1 /*$Id: fdmatrix.c,v 1.52 1999/10/13 20:37:47 bsmith Exp bsmith $*/ 2 3 /* 4 This is where the abstract matrix operations are defined that are 5 used for finite difference computations of Jacobians using coloring. 6 */ 7 8 #include "petsc.h" 9 #include "src/mat/matimpl.h" /*I "mat.h" I*/ 10 #include "src/vec/vecimpl.h" 11 12 #undef __FUNC__ 13 #define __FUNC__ "MatFDColoringView_Draw" 14 static int MatFDColoringView_Draw(MatFDColoring fd,Viewer viewer) 15 { 16 int ierr,i,j,pause; 17 PetscTruth isnull; 18 Draw draw; 19 double xr,yr,xl,yl,h,w,x,y,xc,yc,scale = 0.0; 20 DrawButton button; 21 22 PetscFunctionBegin; 23 ierr = ViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 24 ierr = DrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 25 ierr = DrawSynchronizedClear(draw);CHKERRQ(ierr); 26 27 xr = fd->N; yr = fd->M; h = yr/10.0; w = xr/10.0; 28 xr += w; yr += h; xl = -w; yl = -h; 29 ierr = DrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 30 31 /* loop over colors */ 32 for (i=0; i<fd->ncolors; i++ ) { 33 for ( j=0; j<fd->nrows[i]; j++ ) { 34 y = fd->M - fd->rows[i][j] - fd->rstart; 35 x = fd->columnsforrow[i][j]; 36 ierr = DrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr); 37 } 38 } 39 ierr = DrawSynchronizedFlush(draw);CHKERRQ(ierr); 40 ierr = DrawGetPause(draw,&pause);CHKERRQ(ierr); 41 if (pause >= 0) { PetscSleep(pause); PetscFunctionReturn(0);} 42 ierr = DrawCheckResizedWindow(draw);CHKERRQ(ierr); 43 ierr = DrawSynchronizedGetMouseButton(draw,&button,&xc,&yc,0,0);CHKERRQ(ierr); 44 while (button != BUTTON_RIGHT) { 45 ierr = DrawSynchronizedClear(draw);CHKERRQ(ierr); 46 if (button == BUTTON_LEFT) scale = .5; 47 else if (button == BUTTON_CENTER) scale = 2.; 48 xl = scale*(xl + w - xc) + xc - w*scale; 49 xr = scale*(xr - w - xc) + xc + w*scale; 50 yl = scale*(yl + h - yc) + yc - h*scale; 51 yr = scale*(yr - h - yc) + yc + h*scale; 52 w *= scale; h *= scale; 53 ierr = DrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 54 /* loop over colors */ 55 for (i=0; i<fd->ncolors; i++ ) { 56 for ( j=0; j<fd->nrows[i]; j++ ) { 57 y = fd->M - fd->rows[i][j] - fd->rstart; 58 x = fd->columnsforrow[i][j]; 59 ierr = DrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr); 60 } 61 } 62 ierr = DrawCheckResizedWindow(draw);CHKERRQ(ierr); 63 ierr = DrawSynchronizedGetMouseButton(draw,&button,&xc,&yc,0,0);CHKERRQ(ierr); 64 } 65 66 PetscFunctionReturn(0); 67 } 68 69 #undef __FUNC__ 70 #define __FUNC__ "MatFDColoringView" 71 /*@C 72 MatFDColoringView - Views a finite difference coloring context. 73 74 Collective on MatFDColoring unless Viewer is VIEWER_STDOUT_SELF 75 76 Input Parameters: 77 + c - the coloring context 78 - viewer - visualization context 79 80 Level: intermediate 81 82 Notes: 83 The available visualization contexts include 84 + VIEWER_STDOUT_SELF - standard output (default) 85 . VIEWER_STDOUT_WORLD - synchronized standard 86 output where only the first processor opens 87 the file. All other processors send their 88 data to the first processor to print. 89 - VIEWER_DRAW_WORLD - graphical display of nonzero structure 90 91 .seealso: MatFDColoringCreate() 92 93 .keywords: Mat, finite differences, coloring, view 94 @*/ 95 int MatFDColoringView(MatFDColoring c,Viewer viewer) 96 { 97 int i,j,format,ierr; 98 PetscTruth isdraw,isascii; 99 100 PetscFunctionBegin; 101 PetscValidHeaderSpecific(c,MAT_FDCOLORING_COOKIE); 102 if (!viewer) viewer = VIEWER_STDOUT_SELF; 103 PetscValidHeaderSpecific(viewer,VIEWER_COOKIE); 104 PetscCheckSameComm(c,viewer); 105 106 ierr = PetscTypeCompare((PetscObject)viewer,DRAW_VIEWER,&isdraw);CHKERRQ(ierr); 107 ierr = PetscTypeCompare((PetscObject)viewer,ASCII_VIEWER,&isascii);CHKERRQ(ierr); 108 if (isdraw) { 109 ierr = MatFDColoringView_Draw(c,viewer);CHKERRQ(ierr); 110 } else if (isascii) { 111 ierr = ViewerASCIIPrintf(viewer,"MatFDColoring Object:\n");CHKERRQ(ierr); 112 ierr = ViewerASCIIPrintf(viewer," Error tolerance=%g\n",c->error_rel);CHKERRQ(ierr); 113 ierr = ViewerASCIIPrintf(viewer," Umin=%g\n",c->umin);CHKERRQ(ierr); 114 ierr = ViewerASCIIPrintf(viewer," Number of colors=%d\n",c->ncolors);CHKERRQ(ierr); 115 116 ierr = ViewerGetFormat(viewer,&format);CHKERRQ(ierr); 117 if (format != VIEWER_FORMAT_ASCII_INFO) { 118 for ( i=0; i<c->ncolors; i++ ) { 119 ierr = ViewerASCIIPrintf(viewer," Information for color %d\n",i);CHKERRQ(ierr); 120 ierr = ViewerASCIIPrintf(viewer," Number of columns %d\n",c->ncolumns[i]);CHKERRQ(ierr); 121 for ( j=0; j<c->ncolumns[i]; j++ ) { 122 ierr = ViewerASCIIPrintf(viewer," %d\n",c->columns[i][j]);CHKERRQ(ierr); 123 } 124 ierr = ViewerASCIIPrintf(viewer," Number of rows %d\n",c->nrows[i]);CHKERRQ(ierr); 125 for ( j=0; j<c->nrows[i]; j++ ) { 126 ierr = ViewerASCIIPrintf(viewer," %d %d \n",c->rows[i][j],c->columnsforrow[i][j]);CHKERRQ(ierr); 127 } 128 } 129 } 130 ierr = ViewerFlush(viewer);CHKERRQ(ierr); 131 } else { 132 SETERRQ1(1,1,"Viewer type %s not supported for MatFDColoring",((PetscObject)viewer)->type_name); 133 } 134 PetscFunctionReturn(0); 135 } 136 137 #undef __FUNC__ 138 #define __FUNC__ "MatFDColoringSetParameters" 139 /*@ 140 MatFDColoringSetParameters - Sets the parameters for the sparse approximation of 141 a Jacobian matrix using finite differences. 142 143 Collective on MatFDColoring 144 145 The Jacobian is estimated with the differencing approximation 146 .vb 147 F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where 148 h = error_rel*u[i] if abs(u[i]) > umin 149 = +/- error_rel*umin otherwise, with +/- determined by the sign of u[i] 150 dx_{i} = (0, ... 1, .... 0) 151 .ve 152 153 Input Parameters: 154 + coloring - the coloring context 155 . error_rel - relative error 156 - umin - minimum allowable u-value magnitude 157 158 Level: advanced 159 160 .keywords: Mat, finite differences, coloring, set, parameters 161 162 .seealso: MatFDColoringCreate() 163 @*/ 164 int MatFDColoringSetParameters(MatFDColoring matfd,double error,double umin) 165 { 166 PetscFunctionBegin; 167 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 168 169 if (error != PETSC_DEFAULT) matfd->error_rel = error; 170 if (umin != PETSC_DEFAULT) matfd->umin = umin; 171 PetscFunctionReturn(0); 172 } 173 174 #undef __FUNC__ 175 #define __FUNC__ "MatFDColoringSetFrequency" 176 /*@ 177 MatFDColoringSetFrequency - Sets the frequency for computing new Jacobian 178 matrices. 179 180 Collective on MatFDColoring 181 182 Input Parameters: 183 + coloring - the coloring context 184 - freq - frequency (default is 1) 185 186 Options Database Keys: 187 . -mat_fd_coloring_freq <freq> - Sets coloring frequency 188 189 Level: advanced 190 191 Notes: 192 Using a modified Newton strategy, where the Jacobian remains fixed for several 193 iterations, can be cost effective in terms of overall nonlinear solution 194 efficiency. This parameter indicates that a new Jacobian will be computed every 195 <freq> nonlinear iterations. 196 197 .keywords: Mat, finite differences, coloring, set, frequency 198 199 .seealso: MatFDColoringCreate(), MatFDColoringGetFrequency() 200 @*/ 201 int MatFDColoringSetFrequency(MatFDColoring matfd,int freq) 202 { 203 PetscFunctionBegin; 204 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 205 206 matfd->freq = freq; 207 PetscFunctionReturn(0); 208 } 209 210 #undef __FUNC__ 211 #define __FUNC__ "MatFDColoringGetFrequency" 212 /*@ 213 MatFDColoringGetFrequency - Gets the frequency for computing new Jacobian 214 matrices. 215 216 Not Collective 217 218 Input Parameters: 219 . coloring - the coloring context 220 221 Output Parameters: 222 . freq - frequency (default is 1) 223 224 Options Database Keys: 225 . -mat_fd_coloring_freq <freq> - Sets coloring frequency 226 227 Level: advanced 228 229 Notes: 230 Using a modified Newton strategy, where the Jacobian remains fixed for several 231 iterations, can be cost effective in terms of overall nonlinear solution 232 efficiency. This parameter indicates that a new Jacobian will be computed every 233 <freq> nonlinear iterations. 234 235 .keywords: Mat, finite differences, coloring, get, frequency 236 237 .seealso: MatFDColoringSetFrequency() 238 @*/ 239 int MatFDColoringGetFrequency(MatFDColoring matfd,int *freq) 240 { 241 PetscFunctionBegin; 242 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 243 244 *freq = matfd->freq; 245 PetscFunctionReturn(0); 246 } 247 248 #undef __FUNC__ 249 #define __FUNC__ "MatFDColoringSetFunction" 250 /*@C 251 MatFDColoringSetFunction - Sets the function to use for computing the Jacobian. 252 253 Collective on MatFDColoring 254 255 Input Parameters: 256 + coloring - the coloring context 257 . f - the function 258 - fctx - the optional user-defined function context 259 260 Level: intermediate 261 262 Notes: 263 In Fortran you must call MatFDColoringSetFunctionSNES() for a coloring object to 264 be used with the SNES solvers and MatFDColoringSetFunctionTS() if it is to be used 265 with the TS solvers. 266 267 .keywords: Mat, Jacobian, finite differences, set, function 268 @*/ 269 int MatFDColoringSetFunction(MatFDColoring matfd,int (*f)(void),void *fctx) 270 { 271 PetscFunctionBegin; 272 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 273 274 matfd->f = f; 275 matfd->fctx = fctx; 276 277 PetscFunctionReturn(0); 278 } 279 280 #undef __FUNC__ 281 #define __FUNC__ "MatFDColoringSetFromOptions" 282 /*@ 283 MatFDColoringSetFromOptions - Sets coloring finite difference parameters from 284 the options database. 285 286 Collective on MatFDColoring 287 288 The Jacobian, F'(u), is estimated with the differencing approximation 289 .vb 290 F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where 291 h = error_rel*u[i] if abs(u[i]) > umin 292 = +/- error_rel*umin otherwise, with +/- determined by the sign of u[i] 293 dx_{i} = (0, ... 1, .... 0) 294 .ve 295 296 Input Parameter: 297 . coloring - the coloring context 298 299 Options Database Keys: 300 + -mat_fd_coloring_error <err> - Sets <err> (square root 301 of relative error in the function) 302 . -mat_fd_coloring_umin <umin> - Sets umin, the minimum allowable u-value magnitude 303 . -mat_fd_coloring_freq <freq> - Sets frequency of computing a new Jacobian 304 . -mat_fd_coloring_view - Activates basic viewing 305 . -mat_fd_coloring_view_info - Activates viewing info 306 - -mat_fd_coloring_view_draw - Activates drawing 307 308 Level: intermediate 309 310 .keywords: Mat, finite differences, parameters 311 @*/ 312 int MatFDColoringSetFromOptions(MatFDColoring matfd) 313 { 314 int ierr,flag,freq = 1; 315 double error = PETSC_DEFAULT,umin = PETSC_DEFAULT; 316 317 PetscFunctionBegin; 318 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE); 319 320 ierr = OptionsGetDouble(matfd->prefix,"-mat_fd_coloring_err",&error,&flag);CHKERRQ(ierr); 321 ierr = OptionsGetDouble(matfd->prefix,"-mat_fd_coloring_umin",&umin,&flag);CHKERRQ(ierr); 322 ierr = MatFDColoringSetParameters(matfd,error,umin);CHKERRQ(ierr); 323 ierr = OptionsGetInt(matfd->prefix,"-mat_fd_coloring_freq",&freq,&flag);CHKERRQ(ierr); 324 ierr = MatFDColoringSetFrequency(matfd,freq);CHKERRQ(ierr); 325 ierr = OptionsHasName(PETSC_NULL,"-help",&flag);CHKERRQ(ierr); 326 if (flag) { 327 ierr = MatFDColoringPrintHelp(matfd);CHKERRQ(ierr); 328 } 329 PetscFunctionReturn(0); 330 } 331 332 #undef __FUNC__ 333 #define __FUNC__ "MatFDColoringPrintHelp" 334 /*@ 335 MatFDColoringPrintHelp - Prints help message for matrix finite difference calculations 336 using coloring. 337 338 Collective on MatFDColoring 339 340 Input Parameter: 341 . fdcoloring - the MatFDColoring context 342 343 Level: intermediate 344 345 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringSetFromOptions() 346 @*/ 347 int MatFDColoringPrintHelp(MatFDColoring fd) 348 { 349 int ierr; 350 351 PetscFunctionBegin; 352 PetscValidHeaderSpecific(fd,MAT_FDCOLORING_COOKIE); 353 354 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_err <err>: set sqrt rel tol in function, defaults to %g\n",fd->error_rel);CHKERRQ(ierr); 355 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_umin <umin>: see users manual, defaults to %d\n",fd->umin);CHKERRQ(ierr); 356 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_freq <freq>: frequency that Jacobian is recomputed, defaults to %d\n",fd->freq);CHKERRQ(ierr); 357 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view\n");CHKERRQ(ierr); 358 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view_draw\n");CHKERRQ(ierr); 359 ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view_info\n");CHKERRQ(ierr); 360 PetscFunctionReturn(0); 361 } 362 363 #undef __FUNC__ 364 #define __FUNC__ "MatFDColoringView_Private" 365 int MatFDColoringView_Private(MatFDColoring fd) 366 { 367 int ierr,flg; 368 369 PetscFunctionBegin; 370 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view",&flg);CHKERRQ(ierr); 371 if (flg) { 372 ierr = MatFDColoringView(fd,VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr); 373 } 374 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view_info",&flg);CHKERRQ(ierr); 375 if (flg) { 376 ierr = ViewerPushFormat(VIEWER_STDOUT_(fd->comm),VIEWER_FORMAT_ASCII_INFO,PETSC_NULL);CHKERRQ(ierr); 377 ierr = MatFDColoringView(fd,VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr); 378 ierr = ViewerPopFormat(VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr); 379 } 380 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view_draw",&flg);CHKERRQ(ierr); 381 if (flg) { 382 ierr = MatFDColoringView(fd,VIEWER_DRAW_(fd->comm));CHKERRQ(ierr); 383 ierr = ViewerFlush(VIEWER_DRAW_(fd->comm));CHKERRQ(ierr); 384 } 385 PetscFunctionReturn(0); 386 } 387 388 #undef __FUNC__ 389 #define __FUNC__ "MatFDColoringCreate" 390 /*@C 391 MatFDColoringCreate - Creates a matrix coloring context for finite difference 392 computation of Jacobians. 393 394 Collective on Mat 395 396 Input Parameters: 397 + mat - the matrix containing the nonzero structure of the Jacobian 398 - iscoloring - the coloring of the matrix 399 400 Output Parameter: 401 . color - the new coloring context 402 403 Options Database Keys: 404 + -mat_fd_coloring_view - Activates basic viewing or coloring 405 . -mat_fd_coloring_view_draw - Activates drawing of coloring 406 - -mat_fd_coloring_view_info - Activates viewing of coloring info 407 408 Level: intermediate 409 410 .seealso: MatFDColoringDestroy(),SNESDefaultComputeJacobianColor(), ISColoringCreate(), 411 MatFDColoringSetFunction(), MatFDColoringSetFromOptions() 412 @*/ 413 int MatFDColoringCreate(Mat mat,ISColoring iscoloring,MatFDColoring *color) 414 { 415 MatFDColoring c; 416 MPI_Comm comm; 417 int ierr,M,N; 418 419 PetscFunctionBegin; 420 ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr); 421 if (M != N) SETERRQ(PETSC_ERR_SUP,0,"Only for square matrices"); 422 423 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 424 PetscHeaderCreate(c,_p_MatFDColoring,int,MAT_FDCOLORING_COOKIE,0,"MatFDColoring",comm, 425 MatFDColoringDestroy,MatFDColoringView); 426 PLogObjectCreate(c); 427 428 if (mat->ops->fdcoloringcreate) { 429 ierr = (*mat->ops->fdcoloringcreate)(mat,iscoloring,c);CHKERRQ(ierr); 430 } else { 431 SETERRQ(PETSC_ERR_SUP,0,"Code not yet written for this matrix type"); 432 } 433 434 c->error_rel = 1.e-8; 435 c->umin = 1.e-6; 436 c->freq = 1; 437 438 ierr = MatFDColoringView_Private(c);CHKERRQ(ierr); 439 440 *color = c; 441 442 PetscFunctionReturn(0); 443 } 444 445 #undef __FUNC__ 446 #define __FUNC__ "MatFDColoringDestroy" 447 /*@C 448 MatFDColoringDestroy - Destroys a matrix coloring context that was created 449 via MatFDColoringCreate(). 450 451 Collective on MatFDColoring 452 453 Input Parameter: 454 . c - coloring context 455 456 Level: intermediate 457 458 .seealso: MatFDColoringCreate() 459 @*/ 460 int MatFDColoringDestroy(MatFDColoring c) 461 { 462 int i,ierr; 463 464 PetscFunctionBegin; 465 if (--c->refct > 0) PetscFunctionReturn(0); 466 467 468 for ( i=0; i<c->ncolors; i++ ) { 469 if (c->columns[i]) {ierr = PetscFree(c->columns[i]);CHKERRQ(ierr);} 470 if (c->rows[i]) {ierr = PetscFree(c->rows[i]);CHKERRQ(ierr);} 471 if (c->columnsforrow[i]) {ierr = PetscFree(c->columnsforrow[i]);CHKERRQ(ierr);} 472 } 473 ierr = PetscFree(c->ncolumns);CHKERRQ(ierr); 474 ierr = PetscFree(c->columns);CHKERRQ(ierr); 475 ierr = PetscFree(c->nrows);CHKERRQ(ierr); 476 ierr = PetscFree(c->rows);CHKERRQ(ierr); 477 ierr = PetscFree(c->columnsforrow);CHKERRQ(ierr); 478 ierr = PetscFree(c->scale);CHKERRQ(ierr); 479 if (c->w1) { 480 ierr = VecDestroy(c->w1);CHKERRQ(ierr); 481 ierr = VecDestroy(c->w2);CHKERRQ(ierr); 482 ierr = VecDestroy(c->w3);CHKERRQ(ierr); 483 } 484 PLogObjectDestroy(c); 485 PetscHeaderDestroy(c); 486 PetscFunctionReturn(0); 487 } 488 489 490 #undef __FUNC__ 491 #define __FUNC__ "MatFDColoringApply" 492 /*@ 493 MatFDColoringApply - Given a matrix for which a MatFDColoring context 494 has been created, computes the Jacobian for a function via finite differences. 495 496 Collective on MatFDColoring 497 498 Input Parameters: 499 + mat - location to store Jacobian 500 . coloring - coloring context created with MatFDColoringCreate() 501 . x1 - location at which Jacobian is to be computed 502 - sctx - optional context required by function (actually a SNES context) 503 504 Options Database Keys: 505 . -mat_fd_coloring_freq <freq> - Sets coloring frequency 506 507 Level: intermediate 508 509 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView() 510 511 .keywords: coloring, Jacobian, finite differences 512 @*/ 513 int MatFDColoringApply(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 514 { 515 int k,fg,ierr,N,start,end,l,row,col,srow; 516 Scalar dx, mone = -1.0,*y,*scale = coloring->scale,*xx,*wscale = coloring->wscale; 517 double epsilon = coloring->error_rel, umin = coloring->umin; 518 MPI_Comm comm = coloring->comm; 519 Vec w1,w2,w3; 520 int (*f)(void *,Vec,Vec,void *) = ( int (*)(void *,Vec,Vec,void *))coloring->f; 521 void *fctx = coloring->fctx; 522 523 PetscFunctionBegin; 524 PetscValidHeaderSpecific(J,MAT_COOKIE); 525 PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_COOKIE); 526 PetscValidHeaderSpecific(x1,VEC_COOKIE); 527 528 529 if (!coloring->w1) { 530 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 531 PLogObjectParent(coloring,coloring->w1); 532 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 533 PLogObjectParent(coloring,coloring->w2); 534 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 535 PLogObjectParent(coloring,coloring->w3); 536 } 537 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 538 539 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&fg);CHKERRQ(ierr); 540 if (fg) { 541 PLogInfo(coloring,"MatFDColoringApply: Not calling MatZeroEntries()\n"); 542 } else { 543 ierr = MatZeroEntries(J);CHKERRQ(ierr); 544 } 545 546 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 547 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 548 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 549 550 ierr = PetscMemzero(wscale,N*sizeof(Scalar));CHKERRQ(ierr); 551 /* 552 Loop over each color 553 */ 554 555 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 556 for (k=0; k<coloring->ncolors; k++) { 557 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 558 /* 559 Loop over each column associated with color adding the 560 perturbation to the vector w3. 561 */ 562 for (l=0; l<coloring->ncolumns[k]; l++) { 563 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 564 dx = xx[col-start]; 565 if (dx == 0.0) dx = 1.0; 566 #if !defined(PETSC_USE_COMPLEX) 567 if (dx < umin && dx >= 0.0) dx = umin; 568 else if (dx < 0.0 && dx > -umin) dx = -umin; 569 #else 570 if (PetscAbsScalar(dx) < umin && PetscReal(dx) >= 0.0) dx = umin; 571 else if (PetscReal(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 572 #endif 573 dx *= epsilon; 574 wscale[col] = 1.0/dx; 575 ierr = VecSetValues(w3,1,&col,&dx,ADD_VALUES);CHKERRQ(ierr); 576 } 577 578 /* 579 Evaluate function at x1 + dx (here dx is a vector of perturbations) 580 */ 581 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 582 ierr = VecAXPY(&mone,w1,w2);CHKERRQ(ierr); 583 /* Communicate scale to all processors */ 584 ierr = MPI_Allreduce(wscale,scale,N,MPIU_SCALAR,PetscSum_Op,comm);CHKERRQ(ierr); 585 /* 586 Loop over rows of vector, putting results into Jacobian matrix 587 */ 588 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 589 for (l=0; l<coloring->nrows[k]; l++) { 590 row = coloring->rows[k][l]; 591 col = coloring->columnsforrow[k][l]; 592 y[row] *= scale[col]; 593 srow = row + start; 594 ierr = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 595 } 596 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 597 } 598 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 599 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 600 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 601 PetscFunctionReturn(0); 602 } 603 604 #undef __FUNC__ 605 #define __FUNC__ "MatFDColoringApplyTS" 606 /*@ 607 MatFDColoringApplyTS - Given a matrix for which a MatFDColoring context 608 has been created, computes the Jacobian for a function via finite differences. 609 610 Collective on Mat, MatFDColoring, and Vec 611 612 Input Parameters: 613 + mat - location to store Jacobian 614 . coloring - coloring context created with MatFDColoringCreate() 615 . x1 - location at which Jacobian is to be computed 616 - sctx - optional context required by function (actually a SNES context) 617 618 Options Database Keys: 619 . -mat_fd_coloring_freq <freq> - Sets coloring frequency 620 621 Level: intermediate 622 623 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView() 624 625 .keywords: coloring, Jacobian, finite differences 626 @*/ 627 int MatFDColoringApplyTS(Mat J,MatFDColoring coloring,double t,Vec x1,MatStructure *flag,void *sctx) 628 { 629 int k,fg,ierr,N,start,end,l,row,col,srow; 630 Scalar dx, mone = -1.0,*y,*scale = coloring->scale,*xx,*wscale = coloring->wscale; 631 double epsilon = coloring->error_rel, umin = coloring->umin; 632 MPI_Comm comm = coloring->comm; 633 Vec w1,w2,w3; 634 int (*f)(void *,double,Vec,Vec,void *) = ( int (*)(void *,double,Vec,Vec,void *))coloring->f; 635 void *fctx = coloring->fctx; 636 637 PetscFunctionBegin; 638 PetscValidHeaderSpecific(J,MAT_COOKIE); 639 PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_COOKIE); 640 PetscValidHeaderSpecific(x1,VEC_COOKIE); 641 642 if (!coloring->w1) { 643 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 644 PLogObjectParent(coloring,coloring->w1); 645 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 646 PLogObjectParent(coloring,coloring->w2); 647 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 648 PLogObjectParent(coloring,coloring->w3); 649 } 650 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 651 652 ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&fg);CHKERRQ(ierr); 653 if (fg) { 654 PLogInfo(coloring,"MatFDColoringApplyTS: Not calling MatZeroEntries()\n"); 655 } else { 656 ierr = MatZeroEntries(J);CHKERRQ(ierr); 657 } 658 659 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 660 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 661 ierr = (*f)(sctx,t,x1,w1,fctx);CHKERRQ(ierr); 662 663 ierr = PetscMemzero(wscale,N*sizeof(Scalar));CHKERRQ(ierr); 664 /* 665 Loop over each color 666 */ 667 668 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 669 for (k=0; k<coloring->ncolors; k++) { 670 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 671 /* 672 Loop over each column associated with color adding the 673 perturbation to the vector w3. 674 */ 675 for (l=0; l<coloring->ncolumns[k]; l++) { 676 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 677 dx = xx[col-start]; 678 if (dx == 0.0) dx = 1.0; 679 #if !defined(PETSC_USE_COMPLEX) 680 if (dx < umin && dx >= 0.0) dx = umin; 681 else if (dx < 0.0 && dx > -umin) dx = -umin; 682 #else 683 if (PetscAbsScalar(dx) < umin && PetscReal(dx) >= 0.0) dx = umin; 684 else if (PetscReal(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 685 #endif 686 dx *= epsilon; 687 wscale[col] = 1.0/dx; 688 ierr = VecSetValues(w3,1,&col,&dx,ADD_VALUES);CHKERRQ(ierr); 689 } 690 /* 691 Evaluate function at x1 + dx (here dx is a vector of perturbations) 692 */ 693 ierr = (*f)(sctx,t,w3,w2,fctx);CHKERRQ(ierr); 694 ierr = VecAXPY(&mone,w1,w2);CHKERRQ(ierr); 695 /* Communicate scale to all processors */ 696 ierr = MPI_Allreduce(wscale,scale,N,MPIU_SCALAR,PetscSum_Op,comm);CHKERRQ(ierr); 697 /* 698 Loop over rows of vector, putting results into Jacobian matrix 699 */ 700 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 701 for (l=0; l<coloring->nrows[k]; l++) { 702 row = coloring->rows[k][l]; 703 col = coloring->columnsforrow[k][l]; 704 y[row] *= scale[col]; 705 srow = row + start; 706 ierr = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 707 } 708 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 709 } 710 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 711 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 712 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 713 PetscFunctionReturn(0); 714 } 715 716 717 718