| 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" | 
| 37 | + | #include "Vector3.hpp" | 
| 38 | + |  | 
| 39 |  | namespace oopse { | 
| 40 |  |  | 
| 41 |  | template<typename Real> | 
| 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 | < | void  inverse(); | 
| 258 | < |  | 
| 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 | < | * Sets the value of this matrix to  the inversion of other matrix. | 
| 280 | < | * @ param m the source matrix | 
| 281 | < | */ | 
| 282 | < | void inverse(const SquareMatrix<Real, Dim>& m); | 
| 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 | < | }; | 
| 430 | > | } //namespace oopse | 
| 431 | > | #endif // MATH_SQUAREMATRIX_HPP | 
| 432 |  |  | 
| 74 | – | } | 
| 75 | – | #endif // MATH_SQUAREMATRIX#_HPP |