1 2 /* 3 This is where the abstract matrix operations are defined that are 4 used for finite difference computations of Jacobians using coloring. 5 */ 6 7 #include <petsc-private/matimpl.h> /*I "petscmat.h" I*/ 8 9 #undef __FUNCT__ 10 #define __FUNCT__ "MatFDColoringSetF" 11 PetscErrorCode MatFDColoringSetF(MatFDColoring fd,Vec F) 12 { 13 PetscErrorCode ierr; 14 15 PetscFunctionBegin; 16 if (F) { 17 ierr = VecCopy(F,fd->w1);CHKERRQ(ierr); 18 fd->fset = PETSC_TRUE; 19 } else { 20 fd->fset = PETSC_FALSE; 21 } 22 PetscFunctionReturn(0); 23 } 24 25 #include <petscdraw.h> 26 #undef __FUNCT__ 27 #define __FUNCT__ "MatFDColoringView_Draw_Zoom" 28 static PetscErrorCode MatFDColoringView_Draw_Zoom(PetscDraw draw,void *Aa) 29 { 30 MatFDColoring fd = (MatFDColoring)Aa; 31 PetscErrorCode ierr; 32 PetscInt i,j; 33 PetscReal x,y; 34 35 PetscFunctionBegin; 36 /* loop over colors */ 37 for (i=0; i<fd->ncolors; i++) { 38 for (j=0; j<fd->nrows[i]; j++) { 39 y = fd->M - fd->rows[i][j] - fd->rstart; 40 x = fd->columnsforrow[i][j]; 41 ierr = PetscDrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr); 42 } 43 } 44 PetscFunctionReturn(0); 45 } 46 47 #undef __FUNCT__ 48 #define __FUNCT__ "MatFDColoringView_Draw" 49 static PetscErrorCode MatFDColoringView_Draw(MatFDColoring fd,PetscViewer viewer) 50 { 51 PetscErrorCode ierr; 52 PetscBool isnull; 53 PetscDraw draw; 54 PetscReal xr,yr,xl,yl,h,w; 55 56 PetscFunctionBegin; 57 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 58 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 59 60 ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 61 62 xr = fd->N; yr = fd->M; h = yr/10.0; w = xr/10.0; 63 xr += w; yr += h; xl = -w; yl = -h; 64 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 65 ierr = PetscDrawZoom(draw,MatFDColoringView_Draw_Zoom,fd);CHKERRQ(ierr); 66 ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",NULL);CHKERRQ(ierr); 67 PetscFunctionReturn(0); 68 } 69 70 #undef __FUNCT__ 71 #define __FUNCT__ "MatFDColoringView" 72 /*@C 73 MatFDColoringView - Views a finite difference coloring context. 74 75 Collective on MatFDColoring 76 77 Input Parameters: 78 + c - the coloring context 79 - viewer - visualization context 80 81 Level: intermediate 82 83 Notes: 84 The available visualization contexts include 85 + PETSC_VIEWER_STDOUT_SELF - standard output (default) 86 . PETSC_VIEWER_STDOUT_WORLD - synchronized standard 87 output where only the first processor opens 88 the file. All other processors send their 89 data to the first processor to print. 90 - PETSC_VIEWER_DRAW_WORLD - graphical display of nonzero structure 91 92 Notes: 93 Since PETSc uses only a small number of basic colors (currently 33), if the coloring 94 involves more than 33 then some seemingly identical colors are displayed making it look 95 like an illegal coloring. This is just a graphical artifact. 96 97 .seealso: MatFDColoringCreate() 98 99 .keywords: Mat, finite differences, coloring, view 100 @*/ 101 PetscErrorCode MatFDColoringView(MatFDColoring c,PetscViewer viewer) 102 { 103 PetscErrorCode ierr; 104 PetscInt i,j; 105 PetscBool isdraw,iascii; 106 PetscViewerFormat format; 107 108 PetscFunctionBegin; 109 PetscValidHeaderSpecific(c,MAT_FDCOLORING_CLASSID,1); 110 if (!viewer) { 111 ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)c),&viewer);CHKERRQ(ierr); 112 } 113 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 114 PetscCheckSameComm(c,1,viewer,2); 115 116 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 117 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 118 if (isdraw) { 119 ierr = MatFDColoringView_Draw(c,viewer);CHKERRQ(ierr); 120 } else if (iascii) { 121 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)c,viewer);CHKERRQ(ierr); 122 ierr = PetscViewerASCIIPrintf(viewer," Error tolerance=%G\n",c->error_rel);CHKERRQ(ierr); 123 ierr = PetscViewerASCIIPrintf(viewer," Umin=%G\n",c->umin);CHKERRQ(ierr); 124 ierr = PetscViewerASCIIPrintf(viewer," Number of colors=%D\n",c->ncolors);CHKERRQ(ierr); 125 126 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 127 if (format != PETSC_VIEWER_ASCII_INFO) { 128 for (i=0; i<c->ncolors; i++) { 129 ierr = PetscViewerASCIIPrintf(viewer," Information for color %D\n",i);CHKERRQ(ierr); 130 ierr = PetscViewerASCIIPrintf(viewer," Number of columns %D\n",c->ncolumns[i]);CHKERRQ(ierr); 131 for (j=0; j<c->ncolumns[i]; j++) { 132 ierr = PetscViewerASCIIPrintf(viewer," %D\n",c->columns[i][j]);CHKERRQ(ierr); 133 } 134 ierr = PetscViewerASCIIPrintf(viewer," Number of rows %D\n",c->nrows[i]);CHKERRQ(ierr); 135 for (j=0; j<c->nrows[i]; j++) { 136 ierr = PetscViewerASCIIPrintf(viewer," %D %D \n",c->rows[i][j],c->columnsforrow[i][j]);CHKERRQ(ierr); 137 } 138 } 139 } 140 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 141 } 142 PetscFunctionReturn(0); 143 } 144 145 #undef __FUNCT__ 146 #define __FUNCT__ "MatFDColoringSetParameters" 147 /*@ 148 MatFDColoringSetParameters - Sets the parameters for the sparse approximation of 149 a Jacobian matrix using finite differences. 150 151 Logically Collective on MatFDColoring 152 153 The Jacobian is estimated with the differencing approximation 154 .vb 155 F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where 156 h = error_rel*u[i] if abs(u[i]) > umin 157 = +/- error_rel*umin otherwise, with +/- determined by the sign of u[i] 158 dx_{i} = (0, ... 1, .... 0) 159 .ve 160 161 Input Parameters: 162 + coloring - the coloring context 163 . error_rel - relative error 164 - umin - minimum allowable u-value magnitude 165 166 Level: advanced 167 168 .keywords: Mat, finite differences, coloring, set, parameters 169 170 .seealso: MatFDColoringCreate(), MatFDColoringSetFromOptions() 171 172 @*/ 173 PetscErrorCode MatFDColoringSetParameters(MatFDColoring matfd,PetscReal error,PetscReal umin) 174 { 175 PetscFunctionBegin; 176 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1); 177 PetscValidLogicalCollectiveReal(matfd,error,2); 178 PetscValidLogicalCollectiveReal(matfd,umin,3); 179 if (error != PETSC_DEFAULT) matfd->error_rel = error; 180 if (umin != PETSC_DEFAULT) matfd->umin = umin; 181 PetscFunctionReturn(0); 182 } 183 184 185 186 #undef __FUNCT__ 187 #define __FUNCT__ "MatFDColoringGetFunction" 188 /*@C 189 MatFDColoringGetFunction - Gets the function to use for computing the Jacobian. 190 191 Not Collective 192 193 Input Parameters: 194 . coloring - the coloring context 195 196 Output Parameters: 197 + f - the function 198 - fctx - the optional user-defined function context 199 200 Level: intermediate 201 202 .keywords: Mat, Jacobian, finite differences, set, function 203 204 .seealso: MatFDColoringCreate(), MatFDColoringSetFunction(), MatFDColoringSetFromOptions() 205 206 @*/ 207 PetscErrorCode MatFDColoringGetFunction(MatFDColoring matfd,PetscErrorCode (**f)(void),void **fctx) 208 { 209 PetscFunctionBegin; 210 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1); 211 if (f) *f = matfd->f; 212 if (fctx) *fctx = matfd->fctx; 213 PetscFunctionReturn(0); 214 } 215 216 #undef __FUNCT__ 217 #define __FUNCT__ "MatFDColoringSetFunction" 218 /*@C 219 MatFDColoringSetFunction - Sets the function to use for computing the Jacobian. 220 221 Logically Collective on MatFDColoring 222 223 Input Parameters: 224 + coloring - the coloring context 225 . f - the function 226 - fctx - the optional user-defined function context 227 228 Calling sequence of (*f) function: 229 For SNES: PetscErrorCode (*f)(SNES,Vec,Vec,void*) 230 If not using SNES: PetscErrorCode (*f)(void *dummy,Vec,Vec,void*) and dummy is ignored 231 232 Level: advanced 233 234 Notes: This function is usually used automatically by SNES (when one uses SNESSetJacobian() with the argument 235 SNESComputeJacobianDefaultColor()) and only needs to be used by someone computing a matrix via coloring directly by 236 calling MatFDColoringApply() 237 238 Fortran Notes: 239 In Fortran you must call MatFDColoringSetFunction() for a coloring object to 240 be used without SNES or within the SNES solvers. 241 242 .keywords: Mat, Jacobian, finite differences, set, function 243 244 .seealso: MatFDColoringCreate(), MatFDColoringGetFunction(), MatFDColoringSetFromOptions() 245 246 @*/ 247 PetscErrorCode MatFDColoringSetFunction(MatFDColoring matfd,PetscErrorCode (*f)(void),void *fctx) 248 { 249 PetscFunctionBegin; 250 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1); 251 matfd->f = f; 252 matfd->fctx = fctx; 253 PetscFunctionReturn(0); 254 } 255 256 #undef __FUNCT__ 257 #define __FUNCT__ "MatFDColoringSetFromOptions" 258 /*@ 259 MatFDColoringSetFromOptions - Sets coloring finite difference parameters from 260 the options database. 261 262 Collective on MatFDColoring 263 264 The Jacobian, F'(u), is estimated with the differencing approximation 265 .vb 266 F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where 267 h = error_rel*u[i] if abs(u[i]) > umin 268 = +/- error_rel*umin otherwise, with +/- determined by the sign of u[i] 269 dx_{i} = (0, ... 1, .... 0) 270 .ve 271 272 Input Parameter: 273 . coloring - the coloring context 274 275 Options Database Keys: 276 + -mat_fd_coloring_err <err> - Sets <err> (square root 277 of relative error in the function) 278 . -mat_fd_coloring_umin <umin> - Sets umin, the minimum allowable u-value magnitude 279 . -mat_fd_type - "wp" or "ds" (see MATMFFD_WP or MATMFFD_DS) 280 . -mat_fd_coloring_view - Activates basic viewing 281 . -mat_fd_coloring_view ::ascii_info - Activates viewing info 282 - -mat_fd_coloring_view draw - Activates drawing 283 284 Level: intermediate 285 286 .keywords: Mat, finite differences, parameters 287 288 .seealso: MatFDColoringCreate(), MatFDColoringView(), MatFDColoringSetParameters() 289 290 @*/ 291 PetscErrorCode MatFDColoringSetFromOptions(MatFDColoring matfd) 292 { 293 PetscErrorCode ierr; 294 PetscBool flg; 295 char value[3]; 296 297 PetscFunctionBegin; 298 PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1); 299 300 ierr = PetscObjectOptionsBegin((PetscObject)matfd);CHKERRQ(ierr); 301 ierr = PetscOptionsReal("-mat_fd_coloring_err","Square root of relative error in function","MatFDColoringSetParameters",matfd->error_rel,&matfd->error_rel,0);CHKERRQ(ierr); 302 ierr = PetscOptionsReal("-mat_fd_coloring_umin","Minimum allowable u magnitude","MatFDColoringSetParameters",matfd->umin,&matfd->umin,0);CHKERRQ(ierr); 303 ierr = PetscOptionsString("-mat_fd_type","Algorithm to compute h, wp or ds","MatFDColoringCreate",matfd->htype,value,3,&flg);CHKERRQ(ierr); 304 if (flg) { 305 if (value[0] == 'w' && value[1] == 'p') matfd->htype = "wp"; 306 else if (value[0] == 'd' && value[1] == 's') matfd->htype = "ds"; 307 else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Unknown finite differencing type %s",value); 308 } 309 /* process any options handlers added with PetscObjectAddOptionsHandler() */ 310 ierr = PetscObjectProcessOptionsHandlers((PetscObject)matfd);CHKERRQ(ierr); 311 PetscOptionsEnd();CHKERRQ(ierr); 312 PetscFunctionReturn(0); 313 } 314 315 #undef __FUNCT__ 316 #define __FUNCT__ "MatFDColoringViewFromOptions" 317 PetscErrorCode MatFDColoringViewFromOptions(MatFDColoring fd,const char prefix[],const char optionname[]) 318 { 319 PetscErrorCode ierr; 320 PetscBool flg; 321 PetscViewer viewer; 322 PetscViewerFormat format; 323 324 PetscFunctionBegin; 325 if (prefix) { 326 ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)fd),prefix,optionname,&viewer,&format,&flg);CHKERRQ(ierr); 327 } else { 328 ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)fd),((PetscObject)fd)->prefix,optionname,&viewer,&format,&flg);CHKERRQ(ierr); 329 } 330 if (flg) { 331 ierr = PetscViewerPushFormat(viewer,format);CHKERRQ(ierr); 332 ierr = MatFDColoringView(fd,viewer);CHKERRQ(ierr); 333 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 334 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 335 } 336 PetscFunctionReturn(0); 337 } 338 339 #undef __FUNCT__ 340 #define __FUNCT__ "MatFDColoringCreate" 341 /*@ 342 MatFDColoringCreate - Creates a matrix coloring context for finite difference 343 computation of Jacobians. 344 345 Collective on Mat 346 347 Input Parameters: 348 + mat - the matrix containing the nonzero structure of the Jacobian 349 - iscoloring - the coloring of the matrix; usually obtained with MatGetColoring() or DMCreateColoring() 350 351 Output Parameter: 352 . color - the new coloring context 353 354 Level: intermediate 355 356 .seealso: MatFDColoringDestroy(),SNESComputeJacobianDefaultColor(), ISColoringCreate(), 357 MatFDColoringSetFunction(), MatFDColoringSetFromOptions(), MatFDColoringApply(), 358 MatFDColoringView(), MatFDColoringSetParameters(), MatGetColoring(), DMCreateColoring() 359 @*/ 360 PetscErrorCode MatFDColoringCreate(Mat mat,ISColoring iscoloring,MatFDColoring *color) 361 { 362 MatFDColoring c; 363 MPI_Comm comm; 364 PetscErrorCode ierr; 365 PetscInt M,N; 366 367 PetscFunctionBegin; 368 if (!mat->assembled) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Matrix must be assembled by calls to MatAssemblyBegin/End();"); 369 ierr = PetscLogEventBegin(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr); 370 ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr); 371 if (M != N) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"Only for square matrices"); 372 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 373 ierr = PetscHeaderCreate(c,_p_MatFDColoring,int,MAT_FDCOLORING_CLASSID,"MatFDColoring","Jacobian computation via finite differences with coloring","Mat",comm,MatFDColoringDestroy,MatFDColoringView);CHKERRQ(ierr); 374 375 c->ctype = iscoloring->ctype; 376 377 if (mat->ops->fdcoloringcreate) { 378 ierr = (*mat->ops->fdcoloringcreate)(mat,iscoloring,c);CHKERRQ(ierr); 379 } else SETERRQ1(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"Code not yet written for matrix type %s",((PetscObject)mat)->type_name); 380 381 ierr = MatGetVecs(mat,NULL,&c->w1);CHKERRQ(ierr); 382 ierr = PetscLogObjectParent((PetscObject)c,(PetscObject)c->w1);CHKERRQ(ierr); 383 ierr = VecDuplicate(c->w1,&c->w2);CHKERRQ(ierr); 384 ierr = PetscLogObjectParent((PetscObject)c,(PetscObject)c->w2);CHKERRQ(ierr); 385 386 c->error_rel = PETSC_SQRT_MACHINE_EPSILON; 387 c->umin = 100.0*PETSC_SQRT_MACHINE_EPSILON; 388 c->currentcolor = -1; 389 c->htype = "wp"; 390 c->fset = PETSC_FALSE; 391 392 *color = c; 393 ierr = PetscObjectCompose((PetscObject)mat,"SNESMatFDColoring",(PetscObject)c);CHKERRQ(ierr); 394 ierr = PetscLogEventEnd(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr); 395 PetscFunctionReturn(0); 396 } 397 398 #undef __FUNCT__ 399 #define __FUNCT__ "MatFDColoringDestroy" 400 /*@ 401 MatFDColoringDestroy - Destroys a matrix coloring context that was created 402 via MatFDColoringCreate(). 403 404 Collective on MatFDColoring 405 406 Input Parameter: 407 . c - coloring context 408 409 Level: intermediate 410 411 .seealso: MatFDColoringCreate() 412 @*/ 413 PetscErrorCode MatFDColoringDestroy(MatFDColoring *c) 414 { 415 PetscErrorCode ierr; 416 PetscInt i; 417 418 PetscFunctionBegin; 419 if (!*c) PetscFunctionReturn(0); 420 if (--((PetscObject)(*c))->refct > 0) {*c = 0; PetscFunctionReturn(0);} 421 422 for (i=0; i<(*c)->ncolors; i++) { 423 ierr = PetscFree((*c)->columns[i]);CHKERRQ(ierr); 424 if ((*c)->rows) { 425 ierr = PetscFree((*c)->rows[i]);CHKERRQ(ierr); 426 ierr = PetscFree((*c)->columnsforrow[i]);CHKERRQ(ierr); 427 } 428 if ((*c)->vscaleforrow) {ierr = PetscFree((*c)->vscaleforrow[i]);CHKERRQ(ierr);} 429 } 430 ierr = PetscFree((*c)->ncolumns);CHKERRQ(ierr); 431 ierr = PetscFree((*c)->columns);CHKERRQ(ierr); 432 ierr = PetscFree((*c)->nrows);CHKERRQ(ierr); 433 if ((*c)->rows) { 434 ierr = PetscFree((*c)->rows);CHKERRQ(ierr); 435 ierr = PetscFree((*c)->columnsforrow);CHKERRQ(ierr); 436 } else { 437 ierr = PetscFree((*c)->rowcolden2sp3);CHKERRQ(ierr); 438 } 439 ierr = PetscFree((*c)->vscaleforrow);CHKERRQ(ierr); 440 ierr = VecDestroy(&(*c)->vscale);CHKERRQ(ierr); 441 ierr = VecDestroy(&(*c)->w1);CHKERRQ(ierr); 442 ierr = VecDestroy(&(*c)->w2);CHKERRQ(ierr); 443 ierr = VecDestroy(&(*c)->w3);CHKERRQ(ierr); 444 ierr = PetscHeaderDestroy(c);CHKERRQ(ierr); 445 PetscFunctionReturn(0); 446 } 447 448 #undef __FUNCT__ 449 #define __FUNCT__ "MatFDColoringGetPerturbedColumns" 450 /*@C 451 MatFDColoringGetPerturbedColumns - Returns the indices of the columns that 452 that are currently being perturbed. 453 454 Not Collective 455 456 Input Parameters: 457 . coloring - coloring context created with MatFDColoringCreate() 458 459 Output Parameters: 460 + n - the number of local columns being perturbed 461 - cols - the column indices, in global numbering 462 463 Level: intermediate 464 465 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringApply() 466 467 .keywords: coloring, Jacobian, finite differences 468 @*/ 469 PetscErrorCode MatFDColoringGetPerturbedColumns(MatFDColoring coloring,PetscInt *n,PetscInt *cols[]) 470 { 471 PetscFunctionBegin; 472 if (coloring->currentcolor >= 0) { 473 *n = coloring->ncolumns[coloring->currentcolor]; 474 *cols = coloring->columns[coloring->currentcolor]; 475 } else { 476 *n = 0; 477 } 478 PetscFunctionReturn(0); 479 } 480 481 #undef __FUNCT__ 482 #define __FUNCT__ "MatFDColoringApply" 483 /*@ 484 MatFDColoringApply - Given a matrix for which a MatFDColoring context 485 has been created, computes the Jacobian for a function via finite differences. 486 487 Collective on MatFDColoring 488 489 Input Parameters: 490 + mat - location to store Jacobian 491 . coloring - coloring context created with MatFDColoringCreate() 492 . x1 - location at which Jacobian is to be computed 493 - sctx - context required by function, if this is being used with the SNES solver then it is SNES object, otherwise it is null 494 495 Options Database Keys: 496 + -mat_fd_type - "wp" or "ds" (see MATMFFD_WP or MATMFFD_DS) 497 . -mat_fd_coloring_view - Activates basic viewing or coloring 498 . -mat_fd_coloring_view draw - Activates drawing of coloring 499 - -mat_fd_coloring_view ::ascii_info - Activates viewing of coloring info 500 501 Level: intermediate 502 503 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringSetFunction() 504 505 .keywords: coloring, Jacobian, finite differences 506 @*/ 507 PetscErrorCode MatFDColoringApply(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 508 { 509 PetscErrorCode ierr; 510 511 PetscFunctionBegin; 512 PetscValidHeaderSpecific(J,MAT_CLASSID,1); 513 PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_CLASSID,2); 514 PetscValidHeaderSpecific(x1,VEC_CLASSID,3); 515 if (!coloring->f) SETERRQ(PetscObjectComm((PetscObject)J),PETSC_ERR_ARG_WRONGSTATE,"Must call MatFDColoringSetFunction()"); 516 if (!J->ops->fdcoloringapply) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not supported for this matrix type %s",((PetscObject)J)->type_name); 517 ierr = PetscLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr); 518 ierr = (*J->ops->fdcoloringapply)(J,coloring,x1,flag,sctx);CHKERRQ(ierr); 519 ierr = PetscLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr); 520 PetscFunctionReturn(0); 521 } 522 523 /* #define JACOBIANCOLOROPT */ 524 #if defined(JACOBIANCOLOROPT) 525 #include <petsctime.h> 526 #endif 527 #undef __FUNCT__ 528 #define __FUNCT__ "MatFDColoringApply_AIJ" 529 PetscErrorCode MatFDColoringApply_AIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 530 { 531 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 532 PetscErrorCode ierr; 533 PetscInt k,start,end,l,row,col,srow,**vscaleforrow; 534 PetscScalar dx,*y,*xx,*w3_array; 535 PetscScalar *vscale_array; 536 PetscReal epsilon = coloring->error_rel,umin = coloring->umin,unorm; 537 Vec w1 = coloring->w1,w2=coloring->w2,w3; 538 void *fctx = coloring->fctx; 539 PetscBool flg = PETSC_FALSE; 540 PetscInt ctype = coloring->ctype,N,col_start=0,col_end=0; 541 Vec x1_tmp; 542 #if defined(JACOBIANCOLOROPT) 543 PetscLogDouble t0,t1,time_setvalues=0.0; 544 #endif 545 546 PetscFunctionBegin; 547 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 548 ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 549 if (flg) { 550 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 551 } else { 552 PetscBool assembled; 553 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 554 if (assembled) { 555 ierr = MatZeroEntries(J);CHKERRQ(ierr); 556 } 557 } 558 559 x1_tmp = x1; 560 if (!coloring->vscale) { 561 ierr = VecDuplicate(x1_tmp,&coloring->vscale);CHKERRQ(ierr); 562 } 563 564 if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/ 565 ierr = VecNorm(x1_tmp,NORM_2,&unorm);CHKERRQ(ierr); 566 } 567 ierr = VecGetOwnershipRange(w1,&start,&end);CHKERRQ(ierr); /* OwnershipRange is used by ghosted x! */ 568 569 /* Set w1 = F(x1) */ 570 if (!coloring->fset) { 571 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 572 ierr = (*f)(sctx,x1_tmp,w1,fctx);CHKERRQ(ierr); 573 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 574 } else { 575 coloring->fset = PETSC_FALSE; 576 } 577 578 if (!coloring->w3) { 579 ierr = VecDuplicate(x1_tmp,&coloring->w3);CHKERRQ(ierr); 580 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 581 } 582 w3 = coloring->w3; 583 584 /* Compute all the local scale factors, including ghost points */ 585 ierr = VecGetLocalSize(x1_tmp,&N);CHKERRQ(ierr); 586 ierr = VecGetArray(x1_tmp,&xx);CHKERRQ(ierr); 587 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 588 if (ctype == IS_COLORING_GHOSTED) { 589 col_start = 0; col_end = N; 590 } else if (ctype == IS_COLORING_GLOBAL) { 591 xx = xx - start; 592 vscale_array = vscale_array - start; 593 col_start = start; col_end = N + start; 594 } 595 for (col=col_start; col<col_end; col++) { 596 /* Loop over each local column, vscale[col] = 1./(epsilon*dx[col]) */ 597 if (coloring->htype[0] == 'w') { 598 dx = 1.0 + unorm; 599 } else { 600 dx = xx[col]; 601 } 602 if (dx == (PetscScalar)0.0) dx = 1.0; 603 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 604 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 605 dx *= epsilon; 606 vscale_array[col] = (PetscScalar)1.0/dx; 607 } 608 if (ctype == IS_COLORING_GLOBAL) vscale_array = vscale_array + start; 609 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 610 if (ctype == IS_COLORING_GLOBAL) { 611 ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 612 ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 613 } 614 615 if (coloring->vscaleforrow) { 616 vscaleforrow = coloring->vscaleforrow; 617 } else SETERRQ(PetscObjectComm((PetscObject)J),PETSC_ERR_ARG_NULL,"Null Object: coloring->vscaleforrow"); 618 619 /* 620 Loop over each color 621 */ 622 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 623 for (k=0; k<coloring->ncolors; k++) { 624 coloring->currentcolor = k; 625 626 ierr = VecCopy(x1_tmp,w3);CHKERRQ(ierr); 627 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 628 if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array - start; 629 /* 630 Loop over each column associated with color 631 adding the perturbation to the vector w3. 632 */ 633 for (l=0; l<coloring->ncolumns[k]; l++) { 634 col = coloring->columns[k][l]; /* local column of the matrix we are probing for */ 635 if (coloring->htype[0] == 'w') { 636 dx = 1.0 + unorm; 637 } else { 638 dx = xx[col]; 639 } 640 if (dx == (PetscScalar)0.0) dx = 1.0; 641 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 642 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 643 dx *= epsilon; 644 if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); 645 w3_array[col] += dx; 646 } 647 if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array + start; 648 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 649 650 /* 651 Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 652 w2 = F(x1 + dx) - F(x1) 653 */ 654 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 655 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 656 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 657 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 658 659 /* 660 Loop over rows of vector, putting results into Jacobian matrix 661 */ 662 #if defined(JACOBIANCOLOROPT) 663 ierr = PetscTime(&t0);CHKERRQ(ierr); 664 #endif 665 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 666 for (l=0; l<coloring->nrows[k]; l++) { 667 row = coloring->rows[k][l]; /* local row index */ 668 col = coloring->columnsforrow[k][l]; /* global column index */ 669 y[row] *= vscale_array[vscaleforrow[k][l]]; 670 srow = row + start; 671 ierr = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 672 } 673 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 674 #if defined(JACOBIANCOLOROPT) 675 ierr = PetscTime(&t1);CHKERRQ(ierr); 676 time_setvalues += t1-t0; 677 #endif 678 } /* endof for each color */ 679 #if defined(JACOBIANCOLOROPT) 680 printf(" MatFDColoringApply_AIJ: time_setvalues %g\n",time_setvalues); 681 #endif 682 if (ctype == IS_COLORING_GLOBAL) xx = xx + start; 683 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 684 ierr = VecRestoreArray(x1_tmp,&xx);CHKERRQ(ierr); 685 686 coloring->currentcolor = -1; 687 688 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 689 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 690 691 ierr = MatFDColoringViewFromOptions(coloring,NULL,"-mat_fd_coloring_view");CHKERRQ(ierr); 692 PetscFunctionReturn(0); 693 } 694