/* This is where the abstract matrix operations are defined that are used for finite difference computations of Jacobians using coloring. */ #include /*I "petscmat.h" I*/ #undef __FUNCT__ #define __FUNCT__ "MatFDColoringSetF" PetscErrorCode MatFDColoringSetF(MatFDColoring fd,Vec F) { PetscErrorCode ierr; PetscFunctionBegin; if (F) { ierr = VecCopy(F,fd->w1);CHKERRQ(ierr); fd->fset = PETSC_TRUE; } else { fd->fset = PETSC_FALSE; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringView_Draw_Zoom" static PetscErrorCode MatFDColoringView_Draw_Zoom(PetscDraw draw,void *Aa) { MatFDColoring fd = (MatFDColoring)Aa; PetscErrorCode ierr; PetscInt i,j; PetscReal x,y; PetscFunctionBegin; /* loop over colors */ for (i=0; incolors; i++) { for (j=0; jnrows[i]; j++) { y = fd->M - fd->rows[i][j] - fd->rstart; x = fd->columnsforrow[i][j]; ierr = PetscDrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr); } } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringView_Draw" static PetscErrorCode MatFDColoringView_Draw(MatFDColoring fd,PetscViewer viewer) { PetscErrorCode ierr; PetscBool isnull; PetscDraw draw; PetscReal xr,yr,xl,yl,h,w; PetscFunctionBegin; ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); xr = fd->N; yr = fd->M; h = yr/10.0; w = xr/10.0; xr += w; yr += h; xl = -w; yl = -h; ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); ierr = PetscDrawZoom(draw,MatFDColoringView_Draw_Zoom,fd);CHKERRQ(ierr); ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringView" /*@C MatFDColoringView - Views a finite difference coloring context. Collective on MatFDColoring Input Parameters: + c - the coloring context - viewer - visualization context Level: intermediate Notes: The available visualization contexts include + PETSC_VIEWER_STDOUT_SELF - standard output (default) . PETSC_VIEWER_STDOUT_WORLD - synchronized standard output where only the first processor opens the file. All other processors send their data to the first processor to print. - PETSC_VIEWER_DRAW_WORLD - graphical display of nonzero structure Notes: Since PETSc uses only a small number of basic colors (currently 33), if the coloring involves more than 33 then some seemingly identical colors are displayed making it look like an illegal coloring. This is just a graphical artifact. .seealso: MatFDColoringCreate() .keywords: Mat, finite differences, coloring, view @*/ PetscErrorCode MatFDColoringView(MatFDColoring c,PetscViewer viewer) { PetscErrorCode ierr; PetscInt i,j; PetscBool isdraw,iascii; PetscViewerFormat format; PetscFunctionBegin; PetscValidHeaderSpecific(c,MAT_FDCOLORING_CLASSID,1); if (!viewer) { ierr = PetscViewerASCIIGetStdout(((PetscObject)c)->comm,&viewer);CHKERRQ(ierr); } PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); PetscCheckSameComm(c,1,viewer,2); ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); if (isdraw) { ierr = MatFDColoringView_Draw(c,viewer);CHKERRQ(ierr); } else if (iascii) { ierr = PetscObjectPrintClassNamePrefixType((PetscObject)c,viewer,"MatFDColoring Object");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Error tolerance=%G\n",c->error_rel);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Umin=%G\n",c->umin);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Number of colors=%D\n",c->ncolors);CHKERRQ(ierr); ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); if (format != PETSC_VIEWER_ASCII_INFO) { for (i=0; incolors; i++) { ierr = PetscViewerASCIIPrintf(viewer," Information for color %D\n",i);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Number of columns %D\n",c->ncolumns[i]);CHKERRQ(ierr); for (j=0; jncolumns[i]; j++) { ierr = PetscViewerASCIIPrintf(viewer," %D\n",c->columns[i][j]);CHKERRQ(ierr); } ierr = PetscViewerASCIIPrintf(viewer," Number of rows %D\n",c->nrows[i]);CHKERRQ(ierr); for (j=0; jnrows[i]; j++) { ierr = PetscViewerASCIIPrintf(viewer," %D %D \n",c->rows[i][j],c->columnsforrow[i][j]);CHKERRQ(ierr); } } } ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringSetParameters" /*@ MatFDColoringSetParameters - Sets the parameters for the sparse approximation of a Jacobian matrix using finite differences. Logically Collective on MatFDColoring The Jacobian is estimated with the differencing approximation .vb F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where h = error_rel*u[i] if abs(u[i]) > umin = +/- error_rel*umin otherwise, with +/- determined by the sign of u[i] dx_{i} = (0, ... 1, .... 0) .ve Input Parameters: + coloring - the coloring context . error_rel - relative error - umin - minimum allowable u-value magnitude Level: advanced .keywords: Mat, finite differences, coloring, set, parameters .seealso: MatFDColoringCreate(), MatFDColoringSetFromOptions() @*/ PetscErrorCode MatFDColoringSetParameters(MatFDColoring matfd,PetscReal error,PetscReal umin) { PetscFunctionBegin; PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1); PetscValidLogicalCollectiveReal(matfd,error,2); PetscValidLogicalCollectiveReal(matfd,umin,3); if (error != PETSC_DEFAULT) matfd->error_rel = error; if (umin != PETSC_DEFAULT) matfd->umin = umin; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringGetFunction" /*@C MatFDColoringGetFunction - Gets the function to use for computing the Jacobian. Not Collective Input Parameters: . coloring - the coloring context Output Parameters: + f - the function - fctx - the optional user-defined function context Level: intermediate .keywords: Mat, Jacobian, finite differences, set, function .seealso: MatFDColoringCreate(), MatFDColoringSetFunction(), MatFDColoringSetFromOptions() @*/ PetscErrorCode MatFDColoringGetFunction(MatFDColoring matfd,PetscErrorCode (**f)(void),void **fctx) { PetscFunctionBegin; PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1); if (f) *f = matfd->f; if (fctx) *fctx = matfd->fctx; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringSetFunction" /*@C MatFDColoringSetFunction - Sets the function to use for computing the Jacobian. Logically Collective on MatFDColoring Input Parameters: + coloring - the coloring context . f - the function - fctx - the optional user-defined function context Calling sequence of (*f) function: For SNES: PetscErrorCode (*f)(SNES,Vec,Vec,void*) If not using SNES: PetscErrorCode (*f)(void *dummy,Vec,Vec,void*) and dummy is ignored Level: advanced Notes: This function is usually used automatically by SNES (when one uses SNESSetJacobian() with the argument SNESDefaultComputeJacobianColor()) and only needs to be used by someone computing a matrix via coloring directly by calling MatFDColoringApply() Fortran Notes: In Fortran you must call MatFDColoringSetFunction() for a coloring object to be used without SNES or within the SNES solvers. .keywords: Mat, Jacobian, finite differences, set, function .seealso: MatFDColoringCreate(), MatFDColoringGetFunction(), MatFDColoringSetFromOptions() @*/ PetscErrorCode MatFDColoringSetFunction(MatFDColoring matfd,PetscErrorCode (*f)(void),void *fctx) { PetscFunctionBegin; PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1); matfd->f = f; matfd->fctx = fctx; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringSetFromOptions" /*@ MatFDColoringSetFromOptions - Sets coloring finite difference parameters from the options database. Collective on MatFDColoring The Jacobian, F'(u), is estimated with the differencing approximation .vb F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where h = error_rel*u[i] if abs(u[i]) > umin = +/- error_rel*umin otherwise, with +/- determined by the sign of u[i] dx_{i} = (0, ... 1, .... 0) .ve Input Parameter: . coloring - the coloring context Options Database Keys: + -mat_fd_coloring_err - Sets (square root of relative error in the function) . -mat_fd_coloring_umin - Sets umin, the minimum allowable u-value magnitude . -mat_fd_type - "wp" or "ds" (see MATMFFD_WP or MATMFFD_DS) . -mat_fd_coloring_view - Activates basic viewing . -mat_fd_coloring_view ::ascii_info - Activates viewing info - -mat_fd_coloring_view draw - Activates drawing Level: intermediate .keywords: Mat, finite differences, parameters .seealso: MatFDColoringCreate(), MatFDColoringView(), MatFDColoringSetParameters() @*/ PetscErrorCode MatFDColoringSetFromOptions(MatFDColoring matfd) { PetscErrorCode ierr; PetscBool flg; char value[3]; PetscFunctionBegin; PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1); ierr = PetscObjectOptionsBegin((PetscObject)matfd);CHKERRQ(ierr); ierr = PetscOptionsReal("-mat_fd_coloring_err","Square root of relative error in function","MatFDColoringSetParameters",matfd->error_rel,&matfd->error_rel,0);CHKERRQ(ierr); ierr = PetscOptionsReal("-mat_fd_coloring_umin","Minimum allowable u magnitude","MatFDColoringSetParameters",matfd->umin,&matfd->umin,0);CHKERRQ(ierr); ierr = PetscOptionsString("-mat_fd_type","Algorithm to compute h, wp or ds","MatFDColoringCreate",matfd->htype,value,3,&flg);CHKERRQ(ierr); if (flg) { if (value[0] == 'w' && value[1] == 'p') matfd->htype = "wp"; else if (value[0] == 'd' && value[1] == 's') matfd->htype = "ds"; else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Unknown finite differencing type %s",value); } /* process any options handlers added with PetscObjectAddOptionsHandler() */ ierr = PetscObjectProcessOptionsHandlers((PetscObject)matfd);CHKERRQ(ierr); PetscOptionsEnd();CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringViewFromOptions" PetscErrorCode MatFDColoringViewFromOptions(MatFDColoring fd,const char optionname[]) { PetscErrorCode ierr; PetscBool flg; PetscViewer viewer; PetscViewerFormat format; PetscFunctionBegin; ierr = PetscOptionsGetViewer(((PetscObject)fd)->comm,((PetscObject)fd)->prefix,optionname,&viewer,&format,&flg);CHKERRQ(ierr); if (flg) { ierr = PetscViewerPushFormat(viewer,format);CHKERRQ(ierr); ierr = MatFDColoringView(fd,viewer);CHKERRQ(ierr); ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringCreate" /*@ MatFDColoringCreate - Creates a matrix coloring context for finite difference computation of Jacobians. Collective on Mat Input Parameters: + mat - the matrix containing the nonzero structure of the Jacobian - iscoloring - the coloring of the matrix; usually obtained with MatGetColoring() or DMCreateColoring() Output Parameter: . color - the new coloring context Level: intermediate .seealso: MatFDColoringDestroy(),SNESDefaultComputeJacobianColor(), ISColoringCreate(), MatFDColoringSetFunction(), MatFDColoringSetFromOptions(), MatFDColoringApply(), MatFDColoringView(), MatFDColoringSetParameters(), MatGetColoring(), DMCreateColoring() @*/ PetscErrorCode MatFDColoringCreate(Mat mat,ISColoring iscoloring,MatFDColoring *color) { MatFDColoring c; MPI_Comm comm; PetscErrorCode ierr; PetscInt M,N; PetscFunctionBegin; ierr = PetscLogEventBegin(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr); ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr); if (M != N) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_SUP,"Only for square matrices"); ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); ierr = PetscHeaderCreate(c,_p_MatFDColoring,int,MAT_FDCOLORING_CLASSID,0,"MatFDColoring","Jacobian computation via finite differences with coloring","Mat",comm,MatFDColoringDestroy,MatFDColoringView);CHKERRQ(ierr); c->ctype = iscoloring->ctype; if (mat->ops->fdcoloringcreate) { ierr = (*mat->ops->fdcoloringcreate)(mat,iscoloring,c);CHKERRQ(ierr); } else SETERRQ1(((PetscObject)mat)->comm,PETSC_ERR_SUP,"Code not yet written for matrix type %s",((PetscObject)mat)->type_name); ierr = MatGetVecs(mat,PETSC_NULL,&c->w1);CHKERRQ(ierr); ierr = PetscLogObjectParent(c,c->w1);CHKERRQ(ierr); ierr = VecDuplicate(c->w1,&c->w2);CHKERRQ(ierr); ierr = PetscLogObjectParent(c,c->w2);CHKERRQ(ierr); c->error_rel = PETSC_SQRT_MACHINE_EPSILON; c->umin = 100.0*PETSC_SQRT_MACHINE_EPSILON; c->currentcolor = -1; c->htype = "wp"; c->fset = PETSC_FALSE; *color = c; ierr = PetscObjectCompose((PetscObject)mat,"SNESMatFDColoring",(PetscObject)c);CHKERRQ(ierr); ierr = PetscLogEventEnd(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringDestroy" /*@ MatFDColoringDestroy - Destroys a matrix coloring context that was created via MatFDColoringCreate(). Collective on MatFDColoring Input Parameter: . c - coloring context Level: intermediate .seealso: MatFDColoringCreate() @*/ PetscErrorCode MatFDColoringDestroy(MatFDColoring *c) { PetscErrorCode ierr; PetscInt i; PetscFunctionBegin; if (!*c) PetscFunctionReturn(0); if (--((PetscObject)(*c))->refct > 0) {*c = 0; PetscFunctionReturn(0);} for (i=0; i<(*c)->ncolors; i++) { ierr = PetscFree((*c)->columns[i]);CHKERRQ(ierr); ierr = PetscFree((*c)->rows[i]);CHKERRQ(ierr); ierr = PetscFree((*c)->columnsforrow[i]);CHKERRQ(ierr); if ((*c)->vscaleforrow) {ierr = PetscFree((*c)->vscaleforrow[i]);CHKERRQ(ierr);} } ierr = PetscFree((*c)->ncolumns);CHKERRQ(ierr); ierr = PetscFree((*c)->columns);CHKERRQ(ierr); ierr = PetscFree((*c)->nrows);CHKERRQ(ierr); ierr = PetscFree((*c)->rows);CHKERRQ(ierr); ierr = PetscFree((*c)->columnsforrow);CHKERRQ(ierr); ierr = PetscFree((*c)->vscaleforrow);CHKERRQ(ierr); ierr = VecDestroy(&(*c)->vscale);CHKERRQ(ierr); ierr = VecDestroy(&(*c)->w1);CHKERRQ(ierr); ierr = VecDestroy(&(*c)->w2);CHKERRQ(ierr); ierr = VecDestroy(&(*c)->w3);CHKERRQ(ierr); ierr = PetscHeaderDestroy(c);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringGetPerturbedColumns" /*@C MatFDColoringGetPerturbedColumns - Returns the indices of the columns that that are currently being perturbed. Not Collective Input Parameters: . coloring - coloring context created with MatFDColoringCreate() Output Parameters: + n - the number of local columns being perturbed - cols - the column indices, in global numbering Level: intermediate .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringApply() .keywords: coloring, Jacobian, finite differences @*/ PetscErrorCode MatFDColoringGetPerturbedColumns(MatFDColoring coloring,PetscInt *n,PetscInt *cols[]) { PetscFunctionBegin; if (coloring->currentcolor >= 0) { *n = coloring->ncolumns[coloring->currentcolor]; *cols = coloring->columns[coloring->currentcolor]; } else { *n = 0; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringApply" /*@ MatFDColoringApply - Given a matrix for which a MatFDColoring context has been created, computes the Jacobian for a function via finite differences. Collective on MatFDColoring Input Parameters: + mat - location to store Jacobian . coloring - coloring context created with MatFDColoringCreate() . x1 - location at which Jacobian is to be computed - sctx - context required by function, if this is being used with the SNES solver then it is SNES object, otherwise it is null Options Database Keys: + -mat_fd_type - "wp" or "ds" (see MATMFFD_WP or MATMFFD_DS) . -mat_fd_coloring_view - Activates basic viewing or coloring . -mat_fd_coloring_view draw - Activates drawing of coloring - -mat_fd_coloring_view ::ascii_info - Activates viewing of coloring info Level: intermediate .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringSetFunction() .keywords: coloring, Jacobian, finite differences @*/ PetscErrorCode MatFDColoringApply(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(J,MAT_CLASSID,1); PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_CLASSID,2); PetscValidHeaderSpecific(x1,VEC_CLASSID,3); if (!coloring->f) SETERRQ(((PetscObject)J)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must call MatFDColoringSetFunction()"); if (!J->ops->fdcoloringapply) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not supported for this matrix type %s",((PetscObject)J)->type_name); ierr = (*J->ops->fdcoloringapply)(J,coloring,x1,flag,sctx);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFDColoringApply_AIJ" PetscErrorCode MatFDColoringApply_AIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) { PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; PetscErrorCode ierr; PetscInt k,start,end,l,row,col,srow,**vscaleforrow; PetscScalar dx,*y,*xx,*w3_array; PetscScalar *vscale_array; PetscReal epsilon = coloring->error_rel,umin = coloring->umin,unorm; Vec w1 = coloring->w1,w2=coloring->w2,w3; void *fctx = coloring->fctx; PetscBool flg = PETSC_FALSE; PetscInt ctype = coloring->ctype,N,col_start=0,col_end=0; Vec x1_tmp; PetscFunctionBegin; PetscValidHeaderSpecific(J,MAT_CLASSID,1); PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_CLASSID,2); PetscValidHeaderSpecific(x1,VEC_CLASSID,3); if (!f) SETERRQ(((PetscObject)J)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must call MatFDColoringSetFunction()"); ierr = PetscLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr); ierr = MatSetUnfactored(J);CHKERRQ(ierr); ierr = PetscOptionsGetBool(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&flg,PETSC_NULL);CHKERRQ(ierr); if (flg) { ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); } else { PetscBool assembled; ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); if (assembled) { ierr = MatZeroEntries(J);CHKERRQ(ierr); } } x1_tmp = x1; if (!coloring->vscale) { ierr = VecDuplicate(x1_tmp,&coloring->vscale);CHKERRQ(ierr); } if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/ ierr = VecNorm(x1_tmp,NORM_2,&unorm);CHKERRQ(ierr); } ierr = VecGetOwnershipRange(w1,&start,&end);CHKERRQ(ierr); /* OwnershipRange is used by ghosted x! */ /* Set w1 = F(x1) */ if (!coloring->fset) { ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); ierr = (*f)(sctx,x1_tmp,w1,fctx);CHKERRQ(ierr); ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); } else { coloring->fset = PETSC_FALSE; } if (!coloring->w3) { ierr = VecDuplicate(x1_tmp,&coloring->w3);CHKERRQ(ierr); ierr = PetscLogObjectParent(coloring,coloring->w3);CHKERRQ(ierr); } w3 = coloring->w3; /* Compute all the local scale factors, including ghost points */ ierr = VecGetLocalSize(x1_tmp,&N);CHKERRQ(ierr); ierr = VecGetArray(x1_tmp,&xx);CHKERRQ(ierr); ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); if (ctype == IS_COLORING_GHOSTED) { col_start = 0; col_end = N; } else if (ctype == IS_COLORING_GLOBAL) { xx = xx - start; vscale_array = vscale_array - start; col_start = start; col_end = N + start; } for (col=col_start; colhtype[0] == 'w') { dx = 1.0 + unorm; } else { dx = xx[col]; } if (dx == (PetscScalar)0.0) dx = 1.0; if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; dx *= epsilon; vscale_array[col] = (PetscScalar)1.0/dx; } if (ctype == IS_COLORING_GLOBAL) vscale_array = vscale_array + start; ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); if (ctype == IS_COLORING_GLOBAL) { ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); } if (coloring->vscaleforrow) { vscaleforrow = coloring->vscaleforrow; } else SETERRQ(((PetscObject)J)->comm,PETSC_ERR_ARG_NULL,"Null Object: coloring->vscaleforrow"); /* Loop over each color */ ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); for (k=0; kncolors; k++) { coloring->currentcolor = k; ierr = VecCopy(x1_tmp,w3);CHKERRQ(ierr); ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array - start; /* Loop over each column associated with color adding the perturbation to the vector w3. */ for (l=0; lncolumns[k]; l++) { col = coloring->columns[k][l]; /* local column of the matrix we are probing for */ if (coloring->htype[0] == 'w') { dx = 1.0 + unorm; } else { dx = xx[col]; } if (dx == (PetscScalar)0.0) dx = 1.0; if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; dx *= epsilon; if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); w3_array[col] += dx; } if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); /* Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) w2 = F(x1 + dx) - F(x1) */ ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); /* Loop over rows of vector, putting results into Jacobian matrix */ ierr = VecGetArray(w2,&y);CHKERRQ(ierr); for (l=0; lnrows[k]; l++) { row = coloring->rows[k][l]; /* local row index */ col = coloring->columnsforrow[k][l]; /* global column index */ y[row] *= vscale_array[vscaleforrow[k][l]]; srow = row + start; ierr = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); } ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); } /* endof for each color */ if (ctype == IS_COLORING_GLOBAL) xx = xx + start; ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); ierr = VecRestoreArray(x1_tmp,&xx);CHKERRQ(ierr); coloring->currentcolor = -1; ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = PetscLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr); ierr = MatFDColoringViewFromOptions(coloring,"-mat_fd_coloring_view");CHKERRQ(ierr); PetscFunctionReturn(0); }