PetscErrorCode petscNonlinearConverged(SNES snes, PetscInt it, PetscReal xnorm, PetscReal snorm, PetscReal fnorm, SNESConvergedReason * reason, void * ctx)
{
FEProblem & problem = *static_cast<FEProblem *>(ctx);
NonlinearSystem & system = problem.getNonlinearSystem();
// Let's be nice and always check PETSc error codes.
PetscErrorCode ierr = 0;
// Temporary variables to store SNES tolerances. Usual C-style would be to declare
// but not initialize these... but it bothers me to leave anything uninitialized.
PetscReal atol = 0.; // absolute convergence tolerance
PetscReal rtol = 0.; // relative convergence tolerance
PetscReal stol = 0.; // convergence (step) tolerance in terms of the norm of the change in the solution between steps
PetscInt maxit = 0; // maximum number of iterations
PetscInt maxf = 0; // maximum number of function evaluations
// Ask the SNES object about its tolerances.
ierr = SNESGetTolerances(snes,
&atol,
&rtol,
&stol,
&maxit,
&maxf);
CHKERRABORT(problem.comm().get(),ierr);
// Get current number of function evaluations done by SNES.
PetscInt nfuncs = 0;
ierr = SNESGetNumberFunctionEvals(snes, &nfuncs);
CHKERRABORT(problem.comm().get(),ierr);
// See if SNESSetFunctionDomainError() has been called. Note:
// SNESSetFunctionDomainError() and SNESGetFunctionDomainError()
// were added in different releases of PETSc.
#if !PETSC_VERSION_LESS_THAN(3,3,0)
PetscBool domainerror;
ierr = SNESGetFunctionDomainError(snes, &domainerror);
CHKERRABORT(problem.comm().get(),ierr);
if (domainerror)
{
*reason = SNES_DIVERGED_FUNCTION_DOMAIN;
return 0;
}
#endif
// Error message that will be set by the FEProblem.
std::string msg;
// xnorm: 2-norm of current iterate
// snorm: 2-norm of current step
// fnorm: 2-norm of function at current iterate
MooseNonlinearConvergenceReason moose_reason = problem.checkNonlinearConvergence(msg,
it,
xnorm,
snorm,
fnorm,
rtol,
stol,
atol,
nfuncs,
maxf,
system._initial_residual_before_preset_bcs,
/*div_threshold=*/(1.0/rtol)*system._initial_residual_before_preset_bcs);
if (msg.length() > 0)
PetscInfo(snes, msg.c_str());
switch (moose_reason)
{
case MOOSE_NONLINEAR_ITERATING:
*reason = SNES_CONVERGED_ITERATING;
break;
case MOOSE_CONVERGED_FNORM_ABS:
*reason = SNES_CONVERGED_FNORM_ABS;
break;
case MOOSE_CONVERGED_FNORM_RELATIVE:
*reason = SNES_CONVERGED_FNORM_RELATIVE;
break;
case MOOSE_CONVERGED_SNORM_RELATIVE:
#if PETSC_VERSION_LESS_THAN(3,3,0)
*reason = SNES_CONVERGED_PNORM_RELATIVE;
#else
*reason = SNES_CONVERGED_SNORM_RELATIVE;
#endif
break;
case MOOSE_DIVERGED_FUNCTION_COUNT:
*reason = SNES_DIVERGED_FUNCTION_COUNT;
break;
case MOOSE_DIVERGED_FNORM_NAN:
*reason = SNES_DIVERGED_FNORM_NAN;
break;
case MOOSE_DIVERGED_LINE_SEARCH:
#if PETSC_VERSION_LESS_THAN(3,2,0)
*reason = SNES_DIVERGED_LS_FAILURE;
#else
*reason = SNES_DIVERGED_LINE_SEARCH;
#endif
break;
}
return 0;
}
int main(int argc,char **argv)
{
SNES snes; /* SNES context */
Vec x,r,F,U; /* vectors */
Mat J; /* Jacobian matrix */
MonitorCtx monP; /* monitoring context */
PetscErrorCode ierr;
PetscInt its,n = 5,i,maxit,maxf;
PetscMPIInt size;
PetscScalar h,xp,v,none = -1.0;
PetscReal abstol,rtol,stol,norm;
PetscInitialize(&argc,&argv,(char*)0,help);
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"This is a uniprocessor example only!");
ierr = PetscOptionsGetInt(NULL,"-n",&n,NULL);CHKERRQ(ierr);
h = 1.0/(n-1);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create nonlinear solver context
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = SNESCreate(PETSC_COMM_WORLD,&snes);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create vector data structures; set function evaluation routine
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
/*
Note that we form 1 vector from scratch and then duplicate as needed.
*/
ierr = VecCreate(PETSC_COMM_WORLD,&x);CHKERRQ(ierr);
ierr = VecSetSizes(x,PETSC_DECIDE,n);CHKERRQ(ierr);
ierr = VecSetFromOptions(x);CHKERRQ(ierr);
ierr = VecDuplicate(x,&r);CHKERRQ(ierr);
ierr = VecDuplicate(x,&F);CHKERRQ(ierr);
ierr = VecDuplicate(x,&U);CHKERRQ(ierr);
/*
Set function evaluation routine and vector
*/
ierr = SNESSetFunction(snes,r,FormFunction,(void*)F);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create matrix data structure; set Jacobian evaluation routine
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = MatCreate(PETSC_COMM_WORLD,&J);CHKERRQ(ierr);
ierr = MatSetSizes(J,PETSC_DECIDE,PETSC_DECIDE,n,n);CHKERRQ(ierr);
ierr = MatSetFromOptions(J);CHKERRQ(ierr);
ierr = MatSeqAIJSetPreallocation(J,3,NULL);CHKERRQ(ierr);
/*
Set Jacobian matrix data structure and default Jacobian evaluation
routine. User can override with:
-snes_fd : default finite differencing approximation of Jacobian
-snes_mf : matrix-free Newton-Krylov method with no preconditioning
(unless user explicitly sets preconditioner)
-snes_mf_operator : form preconditioning matrix as set by the user,
but use matrix-free approx for Jacobian-vector
products within Newton-Krylov method
*/
ierr = SNESSetJacobian(snes,J,J,FormJacobian,NULL);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Customize nonlinear solver; set runtime options
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
/*
Set an optional user-defined monitoring routine
*/
ierr = PetscViewerDrawOpen(PETSC_COMM_WORLD,0,0,0,0,400,400,&monP.viewer);CHKERRQ(ierr);
ierr = SNESMonitorSet(snes,Monitor,&monP,0);CHKERRQ(ierr);
/*
Set names for some vectors to facilitate monitoring (optional)
*/
ierr = PetscObjectSetName((PetscObject)x,"Approximate Solution");CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject)U,"Exact Solution");CHKERRQ(ierr);
/*
Set SNES/KSP/KSP/PC runtime options, e.g.,
-snes_view -snes_monitor -ksp_type <ksp> -pc_type <pc>
*/
ierr = SNESSetFromOptions(snes);CHKERRQ(ierr);
/*
Print parameters used for convergence testing (optional) ... just
to demonstrate this routine; this information is also printed with
the option -snes_view
*/
ierr = SNESGetTolerances(snes,&abstol,&rtol,&stol,&maxit,&maxf);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"atol=%G, rtol=%G, stol=%G, maxit=%D, maxf=%D\n",abstol,rtol,stol,maxit,maxf);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Initialize application:
Store right-hand-side of PDE and exact solution
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
xp = 0.0;
for (i=0; i<n; i++) {
v = 6.0*xp + PetscPowScalar(xp+1.e-12,6.0); /* +1.e-12 is to prevent 0^6 */
ierr = VecSetValues(F,1,&i,&v,INSERT_VALUES);CHKERRQ(ierr);
v = xp*xp*xp;
ierr = VecSetValues(U,1,&i,&v,INSERT_VALUES);CHKERRQ(ierr);
xp += h;
}
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Evaluate initial guess; then solve nonlinear system
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
/*
Note: The user should initialize the vector, x, with the initial guess
for the nonlinear solver prior to calling SNESSolve(). In particular,
to employ an initial guess of zero, the user should explicitly set
this vector to zero by calling VecSet().
*/
ierr = FormInitialGuess(x);CHKERRQ(ierr);
ierr = SNESSolve(snes,NULL,x);CHKERRQ(ierr);
ierr = SNESGetIterationNumber(snes,&its);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"number of SNES iterations = %D\n\n",its);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Check solution and clean up
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
/*
Check the error
*/
ierr = VecAXPY(x,none,U);CHKERRQ(ierr);
ierr = VecNorm(x,NORM_2,&norm);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"Norm of error %G, Iterations %D\n",norm,its);CHKERRQ(ierr);
/*
Free work space. All PETSc objects should be destroyed when they
are no longer needed.
*/
ierr = VecDestroy(&x);CHKERRQ(ierr); ierr = VecDestroy(&r);CHKERRQ(ierr);
ierr = VecDestroy(&U);CHKERRQ(ierr); ierr = VecDestroy(&F);CHKERRQ(ierr);
ierr = MatDestroy(&J);CHKERRQ(ierr); ierr = SNESDestroy(&snes);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&monP.viewer);CHKERRQ(ierr);
ierr = PetscFinalize();
return 0;
}
void PETScNewtonKrylovSolver::initializeSolverState(const SAMRAIVectorReal<NDIM, double>& x,
const SAMRAIVectorReal<NDIM, double>& b)
{
IBTK_TIMER_START(t_initialize_solver_state);
int ierr;
// Rudimentary error checking.
#if !defined(NDEBUG)
if (x.getNumberOfComponents() != b.getNumberOfComponents())
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " vectors must have the same number of components"
<< std::endl);
}
const Pointer<PatchHierarchy<NDIM> >& patch_hierarchy = x.getPatchHierarchy();
if (patch_hierarchy != b.getPatchHierarchy())
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " vectors must have the same hierarchy" << std::endl);
}
const int coarsest_ln = x.getCoarsestLevelNumber();
if (coarsest_ln < 0)
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " coarsest level number must not be negative"
<< std::endl);
}
if (coarsest_ln != b.getCoarsestLevelNumber())
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " vectors must have same coarsest level number"
<< std::endl);
}
const int finest_ln = x.getFinestLevelNumber();
if (finest_ln < coarsest_ln)
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " finest level number must be >= coarsest level number"
<< std::endl);
}
if (finest_ln != b.getFinestLevelNumber())
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " vectors must have same finest level number"
<< std::endl);
}
for (int ln = coarsest_ln; ln <= finest_ln; ++ln)
{
if (!patch_hierarchy->getPatchLevel(ln))
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " hierarchy level " << ln << " does not exist"
<< std::endl);
}
}
#endif
// Deallocate the solver state if the solver is already initialized.
if (d_is_initialized)
{
d_reinitializing_solver = true;
deallocateSolverState();
}
// Create the SNES solver.
if (d_managing_petsc_snes)
{
ierr = SNESCreate(d_petsc_comm, &d_petsc_snes);
IBTK_CHKERRQ(ierr);
resetSNESOptions();
}
else if (!d_petsc_snes)
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " cannot initialize solver state for wrapped PETSc SNES "
"object if the wrapped object is NULL" << std::endl);
}
// Setup solution and rhs vectors.
d_x = x.cloneVector(x.getName());
d_petsc_x = PETScSAMRAIVectorReal::createPETScVector(d_x, d_petsc_comm);
d_b = b.cloneVector(b.getName());
d_petsc_b = PETScSAMRAIVectorReal::createPETScVector(d_b, d_petsc_comm);
d_r = b.cloneVector(b.getName());
d_petsc_r = PETScSAMRAIVectorReal::createPETScVector(d_r, d_petsc_comm);
// Setup the nonlinear operator.
if (d_F) d_F->initializeOperatorState(*d_x, *d_b);
if (d_managing_petsc_snes || d_user_provided_function) resetSNESFunction();
// Setup the Jacobian.
if (d_J) d_J->initializeOperatorState(*d_x, *d_b);
if (d_managing_petsc_snes || d_user_provided_jacobian) resetSNESJacobian();
// Set the SNES options from the PETSc options database.
if (d_options_prefix != "")
{
ierr = SNESSetOptionsPrefix(d_petsc_snes, d_options_prefix.c_str());
IBTK_CHKERRQ(ierr);
}
ierr = SNESSetFromOptions(d_petsc_snes);
IBTK_CHKERRQ(ierr);
// Reset the member state variables to correspond to the values used by the
// SNES object. (Command-line options always take precedence.)
ierr = SNESGetTolerances(d_petsc_snes,
&d_abs_residual_tol,
&d_rel_residual_tol,
&d_solution_tol,
&d_max_iterations,
&d_max_evaluations);
IBTK_CHKERRQ(ierr);
// Setup the KrylovLinearSolver wrapper to correspond to the KSP employed by
// the SNES solver.
KSP petsc_ksp;
ierr = SNESGetKSP(d_petsc_snes, &petsc_ksp);
IBTK_CHKERRQ(ierr);
Pointer<PETScKrylovLinearSolver> p_krylov_solver = d_krylov_solver;
if (p_krylov_solver) p_krylov_solver->resetWrappedKSP(petsc_ksp);
// Setup the Krylov solver.
if (d_krylov_solver) d_krylov_solver->initializeSolverState(*d_x, *d_b);
// Indicate that the solver is initialized.
d_reinitializing_solver = false;
d_is_initialized = true;
IBTK_TIMER_STOP(t_initialize_solver_state);
return;
} // initializeSolverState
/*
Applies some sweeps on nonlinear Gauss-Seidel on each process
*/
PetscErrorCode NonlinearGS(SNES snes,Vec X)
{
PetscInt i,j,Mx,My,xs,ys,xm,ym,its,l;
PetscErrorCode ierr;
PetscReal hx,hy,hxdhy,hydhx;
PetscScalar **x,F,J,u,uxx,uyy;
DM da;
Vec localX;
PetscFunctionBeginUser;
ierr = SNESGetTolerances(snes,PETSC_NULL,PETSC_NULL,PETSC_NULL,&its,PETSC_NULL);CHKERRQ(ierr);
ierr = SNESShellGetContext(snes,(void**)&da);CHKERRQ(ierr);
ierr = DMDAGetInfo(da,PETSC_IGNORE,&Mx,&My,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,
PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE);
hx = 1.0/(PetscReal)(Mx-1);
hy = 1.0/(PetscReal)(My-1);
hxdhy = hx/hy;
hydhx = hy/hx;
ierr = DMGetLocalVector(da,&localX);CHKERRQ(ierr);
for (l=0; l<its; l++) {
ierr = DMGlobalToLocalBegin(da,X,INSERT_VALUES,localX);CHKERRQ(ierr);
ierr = DMGlobalToLocalEnd(da,X,INSERT_VALUES,localX);CHKERRQ(ierr);
/*
Get a pointer to vector data.
- For default PETSc vectors, VecGetArray() returns a pointer to
the data array. Otherwise, the routine is implementation dependent.
- You MUST call VecRestoreArray() when you no longer need access to
the array.
*/
ierr = DMDAVecGetArray(da,localX,&x);CHKERRQ(ierr);
/*
Get local grid boundaries (for 2-dimensional DMDA):
xs, ys - starting grid indices (no ghost points)
xm, ym - widths of local grid (no ghost points)
*/
ierr = DMDAGetCorners(da,&xs,&ys,PETSC_NULL,&xm,&ym,PETSC_NULL);CHKERRQ(ierr);
for (j=ys; j<ys+ym; j++) {
for (i=xs; i<xs+xm; i++) {
if (i == 0 || j == 0 || i == Mx-1 || j == My-1) {
/* boundary conditions are all zero Dirichlet */
x[j][i] = 0.0;
} else {
u = x[j][i];
uxx = (2.0*u - x[j][i-1] - x[j][i+1])*hydhx;
uyy = (2.0*u - x[j-1][i] - x[j+1][i])*hxdhy;
F = uxx + uyy;
J = 2.0*(hydhx + hxdhy);
u = u - F/J;
x[j][i] = u;
}
}
}
/*
Restore vector
*/
ierr = DMDAVecRestoreArray(da,localX,&x);CHKERRQ(ierr);
ierr = DMLocalToGlobalBegin(da,localX,INSERT_VALUES,X);CHKERRQ(ierr);
ierr = DMLocalToGlobalEnd(da,localX,INSERT_VALUES,X);CHKERRQ(ierr);
}
ierr = DMRestoreLocalVector(da,&localX);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode SNESLineSearchApply_BT(SNESLineSearch linesearch)
{
PetscBool changed_y,changed_w;
PetscErrorCode ierr;
Vec X,F,Y,W,G;
SNES snes;
PetscReal fnorm, xnorm, ynorm, gnorm;
PetscReal lambda,lambdatemp,lambdaprev,minlambda,maxstep,initslope,alpha,stol;
PetscReal t1,t2,a,b,d;
PetscReal f;
PetscReal g,gprev;
PetscBool domainerror;
PetscViewer monitor;
PetscInt max_its,count;
SNESLineSearch_BT *bt;
Mat jac;
PetscErrorCode (*objective)(SNES,Vec,PetscReal*,void*);
PetscFunctionBegin;
ierr = SNESLineSearchGetVecs(linesearch, &X, &F, &Y, &W, &G);CHKERRQ(ierr);
ierr = SNESLineSearchGetNorms(linesearch, &xnorm, &fnorm, &ynorm);CHKERRQ(ierr);
ierr = SNESLineSearchGetLambda(linesearch, &lambda);CHKERRQ(ierr);
ierr = SNESLineSearchGetSNES(linesearch, &snes);CHKERRQ(ierr);
ierr = SNESLineSearchGetMonitor(linesearch, &monitor);CHKERRQ(ierr);
ierr = SNESLineSearchGetTolerances(linesearch,&minlambda,&maxstep,NULL,NULL,NULL,&max_its);CHKERRQ(ierr);
ierr = SNESGetTolerances(snes,NULL,NULL,&stol,NULL,NULL);CHKERRQ(ierr);
ierr = SNESGetObjective(snes,&objective,NULL);CHKERRQ(ierr);
bt = (SNESLineSearch_BT*)linesearch->data;
alpha = bt->alpha;
ierr = SNESGetJacobian(snes, &jac, NULL, NULL, NULL);CHKERRQ(ierr);
if (!jac && !objective) SETERRQ(PetscObjectComm((PetscObject)linesearch), PETSC_ERR_USER, "SNESLineSearchBT requires a Jacobian matrix");
/* precheck */
ierr = SNESLineSearchPreCheck(linesearch,X,Y,&changed_y);CHKERRQ(ierr);
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_TRUE);CHKERRQ(ierr);
ierr = VecNormBegin(Y, NORM_2, &ynorm);CHKERRQ(ierr);
ierr = VecNormBegin(X, NORM_2, &xnorm);CHKERRQ(ierr);
ierr = VecNormEnd(Y, NORM_2, &ynorm);CHKERRQ(ierr);
ierr = VecNormEnd(X, NORM_2, &xnorm);CHKERRQ(ierr);
if (ynorm == 0.0) {
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: Initial direction and size is 0\n");CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
ierr = VecCopy(X,W);CHKERRQ(ierr);
ierr = VecCopy(F,G);CHKERRQ(ierr);
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (ynorm > maxstep) { /* Step too big, so scale back */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: Scaling step by %14.12e old ynorm %14.12e\n", (double)(maxstep/ynorm),(double)ynorm);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
ierr = VecScale(Y,maxstep/(ynorm));CHKERRQ(ierr);
ynorm = maxstep;
}
/* if the SNES has an objective set, use that instead of the function value */
if (objective) {
ierr = SNESComputeObjective(snes,X,&f);CHKERRQ(ierr);
} else {
f = fnorm*fnorm;
}
/* compute the initial slope */
if (objective) {
/* slope comes from the function (assumed to be the gradient of the objective */
ierr = VecDotRealPart(Y,F,&initslope);CHKERRQ(ierr);
} else {
/* slope comes from the normal equations */
ierr = MatMult(jac,Y,W);CHKERRQ(ierr);
ierr = VecDotRealPart(F,W,&initslope);CHKERRQ(ierr);
if (initslope > 0.0) initslope = -initslope;
if (initslope == 0.0) initslope = -1.0;
}
ierr = VecWAXPY(W,-lambda,Y,X);CHKERRQ(ierr);
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes, W);CHKERRQ(ierr);
}
if (snes->nfuncs >= snes->max_funcs) {
ierr = PetscInfo(snes,"Exceeded maximum function evaluations, while checking full step length!\n");CHKERRQ(ierr);
snes->reason = SNES_DIVERGED_FUNCTION_COUNT;
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (objective) {
ierr = SNESComputeObjective(snes,W,&g);CHKERRQ(ierr);
} else {
ierr = (*linesearch->ops->snesfunc)(snes,W,G);CHKERRQ(ierr);
ierr = SNESGetFunctionDomainError(snes, &domainerror);CHKERRQ(ierr);
if (domainerror) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (linesearch->ops->vinorm) {
gnorm = fnorm;
ierr = (*linesearch->ops->vinorm)(snes, G, W, &gnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(G,NORM_2,&gnorm);CHKERRQ(ierr);
}
g = PetscSqr(gnorm);
}
if (PetscIsInfOrNanReal(g)) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo(monitor,"Aborted due to Nan or Inf in function evaluation\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (!objective) {
ierr = PetscInfo2(snes,"Initial fnorm %14.12e gnorm %14.12e\n", (double)fnorm, (double)gnorm);CHKERRQ(ierr);
}
if (.5*g <= .5*f + lambda*alpha*initslope) { /* Sufficient reduction or step tolerance convergence */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
if (!objective) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Using full step: fnorm %14.12e gnorm %14.12e\n", (double)fnorm, (double)gnorm);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Using full step: obj0 %14.12e obj %14.12e\n", (double)f, (double)g);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
} else {
/* Since the full step didn't work and the step is tiny, quit */
if (stol*xnorm > ynorm) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo2(monitor,"Aborted due to ynorm < stol*xnorm (%14.12e < %14.12e) and inadequate full step.\n",ynorm,stol*xnorm);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/* Fit points with quadratic */
lambdatemp = -initslope/(g - f - 2.0*lambda*initslope);
lambdaprev = lambda;
gprev = g;
if (lambdatemp > .5*lambda) lambdatemp = .5*lambda;
if (lambdatemp <= .1*lambda) lambda = .1*lambda;
else lambda = lambdatemp;
ierr = VecWAXPY(W,-lambda,Y,X);CHKERRQ(ierr);
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes, W);CHKERRQ(ierr);
}
if (snes->nfuncs >= snes->max_funcs) {
ierr = PetscInfo1(snes,"Exceeded maximum function evaluations, while attempting quadratic backtracking! %D \n",snes->nfuncs);CHKERRQ(ierr);
snes->reason = SNES_DIVERGED_FUNCTION_COUNT;
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (objective) {
ierr = SNESComputeObjective(snes,W,&g);CHKERRQ(ierr);
} else {
ierr = (*linesearch->ops->snesfunc)(snes,W,G);CHKERRQ(ierr);
ierr = SNESGetFunctionDomainError(snes, &domainerror);CHKERRQ(ierr);
if (domainerror) PetscFunctionReturn(0);
if (linesearch->ops->vinorm) {
gnorm = fnorm;
ierr = (*linesearch->ops->vinorm)(snes, G, W, &gnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(G,NORM_2,&gnorm);CHKERRQ(ierr);
g = gnorm*gnorm;
}
}
if (PetscIsInfOrNanReal(g)) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo(monitor,"Aborted due to Nan or Inf in function evaluation\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
if (!objective) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: gnorm after quadratic fit %14.12e\n",(double)gnorm);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: obj after quadratic fit %14.12e\n",(double)g);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
if (.5*g < .5*f + lambda*alpha*initslope) { /* sufficient reduction */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratically determined step, lambda=%18.16e\n",(double)lambda);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
} else {
/* Fit points with cubic */
for (count = 0; count < max_its; count++) {
if (lambda <= minlambda) {
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: unable to find good step length! After %D tries \n",count);CHKERRQ(ierr);
if (!objective) {
ierr = PetscViewerASCIIPrintf(monitor,
" Line search: fnorm=%18.16e, gnorm=%18.16e, ynorm=%18.16e, minlambda=%18.16e, lambda=%18.16e, initial slope=%18.16e\n",
(double)fnorm, (double)gnorm, (double)ynorm, (double)minlambda, (double)lambda, (double)initslope);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor,
" Line search: obj(0)=%18.16e, obj=%18.16e, ynorm=%18.16e, minlambda=%18.16e, lambda=%18.16e, initial slope=%18.16e\n",
(double)f, (double)g, (double)ynorm, (double)minlambda, (double)lambda, (double)initslope);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
t1 = .5*(g - f) - lambda*initslope;
t2 = .5*(gprev - f) - lambdaprev*initslope;
a = (t1/(lambda*lambda) - t2/(lambdaprev*lambdaprev))/(lambda-lambdaprev);
b = (-lambdaprev*t1/(lambda*lambda) + lambda*t2/(lambdaprev*lambdaprev))/(lambda-lambdaprev);
d = b*b - 3*a*initslope;
if (d < 0.0) d = 0.0;
if (a == 0.0) lambdatemp = -initslope/(2.0*b);
else lambdatemp = (-b + PetscSqrtReal(d))/(3.0*a);
} else if (linesearch->order == SNES_LINESEARCH_ORDER_QUADRATIC) {
lambdatemp = -initslope/(g - f - 2.0*initslope);
} else SETERRQ(PetscObjectComm((PetscObject)linesearch), PETSC_ERR_SUP, "unsupported line search order for type bt");
lambdaprev = lambda;
gprev = g;
if (lambdatemp > .5*lambda) lambdatemp = .5*lambda;
if (lambdatemp <= .1*lambda) lambda = .1*lambda;
else lambda = lambdatemp;
ierr = VecWAXPY(W,-lambda,Y,X);CHKERRQ(ierr);
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes,W);CHKERRQ(ierr);
}
if (snes->nfuncs >= snes->max_funcs) {
ierr = PetscInfo1(snes,"Exceeded maximum function evaluations, while looking for good step length! %D \n",count);CHKERRQ(ierr);
if (!objective) {
ierr = PetscInfo5(snes,"fnorm=%18.16e, gnorm=%18.16e, ynorm=%18.16e, lambda=%18.16e, initial slope=%18.16e\n",
(double)fnorm,(double)gnorm,(double)ynorm,(double)lambda,(double)initslope);CHKERRQ(ierr);
}
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
snes->reason = SNES_DIVERGED_FUNCTION_COUNT;
PetscFunctionReturn(0);
}
if (objective) {
ierr = SNESComputeObjective(snes,W,&g);CHKERRQ(ierr);
} else {
ierr = (*linesearch->ops->snesfunc)(snes,W,G);CHKERRQ(ierr);
ierr = SNESGetFunctionDomainError(snes, &domainerror);CHKERRQ(ierr);
if (domainerror) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (linesearch->ops->vinorm) {
gnorm = fnorm;
ierr = (*linesearch->ops->vinorm)(snes, G, W, &gnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(G,NORM_2,&gnorm);CHKERRQ(ierr);
g = gnorm*gnorm;
}
}
if (PetscIsInfOrNanReal(gnorm)) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo(monitor,"Aborted due to Nan or Inf in function evaluation\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (.5*g < .5*f + lambda*alpha*initslope) { /* is reduction enough? */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
if (!objective) {
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Cubically determined step, current gnorm %14.12e lambda=%18.16e\n",(double)gnorm,(double)lambda);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratically determined step, current gnorm %14.12e lambda=%18.16e\n",(double)gnorm,(double)lambda);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
} else {
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Cubically determined step, obj %14.12e lambda=%18.16e\n",(double)g,(double)lambda);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratically determined step, obj %14.12e lambda=%18.16e\n",(double)g,(double)lambda);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
}
break;
} else if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
if (!objective) {
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Cubic step no good, shrinking lambda, current gnorm %12.12e lambda=%18.16e\n",(double)gnorm,(double)lambda);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratic step no good, shrinking lambda, current gnorm %12.12e lambda=%18.16e\n",(double)gnorm,(double)lambda);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
} else {
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Cubic step no good, shrinking lambda, obj %12.12e lambda=%18.16e\n",(double)g,(double)lambda);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratic step no good, shrinking lambda, obj %12.12e lambda=%18.16e\n",(double)g,(double)lambda);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
}
}
}
}
/* postcheck */
ierr = SNESLineSearchPostCheck(linesearch,X,Y,W,&changed_y,&changed_w);CHKERRQ(ierr);
if (changed_y) {
ierr = VecWAXPY(W,-lambda,Y,X);CHKERRQ(ierr);
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes, W);CHKERRQ(ierr);
}
}
if (changed_y || changed_w || objective) { /* recompute the function norm if the step has changed or the objective isn't the norm */
ierr = (*linesearch->ops->snesfunc)(snes,W,G);CHKERRQ(ierr);
ierr = SNESGetFunctionDomainError(snes, &domainerror);CHKERRQ(ierr);
if (domainerror) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (linesearch->ops->vinorm) {
gnorm = fnorm;
ierr = (*linesearch->ops->vinorm)(snes, G, W, &gnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(G,NORM_2,&gnorm);CHKERRQ(ierr);
}
ierr = VecNorm(Y,NORM_2,&ynorm);CHKERRQ(ierr);
if (PetscIsInfOrNanReal(gnorm)) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo(monitor,"Aborted due to Nan or Inf in function evaluation\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
}
/* copy the solution over */
ierr = VecCopy(W, X);CHKERRQ(ierr);
ierr = VecCopy(G, F);CHKERRQ(ierr);
ierr = VecNorm(X, NORM_2, &xnorm);CHKERRQ(ierr);
ierr = SNESLineSearchSetLambda(linesearch, lambda);CHKERRQ(ierr);
ierr = SNESLineSearchSetNorms(linesearch, xnorm, gnorm, ynorm);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode SNESLineSearchApply_NLEQERR(SNESLineSearch linesearch)
{
PetscBool changed_y,changed_w;
PetscErrorCode ierr;
Vec X,F,Y,W,G;
SNES snes;
PetscReal fnorm, xnorm, ynorm, gnorm, wnorm;
PetscReal lambda, minlambda, stol;
PetscViewer monitor;
PetscInt max_its, count, snes_iteration;
PetscReal theta, mudash, lambdadash;
SNESLineSearch_NLEQERR *nleqerr = (SNESLineSearch_NLEQERR*)linesearch->data;
KSPConvergedReason kspreason;
PetscFunctionBegin;
ierr = PetscCitationsRegister(NLEQERR_citation, &NLEQERR_cited);CHKERRQ(ierr);
ierr = SNESLineSearchGetVecs(linesearch, &X, &F, &Y, &W, &G);CHKERRQ(ierr);
ierr = SNESLineSearchGetNorms(linesearch, &xnorm, &fnorm, &ynorm);CHKERRQ(ierr);
ierr = SNESLineSearchGetLambda(linesearch, &lambda);CHKERRQ(ierr);
ierr = SNESLineSearchGetSNES(linesearch, &snes);CHKERRQ(ierr);
ierr = SNESLineSearchGetDefaultMonitor(linesearch, &monitor);CHKERRQ(ierr);
ierr = SNESLineSearchGetTolerances(linesearch,&minlambda,NULL,NULL,NULL,NULL,&max_its);CHKERRQ(ierr);
ierr = SNESGetTolerances(snes,NULL,NULL,&stol,NULL,NULL);CHKERRQ(ierr);
/* reset the state of the Lipschitz estimates */
ierr = SNESGetIterationNumber(snes, &snes_iteration);CHKERRQ(ierr);
if (!snes_iteration) {
ierr = SNESLineSearchReset_NLEQERR(linesearch);CHKERRQ(ierr);
}
/* precheck */
ierr = SNESLineSearchPreCheck(linesearch,X,Y,&changed_y);CHKERRQ(ierr);
ierr = SNESLineSearchSetReason(linesearch, SNES_LINESEARCH_SUCCEEDED);CHKERRQ(ierr);
ierr = VecNormBegin(Y, NORM_2, &ynorm);CHKERRQ(ierr);
ierr = VecNormBegin(X, NORM_2, &xnorm);CHKERRQ(ierr);
ierr = VecNormEnd(Y, NORM_2, &ynorm);CHKERRQ(ierr);
ierr = VecNormEnd(X, NORM_2, &xnorm);CHKERRQ(ierr);
/* Note: Y is *minus* the Newton step. For whatever reason PETSc doesn't solve with the minus on the RHS. */
if (ynorm == 0.0) {
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: Initial direction and size is 0\n");CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
ierr = VecCopy(X,W);CHKERRQ(ierr);
ierr = VecCopy(F,G);CHKERRQ(ierr);
ierr = SNESLineSearchSetNorms(linesearch,xnorm,fnorm,ynorm);CHKERRQ(ierr);
ierr = SNESLineSearchSetReason(linesearch, SNES_LINESEARCH_FAILED_REDUCT);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/* At this point, we've solved the Newton system for delta_x, and we assume that
its norm is greater than the solution tolerance (otherwise we wouldn't be in
here). So let's go ahead and estimate the Lipschitz constant.
W contains bar_delta_x_prev at this point. */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: norm of Newton step: %14.12e\n", (double) ynorm);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
/* this needs information from a previous iteration, so can't do it on the first one */
if (nleqerr->norm_delta_x_prev > 0 && nleqerr->norm_bar_delta_x_prev > 0) {
ierr = VecWAXPY(G, +1.0, Y, W);CHKERRQ(ierr); /* bar_delta_x - delta_x; +1 because Y is -delta_x */
ierr = VecNormBegin(G, NORM_2, &gnorm);CHKERRQ(ierr);
ierr = VecNormEnd(G, NORM_2, &gnorm);CHKERRQ(ierr);
nleqerr->mu_curr = nleqerr->lambda_prev * (nleqerr->norm_delta_x_prev * nleqerr->norm_bar_delta_x_prev) / (gnorm * ynorm);
lambda = PetscMin(1.0, nleqerr->mu_curr);
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: Lipschitz estimate: %14.12e; lambda: %14.12e\n", (double) nleqerr->mu_curr, (double) lambda);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
} else {
lambda = linesearch->damping;
}
/* The main while loop of the algorithm.
At the end of this while loop, G should have the accepted new X in it. */
count = 0;
while (PETSC_TRUE) {
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: entering iteration with lambda: %14.12e\n", lambda);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
/* Check that we haven't performed too many iterations */
count += 1;
if (count >= max_its) {
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: maximum iterations reached\n");CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
ierr = SNESLineSearchSetReason(linesearch, SNES_LINESEARCH_FAILED_REDUCT);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/* Now comes the Regularity Test. */
if (lambda <= minlambda) {
/* This isn't what is suggested by Deuflhard, but it works better in my experience */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: lambda has reached lambdamin, taking full Newton step\n");CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
lambda = 1.0;
ierr = VecWAXPY(G, -lambda, Y, X);CHKERRQ(ierr);
/* and clean up the state for next time */
ierr = SNESLineSearchReset_NLEQERR(linesearch);CHKERRQ(ierr);
/*
The clang static analyzer detected a problem here; once the loop is broken the values
nleqerr->norm_delta_x_prev = ynorm;
nleqerr->norm_bar_delta_x_prev = wnorm;
are set, but wnorm has not even been computed.
I don't know if this is the correct fix but by setting ynorm and wnorm to -1.0 at
least the linesearch object is kept in the state set by the SNESLineSearchReset_NLEQERR() call above
*/
ynorm = wnorm = -1.0;
break;
}
/* Compute new trial iterate */
ierr = VecWAXPY(W, -lambda, Y, X);CHKERRQ(ierr);
ierr = SNESComputeFunction(snes, W, G);CHKERRQ(ierr);
/* Solve linear system for bar_delta_x_curr: old Jacobian, new RHS. Note absence of minus sign, compared to Deuflhard, in keeping with PETSc convention */
ierr = KSPSolve(snes->ksp, G, W);CHKERRQ(ierr);
ierr = KSPGetConvergedReason(snes->ksp, &kspreason);CHKERRQ(ierr);
if (kspreason < 0) {
ierr = PetscInfo(snes,"Solution for \\bar{delta x}^{k+1} failed.");CHKERRQ(ierr);
}
/* W now contains -bar_delta_x_curr. */
ierr = VecNorm(W, NORM_2, &wnorm);CHKERRQ(ierr);
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: norm of simplified Newton update: %14.12e\n", (double) wnorm);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
/* compute the monitoring quantities theta and mudash. */
theta = wnorm / ynorm;
ierr = VecWAXPY(G, -(1.0 - lambda), Y, W);CHKERRQ(ierr);
ierr = VecNorm(G, NORM_2, &gnorm);CHKERRQ(ierr);
mudash = (0.5 * ynorm * lambda * lambda) / gnorm;
/* Check for termination of the linesearch */
if (theta >= 1.0) {
/* need to go around again with smaller lambda */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: monotonicity check failed, ratio: %14.12e\n", (double) theta);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
lambda = PetscMin(mudash, 0.5 * lambda);
lambda = PetscMax(lambda, minlambda);
/* continue through the loop, i.e. go back to regularity test */
} else {
/* linesearch terminated */
lambdadash = PetscMin(1.0, mudash);
if (lambdadash == 1.0 && lambda == 1.0 && wnorm <= stol) {
/* store the updated state, X - Y - W, in G:
I need to keep W for the next linesearch */
ierr = VecCopy(X, G);CHKERRQ(ierr);
ierr = VecAXPY(G, -1.0, Y);CHKERRQ(ierr);
ierr = VecAXPY(G, -1.0, W);CHKERRQ(ierr);
break;
}
/* Deuflhard suggests to add the following:
else if (lambdadash >= 4.0 * lambda) {
lambda = lambdadash;
}
to continue through the loop, i.e. go back to regularity test.
I deliberately exclude this, as I have practical experience of this
getting stuck in infinite loops (on e.g. an Allen--Cahn problem). */
else {
/* accept iterate without adding on, i.e. don't use bar_delta_x;
again, I need to keep W for the next linesearch */
ierr = VecWAXPY(G, -lambda, Y, X);CHKERRQ(ierr);
break;
}
}
}
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes, G);CHKERRQ(ierr);
}
/* W currently contains -bar_delta_u. Scale it so that it contains bar_delta_u. */
ierr = VecScale(W, -1.0);CHKERRQ(ierr);
/* postcheck */
ierr = SNESLineSearchPostCheck(linesearch,X,Y,G,&changed_y,&changed_w);CHKERRQ(ierr);
if (changed_y || changed_w) {
ierr = SNESLineSearchSetReason(linesearch, SNES_LINESEARCH_FAILED_USER);CHKERRQ(ierr);
ierr = PetscInfo(snes,"Changing the search direction here doesn't make sense.\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/* copy the solution and information from this iteration over */
nleqerr->norm_delta_x_prev = ynorm;
nleqerr->norm_bar_delta_x_prev = wnorm;
nleqerr->lambda_prev = lambda;
ierr = VecCopy(G, X);CHKERRQ(ierr);
ierr = SNESComputeFunction(snes, X, F);CHKERRQ(ierr);
ierr = VecNorm(X, NORM_2, &xnorm);CHKERRQ(ierr);
ierr = VecNorm(F, NORM_2, &fnorm);CHKERRQ(ierr);
ierr = SNESLineSearchSetLambda(linesearch, lambda);CHKERRQ(ierr);
ierr = SNESLineSearchSetNorms(linesearch, xnorm, fnorm, (ynorm < 0 ? PETSC_INFINITY : ynorm));CHKERRQ(ierr);
PetscFunctionReturn(0);
}
