#include /*I "petscsnes.h" I*/ #include /*@C SNESComputeJacobianDefault - Computes the Jacobian using finite differences. Collective on SNES Input Parameters: + snes - the SNES context . x1 - compute Jacobian at this point - ctx - application's function context, as set with SNESSetFunction() Output Parameters: + J - Jacobian matrix (not altered in this routine) - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) Options Database Key: + -snes_fd - Activates SNESComputeJacobianDefault() . -snes_test_err - Square root of function error tolerance, default square root of machine epsilon (1.e-8 in double, 3.e-4 in single) - -mat_fd_type - Either wp or ds (see MATMFFD_WP or MATMFFD_DS) Notes: This routine is slow and expensive, and is not currently optimized to take advantage of sparsity in the problem. Although SNESComputeJacobianDefault() is not recommended for general use in large-scale applications, It can be useful in checking the correctness of a user-provided Jacobian. An alternative routine that uses coloring to exploit matrix sparsity is SNESComputeJacobianDefaultColor(). This routine ignores the maximum number of function evaluations set with SNESSetTolerances() and the function evaluations it performs are not counted in what is returned by of SNESGetNumberFunctionEvals(). Level: intermediate .seealso: SNESSetJacobian(), SNESComputeJacobianDefaultColor(), MatCreateSNESMF() @*/ PetscErrorCode SNESComputeJacobianDefault(SNES snes,Vec x1,Mat J,Mat B,void *ctx) { Vec j1a,j2a,x2; PetscErrorCode ierr; PetscInt i,N,start,end,j,value,root,max_funcs = snes->max_funcs; PetscScalar dx,*y,wscale; const PetscScalar *xx; PetscReal amax,epsilon = PETSC_SQRT_MACHINE_EPSILON; PetscReal dx_min = 1.e-16,dx_par = 1.e-1,unorm; MPI_Comm comm; PetscBool assembled,use_wp = PETSC_TRUE,flg; const char *list[2] = {"ds","wp"}; PetscMPIInt size; const PetscInt *ranges; DM dm; DMSNES dms; PetscFunctionBegin; snes->max_funcs = PETSC_MAX_INT; /* Since this Jacobian will possibly have "extra" nonzero locations just turn off errors for these locations */ ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE);CHKERRQ(ierr); ierr = PetscOptionsGetReal(((PetscObject)snes)->options,((PetscObject)snes)->prefix,"-snes_test_err",&epsilon,NULL);CHKERRQ(ierr); ierr = PetscObjectGetComm((PetscObject)x1,&comm);CHKERRQ(ierr); ierr = MPI_Comm_size(comm,&size);CHKERRMPI(ierr); ierr = MatAssembled(B,&assembled);CHKERRQ(ierr); if (assembled) { ierr = MatZeroEntries(B);CHKERRQ(ierr); } if (!snes->nvwork) { if (snes->dm) { ierr = DMGetGlobalVector(snes->dm,&j1a);CHKERRQ(ierr); ierr = DMGetGlobalVector(snes->dm,&j2a);CHKERRQ(ierr); ierr = DMGetGlobalVector(snes->dm,&x2);CHKERRQ(ierr); } else { snes->nvwork = 3; ierr = VecDuplicateVecs(x1,snes->nvwork,&snes->vwork);CHKERRQ(ierr); ierr = PetscLogObjectParents(snes,snes->nvwork,snes->vwork);CHKERRQ(ierr); j1a = snes->vwork[0]; j2a = snes->vwork[1]; x2 = snes->vwork[2]; } } ierr = VecGetSize(x1,&N);CHKERRQ(ierr); ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); ierr = DMGetDMSNES(dm,&dms);CHKERRQ(ierr); if (dms->ops->computemffunction) { ierr = SNESComputeMFFunction(snes,x1,j1a);CHKERRQ(ierr); } else { ierr = SNESComputeFunction(snes,x1,j1a);CHKERRQ(ierr); } ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)snes),((PetscObject)snes)->prefix,"Differencing options","SNES");CHKERRQ(ierr); ierr = PetscOptionsEList("-mat_fd_type","Algorithm to compute difference parameter","SNESComputeJacobianDefault",list,2,"wp",&value,&flg);CHKERRQ(ierr); ierr = PetscOptionsEnd();CHKERRQ(ierr); if (flg && !value) use_wp = PETSC_FALSE; if (use_wp) { ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); } /* Compute Jacobian approximation, 1 column at a time. x1 = current iterate, j1a = F(x1) x2 = perturbed iterate, j2a = F(x2) */ for (i=0; i= start && iops->computemffunction) { ierr = SNESComputeMFFunction(snes,x2,j2a);CHKERRQ(ierr); } else { ierr = SNESComputeFunction(snes,x2,j2a);CHKERRQ(ierr); } ierr = VecAXPY(j2a,-1.0,j1a);CHKERRQ(ierr); /* Communicate scale=1/dx_i to all processors */ ierr = VecGetOwnershipRanges(x1,&ranges);CHKERRQ(ierr); root = size; for (j=size-1; j>-1; j--) { root--; if (i>=ranges[j]) break; } ierr = MPI_Bcast(&wscale,1,MPIU_SCALAR,root,comm);CHKERRMPI(ierr); ierr = VecScale(j2a,wscale);CHKERRQ(ierr); ierr = VecNorm(j2a,NORM_INFINITY,&amax);CHKERRQ(ierr); amax *= 1.e-14; ierr = VecGetArray(j2a,&y);CHKERRQ(ierr); for (j=start; j amax || j == i) { ierr = MatSetValues(B,1,&j,1,&i,y+j-start,INSERT_VALUES);CHKERRQ(ierr); } } ierr = VecRestoreArray(j2a,&y);CHKERRQ(ierr); } if (snes->dm) { ierr = DMRestoreGlobalVector(snes->dm,&j1a);CHKERRQ(ierr); ierr = DMRestoreGlobalVector(snes->dm,&j2a);CHKERRQ(ierr); ierr = DMRestoreGlobalVector(snes->dm,&x2);CHKERRQ(ierr); } ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); if (B != J) { ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); } snes->max_funcs = max_funcs; snes->nfuncs -= N; PetscFunctionReturn(0); }