1 #ifdef PETSC_RCS_HEADER 2 static char vcid[] = "$Id: snesj.c,v 1.44 1997/09/25 22:42:32 curfman Exp bsmith $"; 3 #endif 4 5 #include "src/snes/snesimpl.h" /*I "snes.h" I*/ 6 7 #undef __FUNC__ 8 #define __FUNC__ "SNESDefaultComputeJacobian" 9 /*@C 10 SNESDefaultComputeJacobian - Computes the Jacobian using finite differences. 11 12 Input Parameters: 13 . x1 - compute Jacobian at this point 14 . ctx - application's function context, as set with SNESSetFunction() 15 16 Output Parameters: 17 . J - Jacobian matrix (not altered in this routine) 18 . B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 19 . flag - flag indicating whether the matrix sparsity structure has changed 20 21 Options Database Key: 22 $ -snes_fd 23 24 Notes: 25 This routine is slow and expensive, and is not currently optimized 26 to take advantage of sparsity in the problem. Although 27 SNESDefaultComputeJacobian() is not recommended for general use 28 in large-scale applications, It can be useful in checking the 29 correctness of a user-provided Jacobian. 30 31 An alternative routine that uses coloring to explot matrix sparsity is 32 SNESDefaultComputeJacobianWithColoring(). 33 34 .keywords: SNES, finite differences, Jacobian 35 36 .seealso: SNESSetJacobian(), SNESDefaultComputeJacobianWithColoring() 37 @*/ 38 int SNESDefaultComputeJacobian(SNES snes,Vec x1,Mat *J,Mat *B,MatStructure *flag,void *ctx) 39 { 40 Vec j1,j2,x2; 41 int i,ierr,N,start,end,j; 42 Scalar dx, mone = -1.0,*y,scale,*xx,wscale; 43 double amax, epsilon = 1.e-8; /* assumes double precision */ 44 double dx_min = 1.e-16, dx_par = 1.e-1; 45 MPI_Comm comm; 46 int (*eval_fct)(SNES,Vec,Vec); 47 48 PetscFunctionBegin; 49 if (snes->method_class == SNES_NONLINEAR_EQUATIONS) eval_fct = SNESComputeFunction; 50 else if (snes->method_class == SNES_UNCONSTRAINED_MINIMIZATION) eval_fct = SNESComputeGradient; 51 else SETERRQ(1,0,"Invalid method class"); 52 53 PetscObjectGetComm((PetscObject)x1,&comm); 54 MatZeroEntries(*B); 55 if (!snes->nvwork) { 56 ierr = VecDuplicateVecs(x1,3,&snes->vwork); CHKERRQ(ierr); 57 snes->nvwork = 3; 58 PLogObjectParents(snes,3,snes->vwork); 59 } 60 j1 = snes->vwork[0]; j2 = snes->vwork[1]; x2 = snes->vwork[2]; 61 62 ierr = VecGetSize(x1,&N); CHKERRQ(ierr); 63 ierr = VecGetOwnershipRange(x1,&start,&end); CHKERRQ(ierr); 64 VecGetArray(x1,&xx); 65 ierr = eval_fct(snes,x1,j1); CHKERRQ(ierr); 66 67 /* Compute Jacobian approximation, 1 column at a time. 68 x1 = current iterate, j1 = F(x1) 69 x2 = perturbed iterate, j2 = F(x2) 70 */ 71 for ( i=0; i<N; i++ ) { 72 ierr = VecCopy(x1,x2); CHKERRQ(ierr); 73 if ( i>= start && i<end) { 74 dx = xx[i-start]; 75 #if !defined(USE_PETSC_COMPLEX) 76 if (dx < dx_min && dx >= 0.0) dx = dx_par; 77 else if (dx < 0.0 && dx > -dx_min) dx = -dx_par; 78 #else 79 if (abs(dx) < dx_min && real(dx) >= 0.0) dx = dx_par; 80 else if (real(dx) < 0.0 && abs(dx) < dx_min) dx = -dx_par; 81 #endif 82 dx *= epsilon; 83 wscale = 1.0/dx; 84 VecSetValues(x2,1,&i,&dx,ADD_VALUES); 85 } 86 else { 87 wscale = 0.0; 88 } 89 ierr = eval_fct(snes,x2,j2); CHKERRQ(ierr); 90 ierr = VecAXPY(&mone,j1,j2); CHKERRQ(ierr); 91 /* Communicate scale to all processors */ 92 #if !defined(USE_PETSC_COMPLEX) 93 MPI_Allreduce(&wscale,&scale,1,MPI_DOUBLE,MPI_SUM,comm); 94 #else 95 MPI_Allreduce(&wscale,&scale,2,MPI_DOUBLE,MPI_SUM,comm); 96 #endif 97 VecScale(&scale,j2); 98 VecGetArray(j2,&y); 99 VecNorm(j2,NORM_INFINITY,&amax); amax *= 1.e-14; 100 for ( j=start; j<end; j++ ) { 101 if (PetscAbsScalar(y[j-start]) > amax) { 102 ierr = MatSetValues(*B,1,&j,1,&i,y+j-start,INSERT_VALUES); CHKERRQ(ierr); 103 } 104 } 105 VecRestoreArray(j2,&y); 106 } 107 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 108 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 109 *flag = DIFFERENT_NONZERO_PATTERN; 110 PetscFunctionReturn(0); 111 } 112 113 #undef __FUNC__ 114 #define __FUNC__ "SNESDefaultComputeHessian" 115 /*@C 116 SNESDefaultComputeHessian - Computes the Hessian using finite differences. 117 118 Input Parameters: 119 . x1 - compute Hessian at this point 120 . ctx - application's gradient context, as set with SNESSetGradient() 121 122 Output Parameters: 123 . J - Hessian matrix (not altered in this routine) 124 . B - newly computed Hessian matrix to use with preconditioner (generally the same as J) 125 . flag - flag indicating whether the matrix sparsity structure has changed 126 127 Options Database Key: 128 $ -snes_fd 129 130 Notes: 131 This routine is slow and expensive, and is not currently optimized 132 to take advantage of sparsity in the problem. Although 133 SNESDefaultComputeHessian() is not recommended for general use 134 in large-scale applications, It can be useful in checking the 135 correctness of a user-provided Hessian. 136 137 .keywords: SNES, finite differences, Hessian 138 139 .seealso: SNESSetHessian() 140 @*/ 141 int SNESDefaultComputeHessian(SNES snes,Vec x1,Mat *J,Mat *B,MatStructure *flag,void *ctx) 142 { 143 int ierr; 144 145 PetscFunctionBegin; 146 ierr = SNESDefaultComputeJacobian(snes,x1,J,B,flag,ctx);CHKERRQ(ierr); 147 PetscFunctionReturn(0); 148 } 149