NonlinearSystem::NonlinearSystem(FEProblemBase & fe_problem, const std::string & name)
: NonlinearSystemBase(
fe_problem, fe_problem.es().add_system<TransientNonlinearImplicitSystem>(name), name),
_transient_sys(fe_problem.es().get_system<TransientNonlinearImplicitSystem>(name)),
_nl_residual_functor(_fe_problem),
_fd_residual_functor(_fe_problem),
_use_coloring_finite_difference(false)
{
nonlinearSolver()->residual_object = &_nl_residual_functor;
nonlinearSolver()->jacobian = Moose::compute_jacobian;
nonlinearSolver()->bounds = Moose::compute_bounds;
nonlinearSolver()->nullspace = Moose::compute_nullspace;
nonlinearSolver()->transpose_nullspace = Moose::compute_transpose_nullspace;
nonlinearSolver()->nearnullspace = Moose::compute_nearnullspace;
#ifdef LIBMESH_HAVE_PETSC
PetscNonlinearSolver<Real> * petsc_solver =
static_cast<PetscNonlinearSolver<Real> *>(_transient_sys.nonlinear_solver.get());
if (petsc_solver)
{
petsc_solver->set_residual_zero_out(false);
petsc_solver->set_jacobian_zero_out(false);
petsc_solver->use_default_monitor(false);
}
#endif
}
void
RobotSetup::addNWays()
{
int do_quick;
options()->GetEnumValue("do_a_quick_one", do_quick, prefix());
int depth_frac;
options()->GetIntegerValue("branch_on_frac_only", depth_frac, prefix());
// pass user set Sos constraints (code inspired from CoinSolve.cpp)
const TMINLP::SosInfo * sos = nonlinearSolver()->model()->sosConstraints();
if (!getIntParameter(BabSetupBase::DisableSos) && sos && sos->num > 0) //we have some sos constraints
{
const int & numSos = sos->num;
OsiObject ** objects = new OsiObject*[numSos];
const int * starts = sos->starts;
const int * indices = sos->indices;
//const char * types = sos->types;
const double * weights = sos->weights;
bool hasPriorities = false;
const int * varPriorities = nonlinearSolver()->getPriorities();
int numberObjects = nonlinearSolver()->numberObjects();
if (varPriorities)
{
for (int i = 0 ; i < numberObjects ; i++) {
if (varPriorities[i]) {
hasPriorities = true;
break;
}
}
}
const int * sosPriorities = sos->priorities;
if (sosPriorities)
{
for (int i = 0 ; i < numSos ; i++) {
if (sosPriorities[i]) {
hasPriorities = true;
break;
}
}
}
std::vector<std::list<int> > groups(numSos + 1);
for (int i = 0 ; i < numSos ; i++)
{
int start = starts[i];
int length = starts[i + 1] - start;
for(int j = 0 ; j < length ; j++){
groups[(size_t) weights[j]].push_back(indices[start+j]);
}
}
for (int i = 0 ; i < numSos ; i++)
{
int start = starts[i];
int length = starts[i + 1] - start;
BonNWayObject * nway = new BonNWayObject(length, &indices[start],i);
nway->setPriority(1);
for(int j = 0 ; j < length ; j++){//Setup consequences
n_way_consequences cons;
std::vector<int>& ids = cons.indices;
int idx = (int) weights[j];
const std::list<int> &to_add = groups[idx];
for(std::list<int>::const_iterator k = to_add.begin() ;
k != to_add.end() ; k++){
if(*k != indices[start+j]) ids.push_back(*k);
}
nway->setConsequence(j, cons);
}
objects[i] = nway;
if(do_quick)
nway->make_quick();
nway->set_only_frac_branches(depth_frac);
if (hasPriorities && sosPriorities && sosPriorities[i]) {
objects[i]->setPriority(sosPriorities[i]);
}
}
nonlinearSolver()->addObjects(numSos, objects);
for (int i = 0 ; i < numSos ; i++)
delete objects[i];
delete [] objects;
}
}
