1 /* Discretization tools */ 2 3 #include <petscconf.h> 4 #if defined(PETSC_HAVE_MATHIMF_H) 5 #include <mathimf.h> /* this needs to be included before math.h */ 6 #endif 7 8 #include <petscdt.h> /*I "petscdt.h" I*/ 9 #include <petscblaslapack.h> 10 #include <petsc-private/petscimpl.h> 11 #include <petscviewer.h> 12 13 #undef __FUNCT__ 14 #define __FUNCT__ "PetscDTLegendreEval" 15 /*@ 16 PetscDTLegendreEval - evaluate Legendre polynomial at points 17 18 Not Collective 19 20 Input Arguments: 21 + npoints - number of spatial points to evaluate at 22 . points - array of locations to evaluate at 23 . ndegree - number of basis degrees to evaluate 24 - degrees - sorted array of degrees to evaluate 25 26 Output Arguments: 27 + B - row-oriented basis evaluation matrix B[point*ndegree + degree] (dimension npoints*ndegrees, allocated by caller) (or NULL) 28 . D - row-oriented derivative evaluation matrix (or NULL) 29 - D2 - row-oriented second derivative evaluation matrix (or NULL) 30 31 Level: intermediate 32 33 .seealso: PetscDTGaussQuadrature() 34 @*/ 35 PetscErrorCode PetscDTLegendreEval(PetscInt npoints,const PetscReal *points,PetscInt ndegree,const PetscInt *degrees,PetscReal *B,PetscReal *D,PetscReal *D2) 36 { 37 PetscInt i,maxdegree; 38 39 PetscFunctionBegin; 40 if (!npoints || !ndegree) PetscFunctionReturn(0); 41 maxdegree = degrees[ndegree-1]; 42 for (i=0; i<npoints; i++) { 43 PetscReal pm1,pm2,pd1,pd2,pdd1,pdd2,x; 44 PetscInt j,k; 45 x = points[i]; 46 pm2 = 0; 47 pm1 = 1; 48 pd2 = 0; 49 pd1 = 0; 50 pdd2 = 0; 51 pdd1 = 0; 52 k = 0; 53 if (degrees[k] == 0) { 54 if (B) B[i*ndegree+k] = pm1; 55 if (D) D[i*ndegree+k] = pd1; 56 if (D2) D2[i*ndegree+k] = pdd1; 57 k++; 58 } 59 for (j=1; j<=maxdegree; j++,k++) { 60 PetscReal p,d,dd; 61 p = ((2*j-1)*x*pm1 - (j-1)*pm2)/j; 62 d = pd2 + (2*j-1)*pm1; 63 dd = pdd2 + (2*j-1)*pd1; 64 pm2 = pm1; 65 pm1 = p; 66 pd2 = pd1; 67 pd1 = d; 68 pdd2 = pdd1; 69 pdd1 = dd; 70 if (degrees[k] == j) { 71 if (B) B[i*ndegree+k] = p; 72 if (D) D[i*ndegree+k] = d; 73 if (D2) D2[i*ndegree+k] = dd; 74 } 75 } 76 } 77 PetscFunctionReturn(0); 78 } 79 80 #undef __FUNCT__ 81 #define __FUNCT__ "PetscDTGaussQuadrature" 82 /*@ 83 PetscDTGaussQuadrature - create Gauss quadrature 84 85 Not Collective 86 87 Input Arguments: 88 + npoints - number of points 89 . a - left end of interval (often-1) 90 - b - right end of interval (often +1) 91 92 Output Arguments: 93 + x - quadrature points 94 - w - quadrature weights 95 96 Level: intermediate 97 98 References: 99 Golub and Welsch, Calculation of Quadrature Rules, Math. Comp. 23(106), 221--230, 1969. 100 101 .seealso: PetscDTLegendreEval() 102 @*/ 103 PetscErrorCode PetscDTGaussQuadrature(PetscInt npoints,PetscReal a,PetscReal b,PetscReal *x,PetscReal *w) 104 { 105 PetscErrorCode ierr; 106 PetscInt i; 107 PetscReal *work; 108 PetscScalar *Z; 109 PetscBLASInt N,LDZ,info; 110 111 PetscFunctionBegin; 112 /* Set up the Golub-Welsch system */ 113 for (i=0; i<npoints; i++) { 114 x[i] = 0; /* diagonal is 0 */ 115 if (i) w[i-1] = 0.5 / PetscSqrtReal(1 - 1./PetscSqr(2*i)); 116 } 117 ierr = PetscMalloc2(npoints*npoints,PetscScalar,&Z,PetscMax(1,2*npoints-2),PetscReal,&work);CHKERRQ(ierr); 118 ierr = PetscBLASIntCast(npoints,&N);CHKERRQ(ierr); 119 LDZ = N; 120 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 121 PetscStackCallBLAS("LAPACKsteqr",LAPACKsteqr_("I",&N,x,w,Z,&LDZ,work,&info)); 122 ierr = PetscFPTrapPop();CHKERRQ(ierr); 123 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"xSTEQR error"); 124 125 for (i=0; i<(npoints+1)/2; i++) { 126 PetscReal y = 0.5 * (-x[i] + x[npoints-i-1]); /* enforces symmetry */ 127 x[i] = (a+b)/2 - y*(b-a)/2; 128 x[npoints-i-1] = (a+b)/2 + y*(b-a)/2; 129 130 w[i] = w[npoints-1-i] = (b-a)*PetscSqr(0.5*PetscAbsScalar(Z[i*npoints] + Z[(npoints-i-1)*npoints])); 131 } 132 ierr = PetscFree2(Z,work);CHKERRQ(ierr); 133 PetscFunctionReturn(0); 134 } 135 136 #undef __FUNCT__ 137 #define __FUNCT__ "PetscDTFactorial_Internal" 138 /* Evaluates the nth jacobi polynomial with weight parameters a,b at a point x. 139 Recurrence relations implemented from the pseudocode given in Karniadakis and Sherwin, Appendix B */ 140 PETSC_STATIC_INLINE PetscErrorCode PetscDTFactorial_Internal(PetscInt n, PetscReal *factorial) 141 { 142 PetscReal f = 1.0; 143 PetscInt i; 144 145 PetscFunctionBegin; 146 for (i = 1; i < n+1; ++i) f *= i; 147 *factorial = f; 148 PetscFunctionReturn(0); 149 } 150 151 #undef __FUNCT__ 152 #define __FUNCT__ "PetscDTComputeJacobi" 153 /* Evaluates the nth jacobi polynomial with weight parameters a,b at a point x. 154 Recurrence relations implemented from the pseudocode given in Karniadakis and Sherwin, Appendix B */ 155 PETSC_STATIC_INLINE PetscErrorCode PetscDTComputeJacobi(PetscReal a, PetscReal b, PetscInt n, PetscReal x, PetscReal *P) 156 { 157 PetscReal apb, pn1, pn2; 158 PetscInt k; 159 160 PetscFunctionBegin; 161 if (!n) {*P = 1.0; PetscFunctionReturn(0);} 162 if (n == 1) {*P = 0.5 * (a - b + (a + b + 2.0) * x); PetscFunctionReturn(0);} 163 apb = a + b; 164 pn2 = 1.0; 165 pn1 = 0.5 * (a - b + (apb + 2.0) * x); 166 *P = 0.0; 167 for (k = 2; k < n+1; ++k) { 168 PetscReal a1 = 2.0 * k * (k + apb) * (2.0*k + apb - 2.0); 169 PetscReal a2 = (2.0 * k + apb - 1.0) * (a*a - b*b); 170 PetscReal a3 = (2.0 * k + apb - 2.0) * (2.0 * k + apb - 1.0) * (2.0 * k + apb); 171 PetscReal a4 = 2.0 * (k + a - 1.0) * (k + b - 1.0) * (2.0 * k + apb); 172 173 a2 = a2 / a1; 174 a3 = a3 / a1; 175 a4 = a4 / a1; 176 *P = (a2 + a3 * x) * pn1 - a4 * pn2; 177 pn2 = pn1; 178 pn1 = *P; 179 } 180 PetscFunctionReturn(0); 181 } 182 183 #undef __FUNCT__ 184 #define __FUNCT__ "PetscDTComputeJacobiDerivative" 185 /* Evaluates the first derivative of P_{n}^{a,b} at a point x. */ 186 PETSC_STATIC_INLINE PetscErrorCode PetscDTComputeJacobiDerivative(PetscReal a, PetscReal b, PetscInt n, PetscReal x, PetscReal *P) 187 { 188 PetscReal nP; 189 PetscErrorCode ierr; 190 191 PetscFunctionBegin; 192 if (!n) {*P = 0.0; PetscFunctionReturn(0);} 193 ierr = PetscDTComputeJacobi(a+1, b+1, n-1, x, &nP);CHKERRQ(ierr); 194 *P = 0.5 * (a + b + n + 1) * nP; 195 PetscFunctionReturn(0); 196 } 197 198 #undef __FUNCT__ 199 #define __FUNCT__ "PetscDTMapSquareToTriangle_Internal" 200 /* Maps from [-1,1]^2 to the (-1,1) reference triangle */ 201 PETSC_STATIC_INLINE PetscErrorCode PetscDTMapSquareToTriangle_Internal(PetscReal x, PetscReal y, PetscReal *xi, PetscReal *eta) 202 { 203 PetscFunctionBegin; 204 *xi = 0.5 * (1.0 + x) * (1.0 - y) - 1.0; 205 *eta = y; 206 PetscFunctionReturn(0); 207 } 208 209 #undef __FUNCT__ 210 #define __FUNCT__ "PetscDTMapCubeToTetrahedron_Internal" 211 /* Maps from [-1,1]^2 to the (-1,1) reference triangle */ 212 PETSC_STATIC_INLINE PetscErrorCode PetscDTMapCubeToTetrahedron_Internal(PetscReal x, PetscReal y, PetscReal z, PetscReal *xi, PetscReal *eta, PetscReal *zeta) 213 { 214 PetscFunctionBegin; 215 *xi = 0.25 * (1.0 + x) * (1.0 - y) * (1.0 - z) - 1.0; 216 *eta = 0.5 * (1.0 + y) * (1.0 - z) - 1.0; 217 *zeta = z; 218 PetscFunctionReturn(0); 219 } 220 221 #undef __FUNCT__ 222 #define __FUNCT__ "PetscDTGaussJacobiQuadrature1D_Internal" 223 static PetscErrorCode PetscDTGaussJacobiQuadrature1D_Internal(PetscInt npoints, PetscReal a, PetscReal b, PetscReal *x, PetscReal *w) 224 { 225 PetscInt maxIter = 100; 226 PetscReal eps = 1.0e-8; 227 PetscReal a1, a2, a3, a4, a5, a6; 228 PetscInt k; 229 PetscErrorCode ierr; 230 231 PetscFunctionBegin; 232 233 a1 = pow(2, a+b+1); 234 #if defined(PETSC_HAVE_TGAMMA) 235 a2 = tgamma(a + npoints + 1); 236 a3 = tgamma(b + npoints + 1); 237 a4 = tgamma(a + b + npoints + 1); 238 #else 239 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"tgamma() - math routine is unavailable."); 240 #endif 241 242 ierr = PetscDTFactorial_Internal(npoints, &a5);CHKERRQ(ierr); 243 a6 = a1 * a2 * a3 / a4 / a5; 244 /* Computes the m roots of P_{m}^{a,b} on [-1,1] by Newton's method with Chebyshev points as initial guesses. 245 Algorithm implemented from the pseudocode given by Karniadakis and Sherwin and Python in FIAT */ 246 for (k = 0; k < npoints; ++k) { 247 PetscReal r = -cos((2.0*k + 1.0) * PETSC_PI / (2.0 * npoints)), dP; 248 PetscInt j; 249 250 if (k > 0) r = 0.5 * (r + x[k-1]); 251 for (j = 0; j < maxIter; ++j) { 252 PetscReal s = 0.0, delta, f, fp; 253 PetscInt i; 254 255 for (i = 0; i < k; ++i) s = s + 1.0 / (r - x[i]); 256 ierr = PetscDTComputeJacobi(a, b, npoints, r, &f);CHKERRQ(ierr); 257 ierr = PetscDTComputeJacobiDerivative(a, b, npoints, r, &fp);CHKERRQ(ierr); 258 delta = f / (fp - f * s); 259 r = r - delta; 260 if (fabs(delta) < eps) break; 261 } 262 x[k] = r; 263 ierr = PetscDTComputeJacobiDerivative(a, b, npoints, x[k], &dP);CHKERRQ(ierr); 264 w[k] = a6 / (1.0 - PetscSqr(x[k])) / PetscSqr(dP); 265 } 266 PetscFunctionReturn(0); 267 } 268 269 #undef __FUNCT__ 270 #define __FUNCT__ "PetscDTGaussJacobiQuadrature" 271 /*@C 272 PetscDTGaussJacobiQuadrature - create Gauss-Jacobi quadrature for a simplex 273 274 Not Collective 275 276 Input Arguments: 277 + dim - The simplex dimension 278 . npoints - number of points 279 . a - left end of interval (often-1) 280 - b - right end of interval (often +1) 281 282 Output Arguments: 283 + points - quadrature points 284 - weights - quadrature weights 285 286 Level: intermediate 287 288 References: 289 Karniadakis and Sherwin. 290 FIAT 291 292 .seealso: PetscDTGaussQuadrature() 293 @*/ 294 PetscErrorCode PetscDTGaussJacobiQuadrature(PetscInt dim, PetscInt npoints, PetscReal a, PetscReal b, PetscReal *points[], PetscReal *weights[]) 295 { 296 PetscReal *px, *wx, *py, *wy, *pz, *wz, *x, *w; 297 PetscInt i, j, k; 298 PetscErrorCode ierr; 299 300 PetscFunctionBegin; 301 if ((a != -1.0) || (b != 1.0)) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Must use default internal right now"); 302 switch (dim) { 303 case 1: 304 ierr = PetscMalloc(npoints * sizeof(PetscReal), &x);CHKERRQ(ierr); 305 ierr = PetscMalloc(npoints * sizeof(PetscReal), &w);CHKERRQ(ierr); 306 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 0.0, 0.0, x, w);CHKERRQ(ierr); 307 break; 308 case 2: 309 ierr = PetscMalloc(npoints*npoints*2 * sizeof(PetscReal), &x);CHKERRQ(ierr); 310 ierr = PetscMalloc(npoints*npoints * sizeof(PetscReal), &w);CHKERRQ(ierr); 311 ierr = PetscMalloc4(npoints,PetscReal,&px,npoints,PetscReal,&wx,npoints,PetscReal,&py,npoints,PetscReal,&wy);CHKERRQ(ierr); 312 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 0.0, 0.0, px, wx);CHKERRQ(ierr); 313 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 1.0, 0.0, py, wy);CHKERRQ(ierr); 314 for (i = 0; i < npoints; ++i) { 315 for (j = 0; j < npoints; ++j) { 316 ierr = PetscDTMapSquareToTriangle_Internal(px[i], py[j], &x[(i*npoints+j)*2+0], &x[(i*npoints+j)*2+1]);CHKERRQ(ierr); 317 w[i*npoints+j] = 0.5 * wx[i] * wy[j]; 318 } 319 } 320 ierr = PetscFree4(px,wx,py,wy);CHKERRQ(ierr); 321 break; 322 case 3: 323 ierr = PetscMalloc(npoints*npoints*3 * sizeof(PetscReal), &x);CHKERRQ(ierr); 324 ierr = PetscMalloc(npoints*npoints * sizeof(PetscReal), &w);CHKERRQ(ierr); 325 ierr = PetscMalloc6(npoints,PetscReal,&px,npoints,PetscReal,&wx,npoints,PetscReal,&py,npoints,PetscReal,&wy,npoints,PetscReal,&pz,npoints,PetscReal,&wz);CHKERRQ(ierr); 326 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 0.0, 0.0, px, wx);CHKERRQ(ierr); 327 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 1.0, 0.0, py, wy);CHKERRQ(ierr); 328 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 2.0, 0.0, pz, wz);CHKERRQ(ierr); 329 for (i = 0; i < npoints; ++i) { 330 for (j = 0; j < npoints; ++j) { 331 for (k = 0; k < npoints; ++k) { 332 ierr = PetscDTMapCubeToTetrahedron_Internal(px[i], py[j], pz[k], &x[((i*npoints+j)*npoints+k)*3+0], &x[((i*npoints+j)*npoints+k)*3+1], &x[((i*npoints+j)*npoints+k)*3+2]);CHKERRQ(ierr); 333 w[(i*npoints+j)*npoints+k] = 0.125 * wx[i] * wy[j] * wz[k]; 334 } 335 } 336 } 337 ierr = PetscFree6(px,wx,py,wy,pz,wz);CHKERRQ(ierr); 338 break; 339 default: 340 SETERRQ1(PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Cannot construct quadrature rule for dimension %d", dim); 341 } 342 if (points) *points = x; 343 if (weights) *weights = w; 344 PetscFunctionReturn(0); 345 } 346 347 #undef __FUNCT__ 348 #define __FUNCT__ "PetscDTPseudoInverseQR" 349 /* Overwrites A. Can only handle full-rank problems with m>=n 350 * A in column-major format 351 * Ainv in row-major format 352 * tau has length m 353 * worksize must be >= max(1,n) 354 */ 355 static PetscErrorCode PetscDTPseudoInverseQR(PetscInt m,PetscInt mstride,PetscInt n,PetscReal *A_in,PetscReal *Ainv_out,PetscScalar *tau,PetscInt worksize,PetscScalar *work) 356 { 357 PetscErrorCode ierr; 358 PetscBLASInt M,N,K,lda,ldb,ldwork,info; 359 PetscScalar *A,*Ainv,*R,*Q,Alpha; 360 361 PetscFunctionBegin; 362 #if defined(PETSC_USE_COMPLEX) 363 { 364 PetscInt i,j; 365 ierr = PetscMalloc2(m*n,PetscScalar,&A,m*n,PetscScalar,&Ainv);CHKERRQ(ierr); 366 for (j=0; j<n; j++) { 367 for (i=0; i<m; i++) A[i+m*j] = A_in[i+mstride*j]; 368 } 369 mstride = m; 370 } 371 #else 372 A = A_in; 373 Ainv = Ainv_out; 374 #endif 375 376 ierr = PetscBLASIntCast(m,&M);CHKERRQ(ierr); 377 ierr = PetscBLASIntCast(n,&N);CHKERRQ(ierr); 378 ierr = PetscBLASIntCast(mstride,&lda);CHKERRQ(ierr); 379 ierr = PetscBLASIntCast(worksize,&ldwork);CHKERRQ(ierr); 380 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 381 LAPACKgeqrf_(&M,&N,A,&lda,tau,work,&ldwork,&info); 382 ierr = PetscFPTrapPop();CHKERRQ(ierr); 383 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"xGEQRF error"); 384 R = A; /* Upper triangular part of A now contains R, the rest contains the elementary reflectors */ 385 386 /* Extract an explicit representation of Q */ 387 Q = Ainv; 388 ierr = PetscMemcpy(Q,A,mstride*n*sizeof(PetscScalar));CHKERRQ(ierr); 389 K = N; /* full rank */ 390 LAPACKungqr_(&M,&N,&K,Q,&lda,tau,work,&ldwork,&info); 391 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"xORGQR/xUNGQR error"); 392 393 /* Compute A^{-T} = (R^{-1} Q^T)^T = Q R^{-T} */ 394 Alpha = 1.0; 395 ldb = lda; 396 BLAStrsm_("Right","Upper","ConjugateTranspose","NotUnitTriangular",&M,&N,&Alpha,R,&lda,Q,&ldb); 397 /* Ainv is Q, overwritten with inverse */ 398 399 #if defined(PETSC_USE_COMPLEX) 400 { 401 PetscInt i; 402 for (i=0; i<m*n; i++) Ainv_out[i] = PetscRealPart(Ainv[i]); 403 ierr = PetscFree2(A,Ainv);CHKERRQ(ierr); 404 } 405 #endif 406 PetscFunctionReturn(0); 407 } 408 409 #undef __FUNCT__ 410 #define __FUNCT__ "PetscDTLegendreIntegrate" 411 /* Computes integral of L_p' over intervals {(x0,x1),(x1,x2),...} */ 412 static PetscErrorCode PetscDTLegendreIntegrate(PetscInt ninterval,const PetscReal *x,PetscInt ndegree,const PetscInt *degrees,PetscBool Transpose,PetscReal *B) 413 { 414 PetscErrorCode ierr; 415 PetscReal *Bv; 416 PetscInt i,j; 417 418 PetscFunctionBegin; 419 ierr = PetscMalloc((ninterval+1)*ndegree*sizeof(PetscReal),&Bv);CHKERRQ(ierr); 420 /* Point evaluation of L_p on all the source vertices */ 421 ierr = PetscDTLegendreEval(ninterval+1,x,ndegree,degrees,Bv,NULL,NULL);CHKERRQ(ierr); 422 /* Integral over each interval: \int_a^b L_p' = L_p(b)-L_p(a) */ 423 for (i=0; i<ninterval; i++) { 424 for (j=0; j<ndegree; j++) { 425 if (Transpose) B[i+ninterval*j] = Bv[(i+1)*ndegree+j] - Bv[i*ndegree+j]; 426 else B[i*ndegree+j] = Bv[(i+1)*ndegree+j] - Bv[i*ndegree+j]; 427 } 428 } 429 ierr = PetscFree(Bv);CHKERRQ(ierr); 430 PetscFunctionReturn(0); 431 } 432 433 #undef __FUNCT__ 434 #define __FUNCT__ "PetscDTReconstructPoly" 435 /*@ 436 PetscDTReconstructPoly - create matrix representing polynomial reconstruction using cell intervals and evaluation at target intervals 437 438 Not Collective 439 440 Input Arguments: 441 + degree - degree of reconstruction polynomial 442 . nsource - number of source intervals 443 . sourcex - sorted coordinates of source cell boundaries (length nsource+1) 444 . ntarget - number of target intervals 445 - targetx - sorted coordinates of target cell boundaries (length ntarget+1) 446 447 Output Arguments: 448 . R - reconstruction matrix, utarget = sum_s R[t*nsource+s] * usource[s] 449 450 Level: advanced 451 452 .seealso: PetscDTLegendreEval() 453 @*/ 454 PetscErrorCode PetscDTReconstructPoly(PetscInt degree,PetscInt nsource,const PetscReal *sourcex,PetscInt ntarget,const PetscReal *targetx,PetscReal *R) 455 { 456 PetscErrorCode ierr; 457 PetscInt i,j,k,*bdegrees,worksize; 458 PetscReal xmin,xmax,center,hscale,*sourcey,*targety,*Bsource,*Bsinv,*Btarget; 459 PetscScalar *tau,*work; 460 461 PetscFunctionBegin; 462 PetscValidRealPointer(sourcex,3); 463 PetscValidRealPointer(targetx,5); 464 PetscValidRealPointer(R,6); 465 if (degree >= nsource) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Reconstruction degree %D must be less than number of source intervals %D",degree,nsource); 466 #if defined(PETSC_USE_DEBUG) 467 for (i=0; i<nsource; i++) { 468 if (sourcex[i] >= sourcex[i+1]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_CORRUPT,"Source interval %D has negative orientation (%G,%G)",i,sourcex[i],sourcex[i+1]); 469 } 470 for (i=0; i<ntarget; i++) { 471 if (targetx[i] >= targetx[i+1]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_CORRUPT,"Target interval %D has negative orientation (%G,%G)",i,targetx[i],targetx[i+1]); 472 } 473 #endif 474 xmin = PetscMin(sourcex[0],targetx[0]); 475 xmax = PetscMax(sourcex[nsource],targetx[ntarget]); 476 center = (xmin + xmax)/2; 477 hscale = (xmax - xmin)/2; 478 worksize = nsource; 479 ierr = PetscMalloc4(degree+1,PetscInt,&bdegrees,nsource+1,PetscReal,&sourcey,nsource*(degree+1),PetscReal,&Bsource,worksize,PetscScalar,&work);CHKERRQ(ierr); 480 ierr = PetscMalloc4(nsource,PetscScalar,&tau,nsource*(degree+1),PetscReal,&Bsinv,ntarget+1,PetscReal,&targety,ntarget*(degree+1),PetscReal,&Btarget);CHKERRQ(ierr); 481 for (i=0; i<=nsource; i++) sourcey[i] = (sourcex[i]-center)/hscale; 482 for (i=0; i<=degree; i++) bdegrees[i] = i+1; 483 ierr = PetscDTLegendreIntegrate(nsource,sourcey,degree+1,bdegrees,PETSC_TRUE,Bsource);CHKERRQ(ierr); 484 ierr = PetscDTPseudoInverseQR(nsource,nsource,degree+1,Bsource,Bsinv,tau,nsource,work);CHKERRQ(ierr); 485 for (i=0; i<=ntarget; i++) targety[i] = (targetx[i]-center)/hscale; 486 ierr = PetscDTLegendreIntegrate(ntarget,targety,degree+1,bdegrees,PETSC_FALSE,Btarget);CHKERRQ(ierr); 487 for (i=0; i<ntarget; i++) { 488 PetscReal rowsum = 0; 489 for (j=0; j<nsource; j++) { 490 PetscReal sum = 0; 491 for (k=0; k<degree+1; k++) { 492 sum += Btarget[i*(degree+1)+k] * Bsinv[k*nsource+j]; 493 } 494 R[i*nsource+j] = sum; 495 rowsum += sum; 496 } 497 for (j=0; j<nsource; j++) R[i*nsource+j] /= rowsum; /* normalize each row */ 498 } 499 ierr = PetscFree4(bdegrees,sourcey,Bsource,work);CHKERRQ(ierr); 500 ierr = PetscFree4(tau,Bsinv,targety,Btarget);CHKERRQ(ierr); 501 PetscFunctionReturn(0); 502 } 503