bool Solver::solveStep()
{
if ( _field->isSolved() ) {
emit solvingDone(true);
return true;
}
d->rules->solve();
#ifdef DEBUG
PRINT_ELAPSED("fast rules")
#endif
if( _field->isSolved() ) {
emit solvingDone(true);
return true;
}
CoordSet surePoints;
AdviseFull::ProbabilityMap probabilities;
AdviseFull::adviseFull(d->facts, &surePoints, &probabilities);
#ifdef DEBUG
PRINT_ELAPSED("full rules")
#endif
if(!surePoints.empty()) {
CoordSet::iterator i;
for(i=surePoints.begin(); i!=surePoints.end(); ++i) {
bool b = d->rules->reveal(*i);
assert(b);
}
} else if ( !_noGuess ) {
#ifdef DEBUG
cout << "Applying heuristics!" << endl;
cout << *_field << endl;
#endif
// Minimum probability logic
assert(!probabilities.empty());
#ifdef DEBUG
AdviseFull::ProbabilityMap::iterator i=probabilities.begin();
cout << "Probability is " << i->first << endl;
#endif
bool success = d->rules->reveal(probabilities.begin()->second);
if ( !success ) {
emit solvingDone(false);
return false;
}
}
if (_inOneStep) return solveStep();
else QTimer::singleShot(0, this, SLOT(solveStep()));
return false;
}
void
Transient::takeStep(Real input_dt)
{
_picard_it = 0;
_problem.backupMultiApps(EXEC_TIMESTEP_BEGIN);
_problem.backupMultiApps(EXEC_TIMESTEP_END);
while (_picard_it<_picard_max_its && _picard_converged == false)
{
if (_picard_max_its > 1)
{
_console << "\nBeginning Picard Iteration " << _picard_it << "\n" << std::endl;
if (_picard_it == 0) // First Picard iteration - need to save off the initial nonlinear residual
{
_picard_initial_norm = _problem.computeResidualL2Norm();
_console << "Initial Picard Norm: " << _picard_initial_norm << '\n';
}
}
// For every iteration other than the first, we need to restore the state of the MultiApps
if (_picard_it > 0)
{
_problem.restoreMultiApps(EXEC_TIMESTEP_BEGIN);
_problem.restoreMultiApps(EXEC_TIMESTEP_END);
}
solveStep(input_dt);
// If the last solve didn't converge then we need to exit this step completely (even in the case of Picard)
// So we can retry...
if (!lastSolveConverged())
return;
if (_picard_max_its > 1)
{
_picard_timestep_end_norm = _problem.computeResidualL2Norm();
_console << "Picard Norm after TIMESTEP_END MultiApps: " << _picard_timestep_end_norm << '\n';
Real max_norm = std::max(_picard_timestep_begin_norm, _picard_timestep_end_norm);
Real max_relative_drop = max_norm / _picard_initial_norm;
if (max_norm < _picard_abs_tol || max_relative_drop < _picard_rel_tol)
{
_console << "Picard converged!" << std::endl;
_picard_converged = true;
return;
}
}
++_picard_it;
}
}
bool Solver::initSolve(bool oneStep, bool noGuess)
{
_inOneStep = oneStep;
_noGuess = noGuess;
delete d->facts;
d->facts = new AdviseFast::FactSet(_field);
delete d->rules;
d->rules = new AdviseFast::RuleSet(d->facts);
#ifdef DEBUG
d->t0 = time(0);
#endif
return solveStep();
}
void
Transient::takeStep(Real input_dt)
{
_picard_it = 0;
while (_picard_it<_picard_max_its && _picard_converged == false)
{
if (_picard_max_its > 1)
_console << "Beginning Picard Iteration " << _picard_it << "\n" << std::endl;
solveStep(input_dt);
++_picard_it;
}
}
// Try to over-ride reseting the sub-apps
void
AutoRBTransient::takeStep(Real input_dt)
{
_picard_it = 0;
_problem.backupMultiApps(EXEC_TIMESTEP_BEGIN);
_problem.backupMultiApps(EXEC_TIMESTEP_END);
//his_initial_norm_old = getPostprocessorValue("InitialResidual");
// _console << "Update his_old_initial \n" << std::endl;
while (_picard_it<_picard_max_its && _picard_converged == false)
{
if (_picard_max_its > 1)
{
_console << "\nBeginning Picard Iteration " << _picard_it << "\n" << std::endl;
Real _current_norm = _problem.computeResidualL2Norm();
if (_picard_it == 0) // First Picard iteration - need to save off the initial nonlinear residual
{
_picard_initial_norm = _current_norm;
_console << "Initial Picard Norm: " << _picard_initial_norm << '\n';
}
}
// For every iteration other than the first, we need to restore the state of the MultiApps
if (_picard_it > 0)
{
// This is supposed to regain the previous behavior
//_problem.restoreMultiApps(EXEC_TIMESTEP_BEGIN);
//_problem.restoreMultiApps(EXEC_TIMESTEP_END);
}
solveStep(input_dt);
/*
// Remove this check, we check at the beginning of solveStep.
// We could reformulate this check like the other, but I don't think we gain anything.
if (_picard_max_its > 1)
{
_picard_timestep_end_norm = _problem.computeResidualL2Norm();
_console << "Picard Norm after TIMESTEP_END MultiApps: " << _picard_timestep_end_norm << '\n';
Real max_norm = std::max(_picard_timestep_begin_norm, _picard_timestep_end_norm);
Real max_relative_drop = max_norm / _picard_initial_norm;
if (max_norm < _picard_abs_tol || max_relative_drop < _picard_rel_tol)
{
_console << "Picard converged!" << std::endl;
_picard_converged = true;
return;
}
}
*/
++_picard_it;
}
}
