
274 | > | m(0, 2) = data_[0][1]*data_[1][2] - data_[0][2]*data_[1][1]; |
275 | > | m(1, 2) = data_[0][2]*data_[1][0] - data_[0][0]*data_[1][2]; |
276 | > | m(2, 2) = data_[0][0]*data_[1][1] - data_[0][1]*data_[1][0]; |
277 | ||
278 | + | m /= det; |
279 | + | return m; |
280 | + | } |
281 | + | /** |
282 | + | * Extract the eigenvalues and eigenvectors from a 3x3 matrix. |
283 | + | * The eigenvectors (the columns of V) will be normalized. |
284 | + | * The eigenvectors are aligned optimally with the x, y, and z |
285 | + | * axes respectively. |
286 | + | * @param a symmetric matrix whose eigenvectors are to be computed. On return, the matrix is |
287 | + | * overwritten |
288 | + | * @param w will contain the eigenvalues of the matrix On return of this function |
289 | + | * @param v the columns of this matrix will contain the eigenvectors. The eigenvectors are |
290 | + | * normalized and mutually orthogonal. |
291 | + | * @warning a will be overwritten |
292 | + | */ |
293 | + | static void diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, SquareMatrix3<Real>& v); |
294 | }; | |
295 | + | /*========================================================================= |
296 | ||
297 | < | typedef template SquareMatrix3<double> Mat3x3d |
298 | < | typedef template SquareMatrix3<double> RotMat3x3d; |
297 | > | Program: Visualization Toolkit |
298 | > | Module: $RCSfile: SquareMatrix3.hpp,v $ |
299 | > | |
300 | > | Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen |
301 | > | All rights reserved. |
302 | > | See Copyright.txt or http://www.kitware.com/Copyright.htm for details. |
303 | > | |
304 | > | This software is distributed WITHOUT ANY WARRANTY; without even |
305 | > | the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR |
306 | > | PURPOSE. See the above copyright notice for more information. |
307 | > | |
308 | > | =========================================================================*/ |
309 | > | template<typename Real> |
310 | > | void SquareMatrix3<Real>::diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, |
311 | > | SquareMatrix3<Real>& v) { |
312 | > | int i,j,k,maxI; |
313 | > | Real tmp, maxVal; |
314 | > | Vector3<Real> v_maxI, v_k, v_j; |
315 | > | |
316 | > | // diagonalize using Jacobi |
317 | > | jacobi(a, w, v); |
318 | > | // if all the eigenvalues are the same, return identity matrix |
319 | > | if (w[0] == w[1] && w[0] == w[2] ) { |
320 | > | v = SquareMatrix3<Real>::identity(); |
321 | > | return; |
322 | > | } |
323 | > | |
324 | > | // transpose temporarily, it makes it easier to sort the eigenvectors |
325 | > | v = v.transpose(); |
326 | > | |
327 | > | // if two eigenvalues are the same, re-orthogonalize to optimally line |
328 | > | // up the eigenvectors with the x, y, and z axes |
329 | > | for (i = 0; i < 3; i++) { |
330 | > | if (w((i+1)%3) == w((i+2)%3)) {// two eigenvalues are the same |
331 | > | // find maximum element of the independant eigenvector |
332 | > | maxVal = fabs(v(i, 0)); |
333 | > | maxI = 0; |
334 | > | for (j = 1; j < 3; j++) { |
335 | > | if (maxVal < (tmp = fabs(v(i, j)))){ |
336 | > | maxVal = tmp; |
337 | > | maxI = j; |
338 | > | } |
339 | > | } |
340 | > | |
341 | > | // swap the eigenvector into its proper position |
342 | > | if (maxI != i) { |
343 | > | tmp = w(maxI); |
344 | > | w(maxI) = w(i); |
345 | > | w(i) = tmp; |
346 | ||
347 | + | v.swapRow(i, maxI); |
348 | + | } |
349 | + | // maximum element of eigenvector should be positive |
350 | + | if (v(maxI, maxI) < 0) { |
351 | + | v(maxI, 0) = -v(maxI, 0); |
352 | + | v(maxI, 1) = -v(maxI, 1); |
353 | + | v(maxI, 2) = -v(maxI, 2); |
354 | + | } |
355 | + | |
356 | + | // re-orthogonalize the other two eigenvectors |
357 | + | j = (maxI+1)%3; |
358 | + | k = (maxI+2)%3; |
359 | + | |
360 | + | v(j, 0) = 0.0; |
361 | + | v(j, 1) = 0.0; |
362 | + | v(j, 2) = 0.0; |
363 | + | v(j, j) = 1.0; |
364 | + | |
365 | + | /** @todo */ |
366 | + | v_maxI = v.getRow(maxI); |
367 | + | v_j = v.getRow(j); |
368 | + | v_k = cross(v_maxI, v_j); |
369 | + | v_k.normalize(); |
370 | + | v_j = cross(v_k, v_maxI); |
371 | + | v.setRow(j, v_j); |
372 | + | v.setRow(k, v_k); |
373 | + | |
374 | + | |
375 | + | // transpose vectors back to columns |
376 | + | v = v.transpose(); |
377 | + | return; |
378 | + | } |
379 | + | } |
380 | + | |
381 | + | // the three eigenvalues are different, just sort the eigenvectors |
382 | + | // to align them with the x, y, and z axes |
383 | + | |
384 | + | // find the vector with the largest x element, make that vector |
385 | + | // the first vector |
386 | + | maxVal = fabs(v(0, 0)); |
387 | + | maxI = 0; |
388 | + | for (i = 1; i < 3; i++) { |
389 | + | if (maxVal < (tmp = fabs(v(i, 0)))) { |
390 | + | maxVal = tmp; |
391 | + | maxI = i; |
392 | + | } |
393 | + | } |
394 | + | |
395 | + | // swap eigenvalue and eigenvector |
396 | + | if (maxI != 0) { |
397 | + | tmp = w(maxI); |
398 | + | w(maxI) = w(0); |
399 | + | w(0) = tmp; |
400 | + | v.swapRow(maxI, 0); |
401 | + | } |
402 | + | // do the same for the y element |
403 | + | if (fabs(v(1, 1)) < fabs(v(2, 1))) { |
404 | + | tmp = w(2); |
405 | + | w(2) = w(1); |
406 | + | w(1) = tmp; |
407 | + | v.swapRow(2, 1); |
408 | + | } |
409 | + | |
410 | + | // ensure that the sign of the eigenvectors is correct |
411 | + | for (i = 0; i < 2; i++) { |
412 | + | if (v(i, i) < 0) { |
413 | + | v(i, 0) = -v(i, 0); |
414 | + | v(i, 1) = -v(i, 1); |
415 | + | v(i, 2) = -v(i, 2); |
416 | + | } |
417 | + | } |
418 | + | |
419 | + | // set sign of final eigenvector to ensure that determinant is positive |
420 | + | if (v.determinant() < 0) { |
421 | + | v(2, 0) = -v(2, 0); |
422 | + | v(2, 1) = -v(2, 1); |
423 | + | v(2, 2) = -v(2, 2); |
424 | + | } |
425 | + | |
426 | + | // transpose the eigenvectors back again |
427 | + | v = v.transpose(); |
428 | + | return ; |
429 | + | } |
430 | + | typedef SquareMatrix3<double> Mat3x3d; |
431 | + | typedef SquareMatrix3<double> RotMat3x3d; |
432 | + | |
433 | } //namespace oopse | |
434 | #endif // MATH_SQUAREMATRIX_HPP | |
435 | + |
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