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 = PetscRealView(npoints-1,w,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 118 ierr = PetscMalloc2(npoints*npoints,PetscScalar,&Z,PetscMax(1,2*npoints-2),PetscReal,&work);CHKERRQ(ierr); 119 ierr = PetscBLASIntCast(npoints,&N);CHKERRQ(ierr); 120 LDZ = N; 121 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 122 PetscStackCallBLAS("LAPACKsteqr",LAPACKsteqr_("I",&N,x,w,Z,&LDZ,work,&info)); 123 ierr = PetscFPTrapPop();CHKERRQ(ierr); 124 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"xSTEQR error"); 125 126 for (i=0; i<(npoints+1)/2; i++) { 127 PetscReal y = 0.5 * (-x[i] + x[npoints-i-1]); /* enforces symmetry */ 128 x[i] = (a+b)/2 - y*(b-a)/2; 129 x[npoints-i-1] = (a+b)/2 + y*(b-a)/2; 130 131 w[i] = w[npoints-1-i] = (b-a)*PetscSqr(0.5*PetscAbsScalar(Z[i*npoints] + Z[(npoints-i-1)*npoints])); 132 } 133 ierr = PetscFree2(Z,work);CHKERRQ(ierr); 134 PetscFunctionReturn(0); 135 } 136 137 #undef __FUNCT__ 138 #define __FUNCT__ "PetscDTFactorial_Internal" 139 /* Evaluates the nth jacobi polynomial with weight parameters a,b at a point x. 140 Recurrence relations implemented from the pseudocode given in Karniadakis and Sherwin, Appendix B */ 141 PETSC_STATIC_INLINE PetscErrorCode PetscDTFactorial_Internal(PetscInt n, PetscReal *factorial) 142 { 143 PetscReal f = 1.0; 144 PetscInt i; 145 146 PetscFunctionBegin; 147 for (i = 1; i < n+1; ++i) f *= i; 148 *factorial = f; 149 PetscFunctionReturn(0); 150 } 151 152 #undef __FUNCT__ 153 #define __FUNCT__ "PetscDTComputeJacobi" 154 /* Evaluates the nth jacobi polynomial with weight parameters a,b at a point x. 155 Recurrence relations implemented from the pseudocode given in Karniadakis and Sherwin, Appendix B */ 156 PETSC_STATIC_INLINE PetscErrorCode PetscDTComputeJacobi(PetscReal a, PetscReal b, PetscInt n, PetscReal x, PetscReal *P) 157 { 158 PetscReal apb, pn1, pn2; 159 PetscInt k; 160 161 PetscFunctionBegin; 162 if (!n) {*P = 1.0; PetscFunctionReturn(0);} 163 if (n == 1) {*P = 0.5 * (a - b + (a + b + 2.0) * x); PetscFunctionReturn(0);} 164 apb = a + b; 165 pn2 = 1.0; 166 pn1 = 0.5 * (a - b + (apb + 2.0) * x); 167 *P = 0.0; 168 for (k = 2; k < n+1; ++k) { 169 PetscReal a1 = 2.0 * k * (k + apb) * (2.0*k + apb - 2.0); 170 PetscReal a2 = (2.0 * k + apb - 1.0) * (a*a - b*b); 171 PetscReal a3 = (2.0 * k + apb - 2.0) * (2.0 * k + apb - 1.0) * (2.0 * k + apb); 172 PetscReal a4 = 2.0 * (k + a - 1.0) * (k + b - 1.0) * (2.0 * k + apb); 173 174 a2 = a2 / a1; 175 a3 = a3 / a1; 176 a4 = a4 / a1; 177 *P = (a2 + a3 * x) * pn1 - a4 * pn2; 178 pn2 = pn1; 179 pn1 = *P; 180 } 181 PetscFunctionReturn(0); 182 } 183 184 #undef __FUNCT__ 185 #define __FUNCT__ "PetscDTComputeJacobiDerivative" 186 /* Evaluates the first derivative of P_{n}^{a,b} at a point x. */ 187 PETSC_STATIC_INLINE PetscErrorCode PetscDTComputeJacobiDerivative(PetscReal a, PetscReal b, PetscInt n, PetscReal x, PetscReal *P) 188 { 189 PetscReal nP; 190 PetscErrorCode ierr; 191 192 PetscFunctionBegin; 193 if (!n) {*P = 0.0; PetscFunctionReturn(0);} 194 ierr = PetscDTComputeJacobi(a+1, b+1, n-1, x, &nP);CHKERRQ(ierr); 195 *P = 0.5 * (a + b + n + 1) * nP; 196 PetscFunctionReturn(0); 197 } 198 199 #undef __FUNCT__ 200 #define __FUNCT__ "PetscDTMapSquareToTriangle_Internal" 201 /* Maps from [-1,1]^2 to the (-1,1) reference triangle */ 202 PETSC_STATIC_INLINE PetscErrorCode PetscDTMapSquareToTriangle_Internal(PetscReal x, PetscReal y, PetscReal *xi, PetscReal *eta) 203 { 204 PetscFunctionBegin; 205 *xi = 0.5 * (1.0 + x) * (1.0 - y) - 1.0; 206 *eta = y; 207 PetscFunctionReturn(0); 208 } 209 210 #undef __FUNCT__ 211 #define __FUNCT__ "PetscDTMapCubeToTetrahedron_Internal" 212 /* Maps from [-1,1]^2 to the (-1,1) reference triangle */ 213 PETSC_STATIC_INLINE PetscErrorCode PetscDTMapCubeToTetrahedron_Internal(PetscReal x, PetscReal y, PetscReal z, PetscReal *xi, PetscReal *eta, PetscReal *zeta) 214 { 215 PetscFunctionBegin; 216 *xi = 0.25 * (1.0 + x) * (1.0 - y) * (1.0 - z) - 1.0; 217 *eta = 0.5 * (1.0 + y) * (1.0 - z) - 1.0; 218 *zeta = z; 219 PetscFunctionReturn(0); 220 } 221 222 #undef __FUNCT__ 223 #define __FUNCT__ "PetscDTGaussJacobiQuadrature1D_Internal" 224 static PetscErrorCode PetscDTGaussJacobiQuadrature1D_Internal(PetscInt npoints, PetscReal a, PetscReal b, PetscReal *x, PetscReal *w) 225 { 226 PetscInt maxIter = 100; 227 PetscReal eps = 1.0e-8; 228 PetscReal a1, a2, a3, a4, a5, a6; 229 PetscInt k; 230 PetscErrorCode ierr; 231 232 PetscFunctionBegin; 233 234 a1 = pow(2, a+b+1); 235 #if defined(PETSC_HAVE_TGAMMA) 236 a2 = tgamma(a + npoints + 1); 237 a3 = tgamma(b + npoints + 1); 238 a4 = tgamma(a + b + npoints + 1); 239 #else 240 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"tgamma() - math routine is unavailable."); 241 #endif 242 243 ierr = PetscDTFactorial_Internal(npoints, &a5);CHKERRQ(ierr); 244 a6 = a1 * a2 * a3 / a4 / a5; 245 /* Computes the m roots of P_{m}^{a,b} on [-1,1] by Newton's method with Chebyshev points as initial guesses. 246 Algorithm implemented from the pseudocode given by Karniadakis and Sherwin and Python in FIAT */ 247 for (k = 0; k < npoints; ++k) { 248 PetscReal r = -cos((2.0*k + 1.0) * PETSC_PI / (2.0 * npoints)), dP; 249 PetscInt j; 250 251 if (k > 0) r = 0.5 * (r + x[k-1]); 252 for (j = 0; j < maxIter; ++j) { 253 PetscReal s = 0.0, delta, f, fp; 254 PetscInt i; 255 256 for (i = 0; i < k; ++i) s = s + 1.0 / (r - x[i]); 257 ierr = PetscDTComputeJacobi(a, b, npoints, r, &f);CHKERRQ(ierr); 258 ierr = PetscDTComputeJacobiDerivative(a, b, npoints, r, &fp);CHKERRQ(ierr); 259 delta = f / (fp - f * s); 260 r = r - delta; 261 if (fabs(delta) < eps) break; 262 } 263 x[k] = r; 264 ierr = PetscDTComputeJacobiDerivative(a, b, npoints, x[k], &dP);CHKERRQ(ierr); 265 w[k] = a6 / (1.0 - PetscSqr(x[k])) / PetscSqr(dP); 266 } 267 PetscFunctionReturn(0); 268 } 269 270 #undef __FUNCT__ 271 #define __FUNCT__ "PetscDTGaussJacobiQuadrature" 272 /*@C 273 PetscDTGaussJacobiQuadrature - create Gauss-Jacobi quadrature for a simplex 274 275 Not Collective 276 277 Input Arguments: 278 + dim - The simplex dimension 279 . npoints - number of points 280 . a - left end of interval (often-1) 281 - b - right end of interval (often +1) 282 283 Output Arguments: 284 + points - quadrature points 285 - weights - quadrature weights 286 287 Level: intermediate 288 289 References: 290 Karniadakis and Sherwin. 291 FIAT 292 293 .seealso: PetscDTGaussQuadrature() 294 @*/ 295 PetscErrorCode PetscDTGaussJacobiQuadrature(PetscInt dim, PetscInt npoints, PetscReal a, PetscReal b, PetscReal *points[], PetscReal *weights[]) 296 { 297 PetscReal *px, *wx, *py, *wy, *pz, *wz, *x, *w; 298 PetscInt i, j, k; 299 PetscErrorCode ierr; 300 301 PetscFunctionBegin; 302 if ((a != -1.0) || (b != 1.0)) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Must use default internal right now"); 303 switch (dim) { 304 case 1: 305 ierr = PetscMalloc(npoints * sizeof(PetscReal), &x);CHKERRQ(ierr); 306 ierr = PetscMalloc(npoints * sizeof(PetscReal), &w);CHKERRQ(ierr); 307 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 0.0, 0.0, x, w);CHKERRQ(ierr); 308 break; 309 case 2: 310 ierr = PetscMalloc(npoints*npoints*2 * sizeof(PetscReal), &x);CHKERRQ(ierr); 311 ierr = PetscMalloc(npoints*npoints * sizeof(PetscReal), &w);CHKERRQ(ierr); 312 ierr = PetscMalloc4(npoints,PetscReal,&px,npoints,PetscReal,&wx,npoints,PetscReal,&py,npoints,PetscReal,&wy);CHKERRQ(ierr); 313 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 0.0, 0.0, px, wx);CHKERRQ(ierr); 314 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 1.0, 0.0, py, wy);CHKERRQ(ierr); 315 for (i = 0; i < npoints; ++i) { 316 for (j = 0; j < npoints; ++j) { 317 ierr = PetscDTMapSquareToTriangle_Internal(px[i], py[j], &x[(i*npoints+j)*2+0], &x[(i*npoints+j)*2+1]);CHKERRQ(ierr); 318 w[i*npoints+j] = 0.5 * wx[i] * wy[j]; 319 } 320 } 321 ierr = PetscFree4(px,wx,py,wy);CHKERRQ(ierr); 322 break; 323 case 3: 324 ierr = PetscMalloc(npoints*npoints*3 * sizeof(PetscReal), &x);CHKERRQ(ierr); 325 ierr = PetscMalloc(npoints*npoints * sizeof(PetscReal), &w);CHKERRQ(ierr); 326 ierr = PetscMalloc6(npoints,PetscReal,&px,npoints,PetscReal,&wx,npoints,PetscReal,&py,npoints,PetscReal,&wy,npoints,PetscReal,&pz,npoints,PetscReal,&wz);CHKERRQ(ierr); 327 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 0.0, 0.0, px, wx);CHKERRQ(ierr); 328 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 1.0, 0.0, py, wy);CHKERRQ(ierr); 329 ierr = PetscDTGaussJacobiQuadrature1D_Internal(npoints, 2.0, 0.0, pz, wz);CHKERRQ(ierr); 330 for (i = 0; i < npoints; ++i) { 331 for (j = 0; j < npoints; ++j) { 332 for (k = 0; k < npoints; ++k) { 333 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); 334 w[(i*npoints+j)*npoints+k] = 0.125 * wx[i] * wy[j] * wz[k]; 335 } 336 } 337 } 338 ierr = PetscFree6(px,wx,py,wy,pz,wz);CHKERRQ(ierr); 339 break; 340 default: 341 SETERRQ1(PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Cannot construct quadrature rule for dimension %d", dim); 342 } 343 if (points) *points = x; 344 if (weights) *weights = w; 345 PetscFunctionReturn(0); 346 } 347 348 #undef __FUNCT__ 349 #define __FUNCT__ "PetscDTPseudoInverseQR" 350 /* Overwrites A. Can only handle full-rank problems with m>=n 351 * A in column-major format 352 * Ainv in row-major format 353 * tau has length m 354 * worksize must be >= max(1,n) 355 */ 356 static PetscErrorCode PetscDTPseudoInverseQR(PetscInt m,PetscInt mstride,PetscInt n,PetscReal *A_in,PetscReal *Ainv_out,PetscScalar *tau,PetscInt worksize,PetscScalar *work) 357 { 358 PetscErrorCode ierr; 359 PetscBLASInt M,N,K,lda,ldb,ldwork,info; 360 PetscScalar *A,*Ainv,*R,*Q,Alpha; 361 362 PetscFunctionBegin; 363 #if defined(PETSC_USE_COMPLEX) 364 { 365 PetscInt i,j; 366 ierr = PetscMalloc2(m*n,PetscScalar,&A,m*n,PetscScalar,&Ainv);CHKERRQ(ierr); 367 for (j=0; j<n; j++) { 368 for (i=0; i<m; i++) A[i+m*j] = A_in[i+mstride*j]; 369 } 370 mstride = m; 371 } 372 #else 373 A = A_in; 374 Ainv = Ainv_out; 375 #endif 376 377 ierr = PetscBLASIntCast(m,&M);CHKERRQ(ierr); 378 ierr = PetscBLASIntCast(n,&N);CHKERRQ(ierr); 379 ierr = PetscBLASIntCast(mstride,&lda);CHKERRQ(ierr); 380 ierr = PetscBLASIntCast(worksize,&ldwork);CHKERRQ(ierr); 381 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 382 LAPACKgeqrf_(&M,&N,A,&lda,tau,work,&ldwork,&info); 383 ierr = PetscFPTrapPop();CHKERRQ(ierr); 384 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"xGEQRF error"); 385 R = A; /* Upper triangular part of A now contains R, the rest contains the elementary reflectors */ 386 387 /* Extract an explicit representation of Q */ 388 Q = Ainv; 389 ierr = PetscMemcpy(Q,A,mstride*n*sizeof(PetscScalar));CHKERRQ(ierr); 390 K = N; /* full rank */ 391 LAPACKungqr_(&M,&N,&K,Q,&lda,tau,work,&ldwork,&info); 392 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"xORGQR/xUNGQR error"); 393 394 /* Compute A^{-T} = (R^{-1} Q^T)^T = Q R^{-T} */ 395 Alpha = 1.0; 396 ldb = lda; 397 BLAStrsm_("Right","Upper","ConjugateTranspose","NotUnitTriangular",&M,&N,&Alpha,R,&lda,Q,&ldb); 398 /* Ainv is Q, overwritten with inverse */ 399 400 #if defined(PETSC_USE_COMPLEX) 401 { 402 PetscInt i; 403 for (i=0; i<m*n; i++) Ainv_out[i] = PetscRealPart(Ainv[i]); 404 ierr = PetscFree2(A,Ainv);CHKERRQ(ierr); 405 } 406 #endif 407 PetscFunctionReturn(0); 408 } 409 410 #undef __FUNCT__ 411 #define __FUNCT__ "PetscDTLegendreIntegrate" 412 /* Computes integral of L_p' over intervals {(x0,x1),(x1,x2),...} */ 413 static PetscErrorCode PetscDTLegendreIntegrate(PetscInt ninterval,const PetscReal *x,PetscInt ndegree,const PetscInt *degrees,PetscBool Transpose,PetscReal *B) 414 { 415 PetscErrorCode ierr; 416 PetscReal *Bv; 417 PetscInt i,j; 418 419 PetscFunctionBegin; 420 ierr = PetscMalloc((ninterval+1)*ndegree*sizeof(PetscReal),&Bv);CHKERRQ(ierr); 421 /* Point evaluation of L_p on all the source vertices */ 422 ierr = PetscDTLegendreEval(ninterval+1,x,ndegree,degrees,Bv,NULL,NULL);CHKERRQ(ierr); 423 /* Integral over each interval: \int_a^b L_p' = L_p(b)-L_p(a) */ 424 for (i=0; i<ninterval; i++) { 425 for (j=0; j<ndegree; j++) { 426 if (Transpose) B[i+ninterval*j] = Bv[(i+1)*ndegree+j] - Bv[i*ndegree+j]; 427 else B[i*ndegree+j] = Bv[(i+1)*ndegree+j] - Bv[i*ndegree+j]; 428 } 429 } 430 ierr = PetscFree(Bv);CHKERRQ(ierr); 431 PetscFunctionReturn(0); 432 } 433 434 #undef __FUNCT__ 435 #define __FUNCT__ "PetscDTReconstructPoly" 436 /*@ 437 PetscDTReconstructPoly - create matrix representing polynomial reconstruction using cell intervals and evaluation at target intervals 438 439 Not Collective 440 441 Input Arguments: 442 + degree - degree of reconstruction polynomial 443 . nsource - number of source intervals 444 . sourcex - sorted coordinates of source cell boundaries (length nsource+1) 445 . ntarget - number of target intervals 446 - targetx - sorted coordinates of target cell boundaries (length ntarget+1) 447 448 Output Arguments: 449 . R - reconstruction matrix, utarget = sum_s R[t*nsource+s] * usource[s] 450 451 Level: advanced 452 453 .seealso: PetscDTLegendreEval() 454 @*/ 455 PetscErrorCode PetscDTReconstructPoly(PetscInt degree,PetscInt nsource,const PetscReal *sourcex,PetscInt ntarget,const PetscReal *targetx,PetscReal *R) 456 { 457 PetscErrorCode ierr; 458 PetscInt i,j,k,*bdegrees,worksize; 459 PetscReal xmin,xmax,center,hscale,*sourcey,*targety,*Bsource,*Bsinv,*Btarget; 460 PetscScalar *tau,*work; 461 462 PetscFunctionBegin; 463 PetscValidRealPointer(sourcex,3); 464 PetscValidRealPointer(targetx,5); 465 PetscValidRealPointer(R,6); 466 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); 467 #if defined(PETSC_USE_DEBUG) 468 for (i=0; i<nsource; i++) { 469 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]); 470 } 471 for (i=0; i<ntarget; i++) { 472 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]); 473 } 474 #endif 475 xmin = PetscMin(sourcex[0],targetx[0]); 476 xmax = PetscMax(sourcex[nsource],targetx[ntarget]); 477 center = (xmin + xmax)/2; 478 hscale = (xmax - xmin)/2; 479 worksize = nsource; 480 ierr = PetscMalloc4(degree+1,PetscInt,&bdegrees,nsource+1,PetscReal,&sourcey,nsource*(degree+1),PetscReal,&Bsource,worksize,PetscScalar,&work);CHKERRQ(ierr); 481 ierr = PetscMalloc4(nsource,PetscScalar,&tau,nsource*(degree+1),PetscReal,&Bsinv,ntarget+1,PetscReal,&targety,ntarget*(degree+1),PetscReal,&Btarget);CHKERRQ(ierr); 482 for (i=0; i<=nsource; i++) sourcey[i] = (sourcex[i]-center)/hscale; 483 for (i=0; i<=degree; i++) bdegrees[i] = i+1; 484 ierr = PetscDTLegendreIntegrate(nsource,sourcey,degree+1,bdegrees,PETSC_TRUE,Bsource);CHKERRQ(ierr); 485 ierr = PetscDTPseudoInverseQR(nsource,nsource,degree+1,Bsource,Bsinv,tau,nsource,work);CHKERRQ(ierr); 486 for (i=0; i<=ntarget; i++) targety[i] = (targetx[i]-center)/hscale; 487 ierr = PetscDTLegendreIntegrate(ntarget,targety,degree+1,bdegrees,PETSC_FALSE,Btarget);CHKERRQ(ierr); 488 for (i=0; i<ntarget; i++) { 489 PetscReal rowsum = 0; 490 for (j=0; j<nsource; j++) { 491 PetscReal sum = 0; 492 for (k=0; k<degree+1; k++) { 493 sum += Btarget[i*(degree+1)+k] * Bsinv[k*nsource+j]; 494 } 495 R[i*nsource+j] = sum; 496 rowsum += sum; 497 } 498 for (j=0; j<nsource; j++) R[i*nsource+j] /= rowsum; /* normalize each row */ 499 } 500 ierr = PetscFree4(bdegrees,sourcey,Bsource,work);CHKERRQ(ierr); 501 ierr = PetscFree4(tau,Bsinv,targety,Btarget);CHKERRQ(ierr); 502 PetscFunctionReturn(0); 503 } 504