1 2 #ifdef PETSC_RCS_HEADER 3 static char vcid[] = "$Id: fdmatrix.c,v 1.47 1999/05/12 03:30:49 bsmith Exp balay $"; 4 #endif 5 6 /* 7 This is where the abstract matrix operations are defined that are 8 used for finite difference computations of Jacobians using coloring. 9 */ 10 11 #include "petsc.h" 12 #include "src/mat/matimpl.h" /*I "mat.h" I*/ 13 #include "src/vec/vecimpl.h" 14 15 #undef __FUNC__ 16 #define __FUNC__ "MatFDColoringView_Draw" 17 static int MatFDColoringView_Draw(MatFDColoring fd,Viewer viewer) 18 { 19 int ierr,i,j,pause; 20 PetscTruth isnull; 21 Draw draw; 22 double xr,yr,xl,yl,h,w,x,y,xc,yc,scale = 0.0; 23 DrawButton button; 24 25 PetscFunctionBegin; 26 ierr = ViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 27 ierr = DrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 28 ierr = DrawSynchronizedClear(draw);CHKERRQ(ierr); 29 30 xr = fd->N; yr = fd->M; h = yr/10.0; w = xr/10.0; 31 xr += w; yr += h; xl = -w; yl = -h; 32 ierr = DrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 33 34 /* loop over colors */ 35 for (i=0; i<fd->ncolors; i++ ) { 36 for ( j=0; j<fd->nrows[i]; j++ ) { 37 y = fd->M - fd->rows[i][j] - fd->rstart; 38 x = fd->columnsforrow[i][j]; 39 ierr = DrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr); 40 } 41 } 42 ierr = DrawSynchronizedFlush(draw);CHKERRQ(ierr); 43 ierr = DrawGetPause(draw,&pause);CHKERRQ(ierr); 44 if (pause >= 0) { PetscSleep(pause); PetscFunctionReturn(0);} 45 ierr = DrawCheckResizedWindow(draw);CHKERRQ(ierr); 46 ierr = DrawSynchronizedGetMouseButton(draw,&button,&xc,&yc,0,0);CHKERRQ(ierr); 47 while (button != BUTTON_RIGHT) { 48 ierr = DrawSynchronizedClear(draw);CHKERRQ(ierr); 49 if (button == BUTTON_LEFT) scale = .5; 50 else if (button == BUTTON_CENTER) scale = 2.; 51 xl = scale*(xl + w - xc) + xc - w*scale; 52 xr = scale*(xr - w - xc) + xc + w*scale; 53 yl = scale*(yl + h - yc) + yc - h*scale; 54 yr = scale*(yr - h - yc) + yc + h*scale; 55 w *= scale; h *= scale; 56 ierr = DrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 57 /* loop over colors */ 58 for (i=0; i<fd->ncolors; i++ ) { 59 for ( j=0; j<fd->nrows[i]; j++ ) { 60 y = fd->M - fd->rows[i][j] - fd->rstart; 61 x = fd->columnsforrow[i][j]; 62 ierr = DrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr); 63 } 64 } 65 ierr = DrawCheckResizedWindow(draw);CHKERRQ(ierr); 66 ierr = DrawSynchronizedGetMouseButton(draw,&button,&xc,&yc,0,0);CHKERRQ(ierr); 67 } 68 69 PetscFunctionReturn(0); 70 } 71 72 #undef __FUNC__ 73 #define __FUNC__ "MatFDColoringView" 74 /*@C 75 MatFDColoringView - Views a finite difference coloring context. 76 77 Collective on MatFDColoring unless Viewer is VIEWER_STDOUT_SELF 78 79 Input Parameters: 80 + c - the coloring context 81 - viewer - visualization context 82 83 Level: intermediate 84 85 Notes: 86 The available visualization contexts include 87 + VIEWER_STDOUT_SELF - standard output (default) 88 . VIEWER_STDOUT_WORLD - synchronized standard 89 output where only the first processor opens 90 the file. All other processors send their 91 data to the first processor to print. 92 - VIEWER_DRAW_WORLD - graphical display of nonzero structure 93 94 .seealso: MatFDColoringCreate() 95 96 .keywords: Mat, finite differences, coloring, view 97 @*/ 98 int MatFDColoringView(MatFDColoring c,Viewer viewer) 99 { 100 ViewerType vtype; 101 int i,j,format,ierr; 102 103 PetscFunctionBegin; 104 PetscValidHeaderSpecific(c,MAT_FDCOLORING_COOKIE); 105 if (viewer) {PetscValidHeader(viewer);} 106 else {viewer = VIEWER_STDOUT_SELF;} 107 108 ierr = ViewerGetType(viewer,&vtype);CHKERRQ(ierr); 109 if (PetscTypeCompare(vtype,DRAW_VIEWER)) { 110 ierr = MatFDColoringView_Draw(c,viewer);CHKERRQ(ierr); 111 PetscFunctionReturn(0); 112 } else if (PetscTypeCompare(vtype,ASCII_VIEWER)) { 113 ierr = ViewerASCIIPrintf(viewer,"MatFDColoring Object:\n");CHKERRQ(ierr); 114 ierr = ViewerASCIIPrintf(viewer," Error tolerance=%g\n",c->error_rel);CHKERRQ(ierr); 115 ierr = ViewerASCIIPrintf(viewer," Umin=%g\n",c->umin);CHKERRQ(ierr); 116 ierr = ViewerASCIIPrintf(viewer," Number of colors=%d\n",c->ncolors);CHKERRQ(ierr); 117 118 ierr = ViewerGetFormat(viewer,&format);CHKERRQ(ierr); 119 if (format != VIEWER_FORMAT_ASCII_INFO) { 120 for ( i=0; i<c->ncolors; i++ ) { 121 ierr = ViewerASCIIPrintf(viewer," Information for color %d\n",i);CHKERRQ(ierr); 122 ierr = ViewerASCIIPrintf(viewer," Number of columns %d\n",c->ncolumns[i]);CHKERRQ(ierr); 123 for ( j=0; j<c->ncolumns[i]; j++ ) { 124 ierr = ViewerASCIIPrintf(viewer," %d\n",c->columns[i][j]);CHKERRQ(ierr); 125 } 126 ierr = ViewerASCIIPrintf(viewer," Number of rows %d\n",c->nrows[i]);CHKERRQ(ierr); 127 for ( j=0; j<c->nrows[i]; j++ ) { 128 ierr = ViewerASCIIPrintf(viewer," %d %d \n",c->rows[i][j],c->columnsforrow[i][j]);CHKERRQ(ierr); 129 } 130 } 131 } 132 } else { 133 SETERRQ(1,1,"Viewer type not supported for this object"); 134 } 135 PetscFunctionReturn(0); 136 } 137 138 #undef __FUNC__ 139 #define __FUNC__ "MatFDColoringSetParameters" 140 /*@ 141 MatFDColoringSetParameters - Sets the parameters for the sparse approximation of 142 a Jacobian matrix using finite differences. 143 144 Collective on MatFDColoring 145 146 The Jacobian is estimated with the differencing approximation 147 .vb 148 F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where 149 h = error_rel*u[i] if abs(u[i]) > umin 150 = +/- error_rel*umin otherwise, with +/- determined by the sign of u[i] 151 dx_{i} = (0, ... 1, .... 0) 152 .ve 153 154 Input Parameters: 155 + coloring - the coloring context 156 . error_rel - relative error 157 - umin - minimum allowable u-value magnitude 158 159 Level: advanced 160 161 .keywords: Mat, finite differences, coloring, set, parameters 162 163 .seealso: MatFDColoringCreate() 164 @*/ 165 int MatFDColoringSetParameters(MatFDColoring matfd,double error,double umin) 166 { 167 PetscFunctionBegin; 168 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 169 170 if (error != PETSC_DEFAULT) matfd->error_rel = error; 171 if (umin != PETSC_DEFAULT) matfd->umin = umin; 172 PetscFunctionReturn(0); 173 } 174 175 #undef __FUNC__ 176 #define __FUNC__ "MatFDColoringSetFrequency" 177 /*@ 178 MatFDColoringSetFrequency - Sets the frequency for computing new Jacobian 179 matrices. 180 181 Collective on MatFDColoring 182 183 Input Parameters: 184 + coloring - the coloring context 185 - freq - frequency (default is 1) 186 187 Options Database Keys: 188 . -mat_fd_coloring_freq <freq> - Sets coloring frequency 189 190 Level: advanced 191 192 Notes: 193 Using a modified Newton strategy, where the Jacobian remains fixed for several 194 iterations, can be cost effective in terms of overall nonlinear solution 195 efficiency. This parameter indicates that a new Jacobian will be computed every 196 <freq> nonlinear iterations. 197 198 .keywords: Mat, finite differences, coloring, set, frequency 199 200 .seealso: MatFDColoringCreate(), MatFDColoringGetFrequency() 201 @*/ 202 int MatFDColoringSetFrequency(MatFDColoring matfd,int freq) 203 { 204 PetscFunctionBegin; 205 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 206 207 matfd->freq = freq; 208 PetscFunctionReturn(0); 209 } 210 211 #undef __FUNC__ 212 #define __FUNC__ "MatFDColoringGetFrequency" 213 /*@ 214 MatFDColoringGetFrequency - Gets the frequency for computing new Jacobian 215 matrices. 216 217 Not Collective 218 219 Input Parameters: 220 . coloring - the coloring context 221 222 Output Parameters: 223 . freq - frequency (default is 1) 224 225 Options Database Keys: 226 . -mat_fd_coloring_freq <freq> - Sets coloring frequency 227 228 Level: advanced 229 230 Notes: 231 Using a modified Newton strategy, where the Jacobian remains fixed for several 232 iterations, can be cost effective in terms of overall nonlinear solution 233 efficiency. This parameter indicates that a new Jacobian will be computed every 234 <freq> nonlinear iterations. 235 236 .keywords: Mat, finite differences, coloring, get, frequency 237 238 .seealso: MatFDColoringSetFrequency() 239 @*/ 240 int MatFDColoringGetFrequency(MatFDColoring matfd,int *freq) 241 { 242 PetscFunctionBegin; 243 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 244 245 *freq = matfd->freq; 246 PetscFunctionReturn(0); 247 } 248 249 #undef __FUNC__ 250 #define __FUNC__ "MatFDColoringSetFunction" 251 /*@C 252 MatFDColoringSetFunction - Sets the function to use for computing the Jacobian. 253 254 Collective on MatFDColoring 255 256 Input Parameters: 257 + coloring - the coloring context 258 . f - the function 259 - fctx - the optional user-defined function context 260 261 Level: intermediate 262 263 Notes: 264 In Fortran you must call MatFDColoringSetFunctionSNES() for a coloring object to 265 be used with the SNES solvers and MatFDColoringSetFunctionTS() if it is to be used 266 with the TS solvers. 267 268 .keywords: Mat, Jacobian, finite differences, set, function 269 @*/ 270 int MatFDColoringSetFunction(MatFDColoring matfd,int (*f)(void),void *fctx) 271 { 272 PetscFunctionBegin; 273 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 274 275 matfd->f = f; 276 matfd->fctx = fctx; 277 278 PetscFunctionReturn(0); 279 } 280 281 #undef __FUNC__ 282 #define __FUNC__ "MatFDColoringSetFromOptions" 283 /*@ 284 MatFDColoringSetFromOptions - Sets coloring finite difference parameters from 285 the options database. 286 287 Collective on MatFDColoring 288 289 The Jacobian, F'(u), is estimated with the differencing approximation 290 .vb 291 F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where 292 h = error_rel*u[i] if abs(u[i]) > umin 293 = +/- error_rel*umin otherwise, with +/- determined by the sign of u[i] 294 dx_{i} = (0, ... 1, .... 0) 295 .ve 296 297 Input Parameter: 298 . coloring - the coloring context 299 300 Options Database Keys: 301 + -mat_fd_coloring_error <err> - Sets <err> (square root 302 of relative error in the function) 303 . -mat_fd_coloring_umin <umin> - Sets umin, the minimum allowable u-value magnitude 304 . -mat_fd_coloring_freq <freq> - Sets frequency of computing a new Jacobian 305 . -mat_fd_coloring_view - Activates basic viewing 306 . -mat_fd_coloring_view_info - Activates viewing info 307 - -mat_fd_coloring_view_draw - Activates drawing 308 309 Level: intermediate 310 311 .keywords: Mat, finite differences, parameters 312 @*/ 313 int MatFDColoringSetFromOptions(MatFDColoring matfd) 314 { 315 int ierr,flag,freq = 1; 316 double error = PETSC_DEFAULT,umin = PETSC_DEFAULT; 317 318 PetscFunctionBegin; 319 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 320 321 ierr = OptionsGetDouble(matfd->prefix,"-mat_fd_coloring_err",&error,&flag);CHKERRQ(ierr); 322 ierr = OptionsGetDouble(matfd->prefix,"-mat_fd_coloring_umin",&umin,&flag);CHKERRQ(ierr); 323 ierr = MatFDColoringSetParameters(matfd,error,umin);CHKERRQ(ierr); 324 ierr = OptionsGetInt(matfd->prefix,"-mat_fd_coloring_freq",&freq,&flag);CHKERRQ(ierr); 325 ierr = MatFDColoringSetFrequency(matfd,freq);CHKERRQ(ierr); 326 ierr = OptionsHasName(PETSC_NULL,"-help",&flag);CHKERRQ(ierr); 327 if (flag) { 328 ierr = MatFDColoringPrintHelp(matfd);CHKERRQ(ierr); 329 } 330 PetscFunctionReturn(0); 331 } 332 333 #undef __FUNC__ 334 #define __FUNC__ "MatFDColoringPrintHelp" 335 /*@ 336 MatFDColoringPrintHelp - Prints help message for matrix finite difference calculations 337 using coloring. 338 339 Collective on MatFDColoring 340 341 Input Parameter: 342 . fdcoloring - the MatFDColoring context 343 344 Level: intermediate 345 346 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringSetFromOptions() 347 @*/ 348 int MatFDColoringPrintHelp(MatFDColoring fd) 349 { 350 int ierr; 351 352 PetscFunctionBegin; 353 PetscValidHeaderSpecific(fd,MAT_FDCOLORING_COOKIE); 354 355 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_err <err>: set sqrt rel tol in function, defaults to %g\n",fd->error_rel);CHKERRQ(ierr); 356 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_umin <umin>: see users manual, defaults to %d\n",fd->umin);CHKERRQ(ierr); 357 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_freq <freq>: frequency that Jacobian is recomputed, defaults to %d\n",fd->freq);CHKERRQ(ierr); 358 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view\n");CHKERRQ(ierr); 359 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view_draw\n");CHKERRQ(ierr); 360 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view_info\n");CHKERRQ(ierr); 361 PetscFunctionReturn(0); 362 } 363 364 int MatFDColoringView_Private(MatFDColoring fd) 365 { 366 int ierr,flg; 367 368 PetscFunctionBegin; 369 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view",&flg);CHKERRQ(ierr); 370 if (flg) { 371 ierr = MatFDColoringView(fd,VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr); 372 } 373 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view_info",&flg);CHKERRQ(ierr); 374 if (flg) { 375 ierr = ViewerPushFormat(VIEWER_STDOUT_(fd->comm),VIEWER_FORMAT_ASCII_INFO,PETSC_NULL);CHKERRQ(ierr); 376 ierr = MatFDColoringView(fd,VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr); 377 ierr = ViewerPopFormat(VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr); 378 } 379 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view_draw",&flg);CHKERRQ(ierr); 380 if (flg) { 381 ierr = MatFDColoringView(fd,VIEWER_DRAW_(fd->comm));CHKERRQ(ierr); 382 ierr = ViewerFlush(VIEWER_DRAW_(fd->comm));CHKERRQ(ierr); 383 } 384 PetscFunctionReturn(0); 385 } 386 387 #undef __FUNC__ 388 #define __FUNC__ "MatFDColoringCreate" 389 /*@C 390 MatFDColoringCreate - Creates a matrix coloring context for finite difference 391 computation of Jacobians. 392 393 Collective on Mat 394 395 Input Parameters: 396 + mat - the matrix containing the nonzero structure of the Jacobian 397 - iscoloring - the coloring of the matrix 398 399 Output Parameter: 400 . color - the new coloring context 401 402 Options Database Keys: 403 + -mat_fd_coloring_view - Activates basic viewing or coloring 404 . -mat_fd_coloring_view_draw - Activates drawing of coloring 405 - -mat_fd_coloring_view_info - Activates viewing of coloring info 406 407 Level: intermediate 408 409 .seealso: MatFDColoringDestroy() 410 @*/ 411 int MatFDColoringCreate(Mat mat,ISColoring iscoloring,MatFDColoring *color) 412 { 413 MatFDColoring c; 414 MPI_Comm comm; 415 int ierr,M,N; 416 417 PetscFunctionBegin; 418 ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr); 419 if (M != N) SETERRQ(PETSC_ERR_SUP,0,"Only for square matrices"); 420 421 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 422 PetscHeaderCreate(c,_p_MatFDColoring,int,MAT_FDCOLORING_COOKIE,0,"MatFDColoring",comm, 423 MatFDColoringDestroy,MatFDColoringView); 424 PLogObjectCreate(c); 425 426 if (mat->ops->fdcoloringcreate) { 427 ierr = (*mat->ops->fdcoloringcreate)(mat,iscoloring,c);CHKERRQ(ierr); 428 } else { 429 SETERRQ(PETSC_ERR_SUP,0,"Code not yet written for this matrix type"); 430 } 431 432 c->error_rel = 1.e-8; 433 c->umin = 1.e-6; 434 c->freq = 1; 435 436 ierr = MatFDColoringView_Private(c);CHKERRQ(ierr); 437 438 *color = c; 439 440 PetscFunctionReturn(0); 441 } 442 443 #undef __FUNC__ 444 #define __FUNC__ "MatFDColoringDestroy" 445 /*@C 446 MatFDColoringDestroy - Destroys a matrix coloring context that was created 447 via MatFDColoringCreate(). 448 449 Collective on MatFDColoring 450 451 Input Parameter: 452 . c - coloring context 453 454 Level: intermediate 455 456 .seealso: MatFDColoringCreate() 457 @*/ 458 int MatFDColoringDestroy(MatFDColoring c) 459 { 460 int i,ierr; 461 462 PetscFunctionBegin; 463 if (--c->refct > 0) PetscFunctionReturn(0); 464 465 466 for ( i=0; i<c->ncolors; i++ ) { 467 if (c->columns[i]) {ierr = PetscFree(c->columns[i]);CHKERRQ(ierr);} 468 if (c->rows[i]) {ierr = PetscFree(c->rows[i]);CHKERRQ(ierr);} 469 if (c->columnsforrow[i]) {ierr = PetscFree(c->columnsforrow[i]);CHKERRQ(ierr);} 470 } 471 ierr = PetscFree(c->ncolumns);CHKERRQ(ierr); 472 ierr = PetscFree(c->columns);CHKERRQ(ierr); 473 ierr = PetscFree(c->nrows);CHKERRQ(ierr); 474 ierr = PetscFree(c->rows);CHKERRQ(ierr); 475 ierr = PetscFree(c->columnsforrow);CHKERRQ(ierr); 476 ierr = PetscFree(c->scale);CHKERRQ(ierr); 477 if (c->w1) { 478 ierr = VecDestroy(c->w1);CHKERRQ(ierr); 479 ierr = VecDestroy(c->w2);CHKERRQ(ierr); 480 ierr = VecDestroy(c->w3);CHKERRQ(ierr); 481 } 482 PLogObjectDestroy(c); 483 PetscHeaderDestroy(c); 484 PetscFunctionReturn(0); 485 } 486 487 #include "snes.h" 488 489 #undef __FUNC__ 490 #define __FUNC__ "MatFDColoringApply" 491 /*@ 492 MatFDColoringApply - Given a matrix for which a MatFDColoring context 493 has been created, computes the Jacobian for a function via finite differences. 494 495 Collective on MatFDColoring 496 497 Input Parameters: 498 + mat - location to store Jacobian 499 . coloring - coloring context created with MatFDColoringCreate() 500 . x1 - location at which Jacobian is to be computed 501 - sctx - optional context required by function (actually a SNES context) 502 503 Options Database Keys: 504 . -mat_fd_coloring_freq <freq> - Sets coloring frequency 505 506 Level: intermediate 507 508 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView() 509 510 .keywords: coloring, Jacobian, finite differences 511 @*/ 512 int MatFDColoringApply(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 513 { 514 int k,fg,ierr,N,start,end,l,row,col,srow; 515 Scalar dx, mone = -1.0,*y,*scale = coloring->scale,*xx,*wscale = coloring->wscale; 516 double epsilon = coloring->error_rel, umin = coloring->umin; 517 MPI_Comm comm = coloring->comm; 518 Vec w1,w2,w3; 519 int (*f)(void *,Vec,Vec,void *) = ( int (*)(void *,Vec,Vec,void *))coloring->f; 520 void *fctx = coloring->fctx; 521 522 PetscFunctionBegin; 523 PetscValidHeaderSpecific(J,MAT_COOKIE); 524 PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_COOKIE); 525 PetscValidHeaderSpecific(x1,VEC_COOKIE); 526 527 528 if (!coloring->w1) { 529 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 530 PLogObjectParent(coloring,coloring->w1); 531 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 532 PLogObjectParent(coloring,coloring->w2); 533 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 534 PLogObjectParent(coloring,coloring->w3); 535 } 536 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 537 538 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&fg);CHKERRQ(ierr); 539 if (fg) { 540 PLogInfo(coloring,"MatFDColoringApply: Not calling MatZeroEntries()\n"); 541 } else { 542 ierr = MatZeroEntries(J);CHKERRQ(ierr); 543 } 544 545 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 546 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 547 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 548 549 ierr = PetscMemzero(wscale,N*sizeof(Scalar));CHKERRQ(ierr); 550 /* 551 Loop over each color 552 */ 553 554 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 555 for (k=0; k<coloring->ncolors; k++) { 556 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 557 /* 558 Loop over each column associated with color adding the 559 perturbation to the vector w3. 560 */ 561 for (l=0; l<coloring->ncolumns[k]; l++) { 562 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 563 dx = xx[col-start]; 564 if (dx == 0.0) dx = 1.0; 565 #if !defined(PETSC_USE_COMPLEX) 566 if (dx < umin && dx >= 0.0) dx = umin; 567 else if (dx < 0.0 && dx > -umin) dx = -umin; 568 #else 569 if (PetscAbsScalar(dx) < umin && PetscReal(dx) >= 0.0) dx = umin; 570 else if (PetscReal(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 571 #endif 572 dx *= epsilon; 573 wscale[col] = 1.0/dx; 574 ierr = VecSetValues(w3,1,&col,&dx,ADD_VALUES);CHKERRQ(ierr); 575 } 576 577 /* 578 Evaluate function at x1 + dx (here dx is a vector of perturbations) 579 */ 580 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 581 ierr = VecAXPY(&mone,w1,w2);CHKERRQ(ierr); 582 /* Communicate scale to all processors */ 583 #if !defined(PETSC_USE_COMPLEX) 584 ierr = MPI_Allreduce(wscale,scale,N,MPI_DOUBLE,MPI_SUM,comm);CHKERRQ(ierr); 585 #else 586 ierr = MPI_Allreduce(wscale,scale,2*N,MPI_DOUBLE,MPI_SUM,comm);CHKERRQ(ierr); 587 #endif 588 /* 589 Loop over rows of vector, putting results into Jacobian matrix 590 */ 591 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 592 for (l=0; l<coloring->nrows[k]; l++) { 593 row = coloring->rows[k][l]; 594 col = coloring->columnsforrow[k][l]; 595 y[row] *= scale[col]; 596 srow = row + start; 597 ierr = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 598 } 599 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 600 } 601 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 602 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 603 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 604 PetscFunctionReturn(0); 605 } 606 607 #include "ts.h" 608 609 #undef __FUNC__ 610 #define __FUNC__ "MatFDColoringApplyTS" 611 /*@ 612 MatFDColoringApplyTS - Given a matrix for which a MatFDColoring context 613 has been created, computes the Jacobian for a function via finite differences. 614 615 Collective on Mat, MatFDColoring, and Vec 616 617 Input Parameters: 618 + mat - location to store Jacobian 619 . coloring - coloring context created with MatFDColoringCreate() 620 . x1 - location at which Jacobian is to be computed 621 - sctx - optional context required by function (actually a SNES context) 622 623 Options Database Keys: 624 . -mat_fd_coloring_freq <freq> - Sets coloring frequency 625 626 Level: intermediate 627 628 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView() 629 630 .keywords: coloring, Jacobian, finite differences 631 @*/ 632 int MatFDColoringApplyTS(Mat J,MatFDColoring coloring,double t,Vec x1,MatStructure *flag,void *sctx) 633 { 634 int k,fg,ierr,N,start,end,l,row,col,srow; 635 Scalar dx, mone = -1.0,*y,*scale = coloring->scale,*xx,*wscale = coloring->wscale; 636 double epsilon = coloring->error_rel, umin = coloring->umin; 637 MPI_Comm comm = coloring->comm; 638 Vec w1,w2,w3; 639 int (*f)(void *,double,Vec,Vec,void *) = ( int (*)(void *,double,Vec,Vec,void *))coloring->f; 640 void *fctx = coloring->fctx; 641 642 PetscFunctionBegin; 643 PetscValidHeaderSpecific(J,MAT_COOKIE); 644 PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_COOKIE); 645 PetscValidHeaderSpecific(x1,VEC_COOKIE); 646 647 if (!coloring->w1) { 648 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 649 PLogObjectParent(coloring,coloring->w1); 650 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 651 PLogObjectParent(coloring,coloring->w2); 652 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 653 PLogObjectParent(coloring,coloring->w3); 654 } 655 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 656 657 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&fg);CHKERRQ(ierr); 658 if (fg) { 659 PLogInfo(coloring,"MatFDColoringApplyTS: Not calling MatZeroEntries()\n"); 660 } else { 661 ierr = MatZeroEntries(J);CHKERRQ(ierr); 662 } 663 664 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 665 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 666 ierr = (*f)(sctx,t,x1,w1,fctx);CHKERRQ(ierr); 667 668 ierr = PetscMemzero(wscale,N*sizeof(Scalar));CHKERRQ(ierr); 669 /* 670 Loop over each color 671 */ 672 673 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 674 for (k=0; k<coloring->ncolors; k++) { 675 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 676 /* 677 Loop over each column associated with color adding the 678 perturbation to the vector w3. 679 */ 680 for (l=0; l<coloring->ncolumns[k]; l++) { 681 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 682 dx = xx[col-start]; 683 if (dx == 0.0) dx = 1.0; 684 #if !defined(PETSC_USE_COMPLEX) 685 if (dx < umin && dx >= 0.0) dx = umin; 686 else if (dx < 0.0 && dx > -umin) dx = -umin; 687 #else 688 if (PetscAbsScalar(dx) < umin && PetscReal(dx) >= 0.0) dx = umin; 689 else if (PetscReal(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 690 #endif 691 dx *= epsilon; 692 wscale[col] = 1.0/dx; 693 ierr = VecSetValues(w3,1,&col,&dx,ADD_VALUES);CHKERRQ(ierr); 694 } 695 /* 696 Evaluate function at x1 + dx (here dx is a vector of perturbations) 697 */ 698 ierr = (*f)(sctx,t,w3,w2,fctx);CHKERRQ(ierr); 699 ierr = VecAXPY(&mone,w1,w2);CHKERRQ(ierr); 700 /* Communicate scale to all processors */ 701 #if !defined(PETSC_USE_COMPLEX) 702 ierr = MPI_Allreduce(wscale,scale,N,MPI_DOUBLE,MPI_SUM,comm);CHKERRQ(ierr); 703 #else 704 ierr = MPI_Allreduce(wscale,scale,2*N,MPI_DOUBLE,MPI_SUM,comm);CHKERRQ(ierr); 705 #endif 706 /* 707 Loop over rows of vector, putting results into Jacobian matrix 708 */ 709 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 710 for (l=0; l<coloring->nrows[k]; l++) { 711 row = coloring->rows[k][l]; 712 col = coloring->columnsforrow[k][l]; 713 y[row] *= scale[col]; 714 srow = row + start; 715 ierr = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 716 } 717 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 718 } 719 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 720 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 721 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 722 PetscFunctionReturn(0); 723 } 724 725 726 727