Changeset 4627 in orxonox.OLD for orxonox/trunk/src/lib/collision_detection
- Timestamp:
- Jun 14, 2005, 1:39:31 AM (19 years ago)
- Location:
- orxonox/trunk/src/lib/collision_detection
- Files:
-
- 4 edited
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orxonox/trunk/src/lib/collision_detection/Makefile.am
r4547 r4627 25 25 bv_tree_node.h \ 26 26 bounding_volume.h \ 27 bounding_sphere.h 27 bounding_sphere.h \ 28 lin_alg.h 28 29 -
orxonox/trunk/src/lib/collision_detection/Makefile.in
r4547 r4627 208 208 bv_tree_node.h \ 209 209 bounding_volume.h \ 210 bounding_sphere.h 210 bounding_sphere.h \ 211 lin_alg.h 211 212 212 213 all: all-am -
orxonox/trunk/src/lib/collision_detection/lin_alg.h
r4626 r4627 1 /*! 2 \file lin_alg.h 3 \brief Definition of some important linear algebra formulas 4 5 compute the eigenpairs (eigenvalues and eigenvectors) of a real symmetric matrix "A" by the Jacobi method 6 */ 7 8 #include "abstract_model.h" 9 10 #include <stdio.h> 11 #include <math.h> 12 13 #define NDIM 3 14 15 16 typedef float MatrixX[3][3]; 17 18 // 19 // class "EVJacobi" for computing the eigenpairs 20 // (members) 21 // ndim int ... dimension 22 // "ndim" must satisfy 1 < ndim < NDIM 23 // ("NDIM" is given above). 24 // a double [NDIM][NDIM] ... matrix A 25 // aa double ... the square root of 26 // (1/2) x (the sum of the off-diagonal elements squared) 27 // ev double [NDIM] ... eigenvalues 28 // evec double [NDIM][NDIM] ... eigenvectors 29 // evec[i][k], i=1,2,...,ndim are the elements of the eigenvector 30 // corresponding to the k-th eigenvalue ev[k] 31 // vec double [NDIM][NDIM] ... the 2-dimensional array where the matrix elements are stored 32 // lSort int ... 33 // If lSort = 1, sort the eigenvalues d(i) in the descending order, i.e., 34 // ev[1] >= ev[2] >= ... >= ev[ndim], and 35 // if lSort = 0, in the ascending order, i.e., 36 // ev[1] <= ev[2] <= ... <= ev[ndim]. 37 // lMatSize int ... If 1 < ndim < NDIM, lMatSize = 1 38 // otherwise, lMatSize = 0 39 // p int [NDIM] ... index vector for sorting the eigenvalues 40 // (public member functions) 41 // setMatrix void ... give the matrix A 42 // getEigenValue void ... get the eigenvalues 43 // getEigenVector void ... get the eigenvectors 44 // sortEigenpair void ... sort the eigenpairs 45 // (private member functions) 46 // ComputeEigenpair void ... compute the eigenpairs 47 // matrixUpdate void ... each step of the Jacobi method, i.e., 48 // update of the matrix A by Givens' transform. 49 // getP void ... get the index vector p, i.e., sort the eigenvalues. 50 // printMatrix void ... print the elements of the matrix A. 51 // 52 53 class EVJacobi 54 { 55 public: 56 void setMatrix(int, double [][NDIM], int, int); 57 void getEigenValue(double []); 58 void getEigenVector(double [][NDIM]); 59 void sortEigenpair(int); 60 61 private: 62 void ComputeEigenpair(int); 63 void matrixUpdate(void); 64 void getP(void); 65 void printMatrix(void); 66 67 private: 68 double a[NDIM][NDIM], aa, ev[NDIM], evec[NDIM][NDIM], vec[NDIM][NDIM]; 69 int ndim, lSort, p[NDIM], lMatSize; 70 }; 71 72 //------------public member function of the class "EVJacobi"------------------------------ 73 // 74 // give the dimension "ndim" and the matrix "A" and compute the eigenpairs 75 // (input) 76 // ndim0 int ... dimension 77 // a0 double[][NDIM] matrix A 78 // lSort0 int ... lSort 79 // If lSort = 1, sort the eigenvalues d(i) in the descending order, i.e., 80 // ev[1] >= ev[2] >= ... >= ev[ndim], and 81 // if lSort = 0, in the ascending order, i.e., 82 // ev[1] <= ev[2] <= ... <= ev[ndim]. 83 // l_print int ... 84 // If l_print = 1, print the matrices during the iterations. 85 // 86 void EVJacobi::setMatrix(int ndim0, double a0[][NDIM], int lSort0, int l_print) 87 { 88 ndim = ndim0; 89 if (ndim < NDIM && ndim > 1) 90 { 91 lMatSize = 1; 92 lSort = lSort0; 93 for (int i=1; i<=ndim; ++i) 94 for (int j=1; j<=ndim; ++j) 95 a[i][j] = a0[i][j]; 96 // 97 aa = 0.0; 98 for (int i=1; i<=ndim; ++i) 99 for (int j=1; j<=i-1; ++j) 100 aa += a[i][j]*a[i][j]; 101 aa = sqrt(aa); 102 // 103 ComputeEigenpair(l_print); 104 getP(); 105 } 106 else 107 { 108 lMatSize = 0; 109 printf("ndim = %d\n", ndim); 110 printf("ndim must satisfy 1 < ndim < NDIM=%d\n", NDIM); 111 } 112 } 113 // 114 // get the eigenvalues 115 // (input) 116 // ev0[NDIM] double ... the array where the eigenvalues are written 117 void EVJacobi::getEigenValue(double ev0[]) 118 { 119 for (int k=1; k<=ndim; ++k) ev0[k] = ev[p[k]]; 120 } 121 // 122 // get the eigenvectors 123 // (input) 124 // evec0[NDIM][NDIM] double ... the two-dimensional array 125 // where the eigenvectors are written in such a way that 126 // evec0[k][i], i=1,2,...,ndim are the elements of the eigenvector 127 // corresponding to the k-th eigenvalue ev0[k] 128 // 129 void EVJacobi::getEigenVector(double evec0[][NDIM]) 130 { 131 for (int k=1; k<=ndim; ++k) 132 for (int i=1; i<=ndim; ++i) 133 evec0[k][i] = evec[p[k]][i]; 134 } 135 // 136 // sort the eigenpairs 137 // (input) 138 // lSort0 int 139 // If lSort0 = 1, the eigenvalues are sorted in the descending order, i.e., 140 // ev0[1] >= ev0[2] >= ... >= ev0[ndim] 141 // and if lSort0 = 0, in the ascending order, i.e., 142 // ev0[1] <= ev0[2] <= ... <= ev0[ndim] 143 // 144 void EVJacobi::sortEigenpair(int lSort0) 145 { 146 lSort = lSort0; 147 getP(); 148 } 149 //-------private member function of the class "EVJacobi"----- 150 // 151 // compute the eigenpairs 152 // (input) 153 // l_print int 154 // If l_print = 1, print the matrices during the iterations. 155 // 156 void EVJacobi::ComputeEigenpair(int l_print) 157 { 158 if (lMatSize==1) 159 { 160 if (l_print==1) 161 { 162 printf("step %d\n", 0); 163 printMatrix(); 164 printf("\n"); 165 } 166 // 167 double eps = 1.0e-15, epsa = eps * aa; 168 int kend = 1000, l_conv = 0; 169 // 170 for (int i=1; i<=ndim; ++i) 171 for (int j=1; j<=ndim; ++j) 172 vec[i][j] = 0.0; 173 for (int i=1; i<=ndim; ++i) 174 vec[i][i] = 1.0; 175 // 176 for (int k=1; k<=kend; ++k) 177 { 178 matrixUpdate(); 179 double a1 = 0.0; 180 for (int i=1; i<=ndim; ++i) 181 for (int j=1; j<=i-1; ++j) 182 a1 += a[i][j] * a[i][j]; 183 a1 = sqrt(a1); 184 if (a1 < epsa) 185 { 186 if (l_print==1) 187 { 188 printf("converged at step %d\n", k); 189 printMatrix(); 190 printf("\n"); 191 } 192 l_conv = 1; 193 break; 194 } 195 if (l_print==1) 196 if (k%10==0) 197 { 198 printf("step %d\n", k); 199 printMatrix(); 200 printf("\n"); 201 } 202 } 203 // 204 if (l_conv == 0) printf("Jacobi method not converged.\n"); 205 for (int k=1; k<=ndim; ++k) 206 { 207 ev[k] = a[k][k]; 208 for (int i=1; i<=ndim; ++i) evec[k][i] = vec[i][k]; 209 } 210 } 211 } 212 // 213 void EVJacobi::printMatrix(void) 214 { 215 for (int i=1; i<=ndim; ++i) 216 { 217 for (int j=1; j<=ndim; ++j) printf("%8.1e ",a[i][j]); 218 printf("\n"); 219 } 220 } 221 // 222 void EVJacobi::matrixUpdate(void) 223 { 224 double a_new[NDIM][NDIM], vec_new[NDIM][NDIM]; 225 // 226 int p=2, q=1; 227 double amax = fabs(a[p][q]); 228 for (int i=3; i<=ndim; ++i) 229 for (int j=1; j<=i-1; ++j) 230 if (fabs(a[i][j]) > amax) 231 { 232 p = i; 233 q = j; 234 amax = fabs(a[i][j]); 235 } 236 // 237 // Givens' rotation by Rutishauser's rule 238 // 239 double z, t, c, s, u; 240 z = (a[q][q] - a[p][p]) / (2.0 * a[p][q]); 241 t = fabs(z) + sqrt(1.0 + z*z); 242 if (z < 0.0) t = - t; 243 t = 1.0 / t; 244 c = 1.0 / sqrt(1.0 + t*t); 245 s = c * t; 246 u = s / (1.0 + c); 247 // 248 for (int i=1; i<=ndim; ++i) 249 for (int j=1; j<=ndim; ++j) 250 a_new[i][j] = a[i][j]; 251 // 252 a_new[p][p] = a[p][p] - t * a[p][q]; 253 a_new[q][q] = a[q][q] + t * a[p][q]; 254 a_new[p][q] = 0.0; 255 a_new[q][p] = 0.0; 256 for (int j=1; j<=ndim; ++j) 257 if (j!=p && j!=q) 258 { 259 a_new[p][j] = a[p][j] - s * (a[q][j] + u * a[p][j]); 260 a_new[j][p] = a_new[p][j]; 261 a_new[q][j] = a[q][j] + s * (a[p][j] - u * a[q][j]); 262 a_new[j][q] = a_new[q][j]; 263 } 264 // 265 for (int i=1; i<=ndim; ++i) 266 { 267 vec_new[i][p] = vec[i][p] * c - vec[i][q] * s; 268 vec_new[i][q] = vec[i][p] * s + vec[i][q] * c; 269 for (int j=1; j<=ndim; ++j) 270 if (j!=p && j!=q) vec_new[i][j] = vec[i][j]; 271 } 272 // 273 for (int i=1; i<=ndim; ++i) 274 for (int j=1; j<=ndim; ++j) 275 { 276 a[i][j] = a_new[i][j]; 277 vec[i][j] = vec_new[i][j]; 278 } 279 } 280 // 281 // sort the eigenpairs 282 // If l_print=1, sort the eigenvalues in the descending order, i.e., 283 // ev[1] >= ev[2] >= ... >= ev[ndim], and 284 // if l_print=0, in the ascending order, i.e., 285 // ev[1] <= ev[2] <= ... <= ev[ndim]. 286 // 287 void EVJacobi::getP(void) 288 { 289 for (int i=1; i<=ndim; ++i) p[i] = i; 290 // 291 if (lSort==1) 292 { 293 for (int k=1; k<=ndim; ++k) 294 { 295 double emax = ev[p[k]]; 296 for (int i=k+1; i<=ndim; ++i) 297 { 298 if (emax < ev[p[i]]) 299 { 300 emax = ev[p[i]]; 301 int pp = p[k]; 302 p[k] = p[i]; 303 p[i] = pp; 304 } 305 } 306 } 307 } 308 if (lSort==0) 309 { 310 for (int k=1; k<=ndim; ++k) 311 { 312 double emin = ev[p[k]]; 313 for (int i=k+1; i<=ndim; ++i) 314 { 315 if (emin > ev[p[i]]) 316 { 317 emin = ev[p[i]]; 318 int pp = p[k]; 319 p[k] = p[i]; 320 p[i] = pp; 321 } 322 } 323 } 324 } 325 } 326 327 328 329 330 331 332 333 // void jacobi(Matrix A, int n, sVec3D d, Matrix V, int *nRot) 334 // { 335 // sVec3D B, Z; 336 // double c, g, h, s, sm, t, tau, theta, tresh; 337 // int i, j, ip, iq; 338 // 339 // void *vmblock1 = NULL; 340 // 341 // //allocate vectors B, Z 342 // vmblock1 = vminit(); 343 // //B = (REAL *) vmalloc(vmblock1, VEKTOR, 100, 0); 344 // //Z = (REAL *) vmalloc(vmblock1, VEKTOR, 100, 0); 345 // 346 // //initialize V to identity matrix 347 // for(int i = 1; i <= n; i++) 348 // { 349 // for(int j = 1; j <= n; j++) 350 // V[i][j] = 0; 351 // V[i][i] = 1; 352 // } 353 // 354 // for(int i = 1; i <= n; i++) 355 // { 356 // B[i] = A[i][i]; 357 // D[i] = B[i]; 358 // Z[i] = 0; 359 // } 360 // 361 // *nRot = 0; 362 // for(int i = 1; i<=50; i++) 363 // { 364 // sm = 0; 365 // for(int k = 1; k < n; k++) //sum off-diagonal elements 366 // for (int l = k + 1; l <= n; k++) 367 // sm = sm + fabs(A[k][l]); 368 // if ( sm == 0 ) 369 // { 370 // //vmfree(vmblock1); 371 // return; //normal return 372 // } 373 // if (i < 4) 374 // tresh = 0.2 * sm * sm; 375 // else 376 // tresh = 0; 377 // for(int k = 1; k < n; k++) 378 // { 379 // for (iq=ip+1; iq<=N; iq++) { 380 // g=100*fabs(A[ip][iq]); 381 // // after 4 sweeps, skip the rotation if the off-diagonal element is small 382 // if ((i > 4) && (fabs(D[ip])+g == fabs(D[ip])) && (fabs(D[iq])+g == fabs(D[iq]))) 383 // A[ip][iq]=0; 384 // else if (fabs(A[ip][iq]) > tresh) { 385 // h=D[iq]-D[ip]; 386 // if (fabs(h)+g == fabs(h)) 387 // t=A[ip][iq]/h; 388 // else { 389 // theta=0.5*h/A[ip][iq]; 390 // t=1/(fabs(theta)+sqrt(1.0+theta*theta)); 391 // if (theta < 0) t=-t; 392 // } 393 // c=1.0/sqrt(1.0+t*t); 394 // s=t*c; 395 // tau=s/(1.0+c); 396 // h=t*A[ip][iq]; 397 // Z[ip] -= h; 398 // Z[iq] += h; 399 // D[ip] -= h; 400 // D[iq] += h; 401 // A[ip][iq]=0; 402 // for (j=1; j<ip; j++) { 403 // g=A[j][ip]; 404 // h=A[j][iq]; 405 // A[j][ip] = g-s*(h+g*tau); 406 // A[j][iq] = h+s*(g-h*tau); 407 // } 408 // for (j=ip+1; j<iq; j++) { 409 // g=A[ip][j]; 410 // h=A[j][iq]; 411 // A[ip][j] = g-s*(h+g*tau); 412 // A[j][iq] = h+s*(g-h*tau); 413 // } 414 // for (j=iq+1; j<=N; j++) { 415 // g=A[ip][j]; 416 // h=A[iq][j]; 417 // A[ip][j] = g-s*(h+g*tau); 418 // A[iq][j] = h+s*(g-h*tau); 419 // } 420 // for (j=1; j<=N; j++) { 421 // g=V[j][ip]; 422 // h=V[j][iq]; 423 // V[j][ip] = g-s*(h+g*tau); 424 // V[j][iq] = h+s*(g-h*tau); 425 // } 426 // *NROT=*NROT+1; 427 // } //end ((i.gt.4)...else if 428 // } // main iq loop 429 // } // main ip loop 430 // for (ip=1; ip<=N; ip++) { 431 // B[ip] += Z[ip]; 432 // D[ip]=B[ip]; 433 // Z[ip]=0; 434 // } 435 // } //end of main i loop 436 // printf("\n 50 iterations !\n"); 437 // vmfree(vmblock1); 438 // return; //too many iterations 439 // } 440 -
orxonox/trunk/src/lib/collision_detection/obb_tree_node.cc
r4626 r4627 36 36 #include "newmatio.h" 37 37 38 #include "lin_alg.h" 39 38 40 39 41 … … 101 103 Vector p, q, r; //!< holder of the polygon data, much more conveniant to work with Vector than sVec3d 102 104 Vector t1, t2; //!< temporary values 103 floatcovariance[3][3]; //!< the covariance matrix105 double covariance[3][3]; //!< the covariance matrix 104 106 105 107 this->numOfVertices = length; … … 191 193 Vector** axis = new Vector*[3]; //!< the references to the obb axis 192 194 193 C(1,1) = covariance[0][0]; 194 C(1,2) = covariance[0][1]; 195 C(1,3) = covariance[0][2]; 196 C(2,1) = covariance[1][0]; 197 C(2,2) = covariance[1][1]; 198 C(2,3) = covariance[1][2]; 199 C(3,1) = covariance[2][0]; 200 C(3,2) = covariance[2][1]; 201 C(3,3) = covariance[2][2]; 195 196 double a[4][4]; 197 198 a[0][0] = C(1,1) = covariance[0][0]; 199 a[0][1] = C(1,2) = covariance[0][1]; 200 a[0][2] = C(1,3) = covariance[0][2]; 201 a[1][0] = C(2,1) = covariance[1][0]; 202 a[1][1] = C(2,2) = covariance[1][1]; 203 a[1][2] = C(2,3) = covariance[1][2]; 204 a[2][0] = C(3,1) = covariance[2][0]; 205 a[2][1] = C(3,2) = covariance[2][1]; 206 a[2][2] = C(3,3) = covariance[2][2]; 202 207 203 208 Jacobi(C, D, V); /* do the jacobi decomposition */ 204 209 PRINTF(0)("-- Done Jacobi Decomposition\n"); 205 210 206 // printf("\nwe got a result! YES: \n"); 207 // 208 // for(int j = 1; j < 4; ++j) 209 // { 210 // printf(" |"); 211 // for(int k = 1; k < 4; ++k) 212 // { 213 // printf(" \b%f ", V(j, k)); 214 // } 215 // printf(" |\n"); 216 // } 211 212 /* new jacobi tests */ 213 double eigenvectors[3][3]; 214 double eigval[3]; 215 216 EVJacobi jac; 217 jac.setMatrix(2, covariance, 0, 0); 218 jac.getEigenVector(eigenvectors); 219 220 221 printf("Old Jacobi\n"); 222 for(int j = 1; j < 4; ++j) 223 { 224 printf(" |"); 225 for(int k = 1; k < 4; ++k) 226 { 227 printf(" \b%f ", V(j, k)); 228 } 229 printf(" |\n"); 230 } 231 232 printf("New Jacobi\n"); 233 for(int j = 0; j < 3; ++j) 234 { 235 printf(" |"); 236 for(int k = 0; k < 3; ++k) 237 { 238 printf(" \b%f ", eigenvectors[j][k]); 239 } 240 printf(" |\n"); 241 } 217 242 218 243 axis[0] = new Vector(V(1, 1), V(2, 1), V(3, 1));
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