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root/OpenMD/branches/development/src/math/SquareMatrix3.hpp
Revision: 1753
Committed: Tue Jun 12 13:20:28 2012 UTC (12 years, 10 months ago) by gezelter
File size: 18652 byte(s)
Log Message:
Added a double dot tensor contraction.

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# Content
1 /*
2 * Copyright (c) 2005 The University of Notre Dame. All Rights Reserved.
3 *
4 * The University of Notre Dame grants you ("Licensee") a
5 * non-exclusive, royalty free, license to use, modify and
6 * redistribute this software in source and binary code form, provided
7 * that the following conditions are met:
8 *
9 * 1. Redistributions of source code must retain the above copyright
10 * notice, this list of conditions and the following disclaimer.
11 *
12 * 2. Redistributions in binary form must reproduce the above copyright
13 * notice, this list of conditions and the following disclaimer in the
14 * documentation and/or other materials provided with the
15 * distribution.
16 *
17 * This software is provided "AS IS," without a warranty of any
18 * kind. All express or implied conditions, representations and
19 * warranties, including any implied warranty of merchantability,
20 * fitness for a particular purpose or non-infringement, are hereby
21 * excluded. The University of Notre Dame and its licensors shall not
22 * be liable for any damages suffered by licensee as a result of
23 * using, modifying or distributing the software or its
24 * derivatives. In no event will the University of Notre Dame or its
25 * licensors be liable for any lost revenue, profit or data, or for
26 * direct, indirect, special, consequential, incidental or punitive
27 * damages, however caused and regardless of the theory of liability,
28 * arising out of the use of or inability to use software, even if the
29 * University of Notre Dame has been advised of the possibility of
30 * such damages.
31 *
32 * SUPPORT OPEN SCIENCE! If you use OpenMD or its source code in your
33 * research, please cite the appropriate papers when you publish your
34 * work. Good starting points are:
35 *
36 * [1] Meineke, et al., J. Comp. Chem. 26, 252-271 (2005).
37 * [2] Fennell & Gezelter, J. Chem. Phys. 124, 234104 (2006).
38 * [3] Sun, Lin & Gezelter, J. Chem. Phys. 128, 24107 (2008).
39 * [4] Kuang & Gezelter, J. Chem. Phys. 133, 164101 (2010).
40 * [5] Vardeman, Stocker & Gezelter, J. Chem. Theory Comput. 7, 834 (2011).
41 */
42
43 /**
44 * @file SquareMatrix3.hpp
45 * @author Teng Lin
46 * @date 10/11/2004
47 * @version 1.0
48 */
49 #ifndef MATH_SQUAREMATRIX3_HPP
50 #define MATH_SQUAREMATRIX3_HPP
51 #include <vector>
52 #include "Quaternion.hpp"
53 #include "SquareMatrix.hpp"
54 #include "Vector3.hpp"
55 #include "utils/NumericConstant.hpp"
56 namespace OpenMD {
57
58 template<typename Real>
59 class SquareMatrix3 : public SquareMatrix<Real, 3> {
60 public:
61
62 typedef Real ElemType;
63 typedef Real* ElemPoinerType;
64
65 /** default constructor */
66 SquareMatrix3() : SquareMatrix<Real, 3>() {
67 }
68
69 /** Constructs and initializes every element of this matrix to a scalar */
70 SquareMatrix3(Real s) : SquareMatrix<Real,3>(s){
71 }
72
73 /** Constructs and initializes from an array */
74 SquareMatrix3(Real* array) : SquareMatrix<Real,3>(array){
75 }
76
77
78 /** copy constructor */
79 SquareMatrix3(const SquareMatrix<Real, 3>& m) : SquareMatrix<Real, 3>(m) {
80 }
81
82 SquareMatrix3( const Vector3<Real>& eulerAngles) {
83 setupRotMat(eulerAngles);
84 }
85
86 SquareMatrix3(Real phi, Real theta, Real psi) {
87 setupRotMat(phi, theta, psi);
88 }
89
90 SquareMatrix3(const Quaternion<Real>& q) {
91 setupRotMat(q);
92
93 }
94
95 SquareMatrix3(Real w, Real x, Real y, Real z) {
96 setupRotMat(w, x, y, z);
97 }
98
99 /** copy assignment operator */
100 SquareMatrix3<Real>& operator =(const SquareMatrix<Real, 3>& m) {
101 if (this == &m)
102 return *this;
103 SquareMatrix<Real, 3>::operator=(m);
104 return *this;
105 }
106
107
108 SquareMatrix3<Real>& operator =(const Quaternion<Real>& q) {
109 this->setupRotMat(q);
110 return *this;
111 }
112
113
114 /**
115 * Sets this matrix to a rotation matrix by three euler angles
116 * @ param euler
117 */
118 void setupRotMat(const Vector3<Real>& eulerAngles) {
119 setupRotMat(eulerAngles[0], eulerAngles[1], eulerAngles[2]);
120 }
121
122 /**
123 * Sets this matrix to a rotation matrix by three euler angles
124 * @param phi
125 * @param theta
126 * @psi theta
127 */
128 void setupRotMat(Real phi, Real theta, Real psi) {
129 Real sphi, stheta, spsi;
130 Real cphi, ctheta, cpsi;
131
132 sphi = sin(phi);
133 stheta = sin(theta);
134 spsi = sin(psi);
135 cphi = cos(phi);
136 ctheta = cos(theta);
137 cpsi = cos(psi);
138
139 this->data_[0][0] = cpsi * cphi - ctheta * sphi * spsi;
140 this->data_[0][1] = cpsi * sphi + ctheta * cphi * spsi;
141 this->data_[0][2] = spsi * stheta;
142
143 this->data_[1][0] = -spsi * ctheta - ctheta * sphi * cpsi;
144 this->data_[1][1] = -spsi * stheta + ctheta * cphi * cpsi;
145 this->data_[1][2] = cpsi * stheta;
146
147 this->data_[2][0] = stheta * sphi;
148 this->data_[2][1] = -stheta * cphi;
149 this->data_[2][2] = ctheta;
150 }
151
152
153 /**
154 * Sets this matrix to a rotation matrix by quaternion
155 * @param quat
156 */
157 void setupRotMat(const Quaternion<Real>& quat) {
158 setupRotMat(quat.w(), quat.x(), quat.y(), quat.z());
159 }
160
161 /**
162 * Sets this matrix to a rotation matrix by quaternion
163 * @param w the first element
164 * @param x the second element
165 * @param y the third element
166 * @param z the fourth element
167 */
168 void setupRotMat(Real w, Real x, Real y, Real z) {
169 Quaternion<Real> q(w, x, y, z);
170 *this = q.toRotationMatrix3();
171 }
172
173 void setupSkewMat(Vector3<Real> v) {
174 setupSkewMat(v[0], v[1], v[2]);
175 }
176
177 void setupSkewMat(Real v1, Real v2, Real v3) {
178 this->data_[0][0] = 0;
179 this->data_[0][1] = -v3;
180 this->data_[0][2] = v2;
181 this->data_[1][0] = v3;
182 this->data_[1][1] = 0;
183 this->data_[1][2] = -v1;
184 this->data_[2][0] = -v2;
185 this->data_[2][1] = v1;
186 this->data_[2][2] = 0;
187
188
189 }
190
191
192 /**
193 * Returns the quaternion from this rotation matrix
194 * @return the quaternion from this rotation matrix
195 * @exception invalid rotation matrix
196 */
197 Quaternion<Real> toQuaternion() {
198 Quaternion<Real> q;
199 Real t, s;
200 Real ad1, ad2, ad3;
201 t = this->data_[0][0] + this->data_[1][1] + this->data_[2][2] + 1.0;
202
203 if( t > NumericConstant::epsilon ){
204
205 s = 0.5 / sqrt( t );
206 q[0] = 0.25 / s;
207 q[1] = (this->data_[1][2] - this->data_[2][1]) * s;
208 q[2] = (this->data_[2][0] - this->data_[0][2]) * s;
209 q[3] = (this->data_[0][1] - this->data_[1][0]) * s;
210 } else {
211
212 ad1 = this->data_[0][0];
213 ad2 = this->data_[1][1];
214 ad3 = this->data_[2][2];
215
216 if( ad1 >= ad2 && ad1 >= ad3 ){
217
218 s = 0.5 / sqrt( 1.0 + this->data_[0][0] - this->data_[1][1] - this->data_[2][2] );
219 q[0] = (this->data_[1][2] - this->data_[2][1]) * s;
220 q[1] = 0.25 / s;
221 q[2] = (this->data_[0][1] + this->data_[1][0]) * s;
222 q[3] = (this->data_[0][2] + this->data_[2][0]) * s;
223 } else if ( ad2 >= ad1 && ad2 >= ad3 ) {
224 s = 0.5 / sqrt( 1.0 + this->data_[1][1] - this->data_[0][0] - this->data_[2][2] );
225 q[0] = (this->data_[2][0] - this->data_[0][2] ) * s;
226 q[1] = (this->data_[0][1] + this->data_[1][0]) * s;
227 q[2] = 0.25 / s;
228 q[3] = (this->data_[1][2] + this->data_[2][1]) * s;
229 } else {
230
231 s = 0.5 / sqrt( 1.0 + this->data_[2][2] - this->data_[0][0] - this->data_[1][1] );
232 q[0] = (this->data_[0][1] - this->data_[1][0]) * s;
233 q[1] = (this->data_[0][2] + this->data_[2][0]) * s;
234 q[2] = (this->data_[1][2] + this->data_[2][1]) * s;
235 q[3] = 0.25 / s;
236 }
237 }
238
239 return q;
240
241 }
242
243 /**
244 * Returns the euler angles from this rotation matrix
245 * @return the euler angles in a vector
246 * @exception invalid rotation matrix
247 * We use so-called "x-convention", which is the most common definition.
248 * In this convention, the rotation given by Euler angles (phi, theta,
249 * psi), where the first rotation is by an angle phi about the z-axis,
250 * the second is by an angle theta (0 <= theta <= 180) about the x-axis,
251 * and the third is by an angle psi about the z-axis (again).
252 */
253 Vector3<Real> toEulerAngles() {
254 Vector3<Real> myEuler;
255 Real phi;
256 Real theta;
257 Real psi;
258 Real ctheta;
259 Real stheta;
260
261 // set the tolerance for Euler angles and rotation elements
262
263 theta = acos(std::min((RealType)1.0, std::max((RealType)-1.0,this->data_[2][2])));
264 ctheta = this->data_[2][2];
265 stheta = sqrt(1.0 - ctheta * ctheta);
266
267 // when sin(theta) is close to 0, we need to consider
268 // singularity In this case, we can assign an arbitary value to
269 // phi (or psi), and then determine the psi (or phi) or
270 // vice-versa. We'll assume that phi always gets the rotation,
271 // and psi is 0 in cases of singularity.
272 // we use atan2 instead of atan, since atan2 will give us -Pi to Pi.
273 // Since 0 <= theta <= 180, sin(theta) will be always
274 // non-negative. Therefore, it will never change the sign of both of
275 // the parameters passed to atan2.
276
277 if (fabs(stheta) < 1e-6){
278 psi = 0.0;
279 phi = atan2(-this->data_[1][0], this->data_[0][0]);
280 }
281 // we only have one unique solution
282 else{
283 phi = atan2(this->data_[2][0], -this->data_[2][1]);
284 psi = atan2(this->data_[0][2], this->data_[1][2]);
285 }
286
287 //wrap phi and psi, make sure they are in the range from 0 to 2*Pi
288 if (phi < 0)
289 phi += 2.0 * M_PI;
290
291 if (psi < 0)
292 psi += 2.0 * M_PI;
293
294 myEuler[0] = phi;
295 myEuler[1] = theta;
296 myEuler[2] = psi;
297
298 return myEuler;
299 }
300
301 /** Returns the determinant of this matrix. */
302 Real determinant() const {
303 Real x,y,z;
304
305 x = this->data_[0][0] * (this->data_[1][1] * this->data_[2][2] - this->data_[1][2] * this->data_[2][1]);
306 y = this->data_[0][1] * (this->data_[1][2] * this->data_[2][0] - this->data_[1][0] * this->data_[2][2]);
307 z = this->data_[0][2] * (this->data_[1][0] * this->data_[2][1] - this->data_[1][1] * this->data_[2][0]);
308
309 return(x + y + z);
310 }
311
312 /** Returns the trace of this matrix. */
313 Real trace() const {
314 return this->data_[0][0] + this->data_[1][1] + this->data_[2][2];
315 }
316
317 /**
318 * Sets the value of this matrix to the inversion of itself.
319 * @note since simple algorithm can be applied to inverse the 3 by 3 matrix, we hide the
320 * implementation of inverse in SquareMatrix class
321 */
322 SquareMatrix3<Real> inverse() const {
323 SquareMatrix3<Real> m;
324 RealType det = determinant();
325 if (fabs(det) <= OpenMD::epsilon) {
326 //"The method was called on a matrix with |determinant| <= 1e-6.",
327 //"This is a runtime or a programming error in your application.");
328 std::vector<int> zeroDiagElementIndex;
329 for (int i =0; i < 3; ++i) {
330 if (fabs(this->data_[i][i]) <= OpenMD::epsilon) {
331 zeroDiagElementIndex.push_back(i);
332 }
333 }
334
335 if (zeroDiagElementIndex.size() == 2) {
336 int index = zeroDiagElementIndex[0];
337 m(index, index) = 1.0 / this->data_[index][index];
338 }else if (zeroDiagElementIndex.size() == 1) {
339
340 int a = (zeroDiagElementIndex[0] + 1) % 3;
341 int b = (zeroDiagElementIndex[0] + 2) %3;
342 RealType denom = this->data_[a][a] * this->data_[b][b] - this->data_[b][a]*this->data_[a][b];
343 m(a, a) = this->data_[b][b] /denom;
344 m(b, a) = -this->data_[b][a]/denom;
345
346 m(a,b) = -this->data_[a][b]/denom;
347 m(b, b) = this->data_[a][a]/denom;
348
349 }
350
351 /*
352 for(std::vector<int>::iterator iter = zeroDiagElementIndex.begin(); iter != zeroDiagElementIndex.end() ++iter) {
353 if (this->data_[*iter][0] > OpenMD::epsilon || this->data_[*iter][1] ||this->data_[*iter][2] ||
354 this->data_[0][*iter] > OpenMD::epsilon || this->data_[1][*iter] ||this->data_[2][*iter] ) {
355 std::cout << "can not inverse matrix" << std::endl;
356 }
357 }
358 */
359 } else {
360
361 m(0, 0) = this->data_[1][1]*this->data_[2][2] - this->data_[1][2]*this->data_[2][1];
362 m(1, 0) = this->data_[1][2]*this->data_[2][0] - this->data_[1][0]*this->data_[2][2];
363 m(2, 0) = this->data_[1][0]*this->data_[2][1] - this->data_[1][1]*this->data_[2][0];
364 m(0, 1) = this->data_[2][1]*this->data_[0][2] - this->data_[2][2]*this->data_[0][1];
365 m(1, 1) = this->data_[2][2]*this->data_[0][0] - this->data_[2][0]*this->data_[0][2];
366 m(2, 1) = this->data_[2][0]*this->data_[0][1] - this->data_[2][1]*this->data_[0][0];
367 m(0, 2) = this->data_[0][1]*this->data_[1][2] - this->data_[0][2]*this->data_[1][1];
368 m(1, 2) = this->data_[0][2]*this->data_[1][0] - this->data_[0][0]*this->data_[1][2];
369 m(2, 2) = this->data_[0][0]*this->data_[1][1] - this->data_[0][1]*this->data_[1][0];
370
371 m /= det;
372 }
373 return m;
374 }
375
376 SquareMatrix3<Real> transpose() const{
377 SquareMatrix3<Real> result;
378
379 for (unsigned int i = 0; i < 3; i++)
380 for (unsigned int j = 0; j < 3; j++)
381 result(j, i) = this->data_[i][j];
382
383 return result;
384 }
385 /**
386 * Extract the eigenvalues and eigenvectors from a 3x3 matrix.
387 * The eigenvectors (the columns of V) will be normalized.
388 * The eigenvectors are aligned optimally with the x, y, and z
389 * axes respectively.
390 * @param a symmetric matrix whose eigenvectors are to be computed. On return, the matrix is
391 * overwritten
392 * @param w will contain the eigenvalues of the matrix On return of this function
393 * @param v the columns of this matrix will contain the eigenvectors. The eigenvectors are
394 * normalized and mutually orthogonal.
395 * @warning a will be overwritten
396 */
397 static void diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, SquareMatrix3<Real>& v);
398 };
399 /*=========================================================================
400
401 Program: Visualization Toolkit
402 Module: $RCSfile: SquareMatrix3.hpp,v $
403
404 Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
405 All rights reserved.
406 See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
407
408 This software is distributed WITHOUT ANY WARRANTY; without even
409 the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
410 PURPOSE. See the above copyright notice for more information.
411
412 =========================================================================*/
413 template<typename Real>
414 void SquareMatrix3<Real>::diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w,
415 SquareMatrix3<Real>& v) {
416 int i,j,k,maxI;
417 Real tmp, maxVal;
418 Vector3<Real> v_maxI, v_k, v_j;
419
420 // diagonalize using Jacobi
421 SquareMatrix3<Real>::jacobi(a, w, v);
422 // if all the eigenvalues are the same, return identity matrix
423 if (w[0] == w[1] && w[0] == w[2] ) {
424 v = SquareMatrix3<Real>::identity();
425 return;
426 }
427
428 // transpose temporarily, it makes it easier to sort the eigenvectors
429 v = v.transpose();
430
431 // if two eigenvalues are the same, re-orthogonalize to optimally line
432 // up the eigenvectors with the x, y, and z axes
433 for (i = 0; i < 3; i++) {
434 if (w((i+1)%3) == w((i+2)%3)) {// two eigenvalues are the same
435 // find maximum element of the independant eigenvector
436 maxVal = fabs(v(i, 0));
437 maxI = 0;
438 for (j = 1; j < 3; j++) {
439 if (maxVal < (tmp = fabs(v(i, j)))){
440 maxVal = tmp;
441 maxI = j;
442 }
443 }
444
445 // swap the eigenvector into its proper position
446 if (maxI != i) {
447 tmp = w(maxI);
448 w(maxI) = w(i);
449 w(i) = tmp;
450
451 v.swapRow(i, maxI);
452 }
453 // maximum element of eigenvector should be positive
454 if (v(maxI, maxI) < 0) {
455 v(maxI, 0) = -v(maxI, 0);
456 v(maxI, 1) = -v(maxI, 1);
457 v(maxI, 2) = -v(maxI, 2);
458 }
459
460 // re-orthogonalize the other two eigenvectors
461 j = (maxI+1)%3;
462 k = (maxI+2)%3;
463
464 v(j, 0) = 0.0;
465 v(j, 1) = 0.0;
466 v(j, 2) = 0.0;
467 v(j, j) = 1.0;
468
469 /** @todo */
470 v_maxI = v.getRow(maxI);
471 v_j = v.getRow(j);
472 v_k = cross(v_maxI, v_j);
473 v_k.normalize();
474 v_j = cross(v_k, v_maxI);
475 v.setRow(j, v_j);
476 v.setRow(k, v_k);
477
478
479 // transpose vectors back to columns
480 v = v.transpose();
481 return;
482 }
483 }
484
485 // the three eigenvalues are different, just sort the eigenvectors
486 // to align them with the x, y, and z axes
487
488 // find the vector with the largest x element, make that vector
489 // the first vector
490 maxVal = fabs(v(0, 0));
491 maxI = 0;
492 for (i = 1; i < 3; i++) {
493 if (maxVal < (tmp = fabs(v(i, 0)))) {
494 maxVal = tmp;
495 maxI = i;
496 }
497 }
498
499 // swap eigenvalue and eigenvector
500 if (maxI != 0) {
501 tmp = w(maxI);
502 w(maxI) = w(0);
503 w(0) = tmp;
504 v.swapRow(maxI, 0);
505 }
506 // do the same for the y element
507 if (fabs(v(1, 1)) < fabs(v(2, 1))) {
508 tmp = w(2);
509 w(2) = w(1);
510 w(1) = tmp;
511 v.swapRow(2, 1);
512 }
513
514 // ensure that the sign of the eigenvectors is correct
515 for (i = 0; i < 2; i++) {
516 if (v(i, i) < 0) {
517 v(i, 0) = -v(i, 0);
518 v(i, 1) = -v(i, 1);
519 v(i, 2) = -v(i, 2);
520 }
521 }
522
523 // set sign of final eigenvector to ensure that determinant is positive
524 if (v.determinant() < 0) {
525 v(2, 0) = -v(2, 0);
526 v(2, 1) = -v(2, 1);
527 v(2, 2) = -v(2, 2);
528 }
529
530 // transpose the eigenvectors back again
531 v = v.transpose();
532 return ;
533 }
534
535 /**
536 * Return the multiplication of two matrixes (m1 * m2).
537 * @return the multiplication of two matrixes
538 * @param m1 the first matrix
539 * @param m2 the second matrix
540 */
541 template<typename Real>
542 inline SquareMatrix3<Real> operator *(const SquareMatrix3<Real>& m1, const SquareMatrix3<Real>& m2) {
543 SquareMatrix3<Real> result;
544
545 for (unsigned int i = 0; i < 3; i++)
546 for (unsigned int j = 0; j < 3; j++)
547 for (unsigned int k = 0; k < 3; k++)
548 result(i, j) += m1(i, k) * m2(k, j);
549
550 return result;
551 }
552
553 template<typename Real>
554 inline SquareMatrix3<Real> outProduct(const Vector3<Real>& v1, const Vector3<Real>& v2) {
555 SquareMatrix3<Real> result;
556
557 for (unsigned int i = 0; i < 3; i++) {
558 for (unsigned int j = 0; j < 3; j++) {
559 result(i, j) = v1[i] * v2[j];
560 }
561 }
562
563 return result;
564 }
565
566
567 typedef SquareMatrix3<RealType> Mat3x3d;
568 typedef SquareMatrix3<RealType> RotMat3x3d;
569
570 } //namespace OpenMD
571 #endif // MATH_SQUAREMATRIX_HPP
572

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