int RestrictedMultiVectorWrapper::restrict_comm(Teuchos::RCP<Epetra_MultiVector> input_mv){
input_mv_=input_mv;
/* Pull the Input Matrix Info */
const Epetra_MpiComm *InComm = dynamic_cast<const Epetra_MpiComm*>(& input_mv_->Comm());
const Epetra_BlockMap *InMap = dynamic_cast<const Epetra_BlockMap*>(& input_mv_->Map());
if(!InComm || !InMap) return -1;
if(!subcomm_is_set){
/* Build the Split Communicators, If Needed */
int color;
if(InMap->NumMyElements()) color=1;
else color=MPI_UNDEFINED;
MPI_Comm_split(InComm->Comm(),color,InComm->MyPID(),&MPI_SubComm_);
}
else{
/* Sanity check user-provided subcomm - drop an error if the MPISubComm
does not include a processor with data. */
if (input_mv->MyLength() && MPI_SubComm_ == MPI_COMM_NULL)
return(-2);
}
/* Mark active processors */
if(MPI_SubComm_ == MPI_COMM_NULL) proc_is_active=false;
else proc_is_active=true;
int Nrows=InMap->NumGlobalElements();
if(proc_is_active){
RestrictedComm_=new Epetra_MpiComm(MPI_SubComm_);
/* Build the Restricted Maps */
ResMap_ = new Epetra_BlockMap(Nrows,InMap->NumMyElements(),InMap->MyGlobalElements(),
InMap->ElementSizeList(),InMap->IndexBase(),*RestrictedComm_);
/* Allocate the restricted matrix*/
double *A; int LDA;
input_mv_->ExtractView(&A,&LDA);
restricted_mv_ = Teuchos::rcp(new Epetra_MultiVector(View,*ResMap_,A,LDA,input_mv_->NumVectors()));
}
}/*end restrict_comm*/
void
Albany::ModelEvaluator::evalModel(const InArgs& inArgs,
const OutArgs& outArgs) const
{
Teuchos::TimeMonitor Timer(*timer); //start timer
//
// Get the input arguments
//
Teuchos::RCP<const Epetra_Vector> x = inArgs.get_x();
Teuchos::RCP<const Epetra_Vector> x_dot;
Teuchos::RCP<const Epetra_Vector> x_dotdot;
double alpha = 0.0;
double omega = 0.0;
double beta = 1.0;
double curr_time = 0.0;
x_dot = inArgs.get_x_dot();
x_dotdot = inArgs.get_x_dotdot();
if (x_dot != Teuchos::null || x_dotdot != Teuchos::null) {
alpha = inArgs.get_alpha();
omega = inArgs.get_omega();
beta = inArgs.get_beta();
curr_time = inArgs.get_t();
}
for (int i=0; i<num_param_vecs; i++) {
Teuchos::RCP<const Epetra_Vector> p = inArgs.get_p(i);
if (p != Teuchos::null) {
for (unsigned int j=0; j<sacado_param_vec[i].size(); j++)
sacado_param_vec[i][j].baseValue = (*p)[j];
}
}
for (int i=0; i<num_dist_param_vecs; i++) {
Teuchos::RCP<const Epetra_Vector> p = inArgs.get_p(i+num_param_vecs);
if (p != Teuchos::null) {
*(distParamLib->get(dist_param_names[i])->vector()) = *p;
}
}
//
// Get the output arguments
//
EpetraExt::ModelEvaluator::Evaluation<Epetra_Vector> f_out = outArgs.get_f();
Teuchos::RCP<Epetra_Operator> W_out = outArgs.get_W();
// Cast W to a CrsMatrix, throw an exception if this fails
Teuchos::RCP<Epetra_CrsMatrix> W_out_crs;
if (W_out != Teuchos::null)
W_out_crs = Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_out, true);
int test_var = 0;
if(test_var != 0){
std::cout << "The current solution length is: " << x->MyLength() << std::endl;
x->Print(std::cout);
}
// Get preconditioner operator, if requested
Teuchos::RCP<Epetra_Operator> WPrec_out;
if (outArgs.supports(OUT_ARG_WPrec)) WPrec_out = outArgs.get_WPrec();
//
// Compute the functions
//
bool f_already_computed = false;
// W matrix
if (W_out != Teuchos::null) {
app->computeGlobalJacobian(alpha, beta, omega, curr_time, x_dot.get(), x_dotdot.get(),*x,
sacado_param_vec, f_out.get(), *W_out_crs);
f_already_computed=true;
if(test_var != 0){
//std::cout << "The current rhs length is: " << f_out->MyLength() << std::endl;
//f_out->Print(std::cout);
std::cout << "The current Jacobian length is: " << W_out_crs->NumGlobalRows() << std::endl;
W_out_crs->Print(std::cout);
}
}
if (WPrec_out != Teuchos::null) {
app->computeGlobalJacobian(alpha, beta, omega, curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, f_out.get(), *Extra_W_crs);
f_already_computed=true;
if(test_var != 0){
//std::cout << "The current rhs length is: " << f_out->MyLength() << std::endl;
//f_out->Print(std::cout);
std::cout << "The current preconditioner length is: " << Extra_W_crs->NumGlobalRows() << std::endl;
Extra_W_crs->Print(std::cout);
}
app->computeGlobalPreconditioner(Extra_W_crs, WPrec_out);
}
// scalar df/dp
for (int i=0; i<num_param_vecs; i++) {
Teuchos::RCP<Epetra_MultiVector> dfdp_out =
outArgs.get_DfDp(i).getMultiVector();
if (dfdp_out != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DfDp(i).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[i],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int j=0; j<p_indexes.size(); j++)
p_vec->addParam(sacado_param_vec[i][p_indexes[j]].family,
sacado_param_vec[i][p_indexes[j]].baseValue);
}
app->computeGlobalTangent(0.0, 0.0, 0.0, curr_time, false, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, p_vec.get(),
NULL, NULL, NULL, NULL, f_out.get(), NULL,
dfdp_out.get());
f_already_computed=true;
if(test_var != 0){
std::cout << "The current rhs length is: " << f_out->MyLength() << std::endl;
f_out->Print(std::cout);
}
}
}
// distributed df/dp
for (int i=0; i<num_dist_param_vecs; i++) {
Teuchos::RCP<Epetra_Operator> dfdp_out =
outArgs.get_DfDp(i+num_param_vecs).getLinearOp();
if (dfdp_out != Teuchos::null) {
Teuchos::RCP<DistributedParameterDerivativeOp> dfdp_op =
Teuchos::rcp_dynamic_cast<DistributedParameterDerivativeOp>(dfdp_out);
dfdp_op->set(curr_time, x_dot, x_dotdot, x,
Teuchos::rcp(&sacado_param_vec,false));
}
}
// f
if (app->is_adjoint) {
Derivative f_deriv(f_out, DERIV_TRANS_MV_BY_ROW);
int response_index = 0; // need to add capability for sending this in
app->evaluateResponseDerivative(response_index, curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, NULL,
NULL, f_deriv, Derivative(), Derivative(), Derivative());
}
else {
if (f_out != Teuchos::null && !f_already_computed) {
app->computeGlobalResidual(curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, *f_out);
if(test_var != 0){
std::cout << "The current rhs length is: " << f_out->MyLength() << std::endl;
f_out->Print(std::cout);
}
}
}
// Response functions
for (int i=0; i<outArgs.Ng(); i++) {
Teuchos::RCP<Epetra_Vector> g_out = outArgs.get_g(i);
bool g_computed = false;
Derivative dgdx_out = outArgs.get_DgDx(i);
Derivative dgdxdot_out = outArgs.get_DgDx_dot(i);
Derivative dgdxdotdot_out = outArgs.get_DgDx_dotdot(i);
// dg/dx, dg/dxdot
if (!dgdx_out.isEmpty() || !dgdxdot_out.isEmpty() || !dgdxdotdot_out.isEmpty() ) {
app->evaluateResponseDerivative(i, curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, NULL,
g_out.get(), dgdx_out,
dgdxdot_out, dgdxdotdot_out, Derivative());
g_computed = true;
}
// dg/dp
for (int j=0; j<num_param_vecs; j++) {
Teuchos::RCP<Epetra_MultiVector> dgdp_out =
outArgs.get_DgDp(i,j).getMultiVector();
if (dgdp_out != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DgDp(i,j).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[j],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int k=0; k<p_indexes.size(); k++)
p_vec->addParam(sacado_param_vec[j][p_indexes[k]].family,
sacado_param_vec[j][p_indexes[k]].baseValue);
}
app->evaluateResponseTangent(i, alpha, beta, omega, curr_time, false,
x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, p_vec.get(),
NULL, NULL, NULL, NULL, g_out.get(), NULL,
dgdp_out.get());
g_computed = true;
}
}
// Need to handle dg/dp for distributed p
if (g_out != Teuchos::null && !g_computed)
app->evaluateResponse(i, curr_time, x_dot.get(), x_dotdot.get(), *x, sacado_param_vec,
*g_out);
}
//
// Stochastic Galerkin
//
#ifdef ALBANY_SG_MP
InArgs::sg_const_vector_t x_sg = inArgs.get_x_sg();
if (x_sg != Teuchos::null) {
app->init_sg(inArgs.get_sg_basis(),
inArgs.get_sg_quadrature(),
inArgs.get_sg_expansion(),
x_sg->productComm());
InArgs::sg_const_vector_t x_dot_sg = inArgs.get_x_dot_sg();
InArgs::sg_const_vector_t x_dotdot_sg = inArgs.get_x_dotdot_sg();
if (x_dot_sg != Teuchos::null || x_dotdot_sg != Teuchos::null) {
alpha = inArgs.get_alpha();
omega = inArgs.get_omega();
beta = inArgs.get_beta();
curr_time = inArgs.get_t();
}
InArgs::sg_const_vector_t epetra_p_sg = inArgs.get_p_sg(0);
Teuchos::Array<int> p_sg_index;
for (int i=0; i<num_param_vecs; i++) {
InArgs::sg_const_vector_t p_sg = inArgs.get_p_sg(i);
if (p_sg != Teuchos::null) {
p_sg_index.push_back(i);
for (int j=0; j<p_sg_vals[i].size(); j++) {
int num_sg_blocks = p_sg->size();
p_sg_vals[i][j].reset(app->getStochasticExpansion(), num_sg_blocks);
p_sg_vals[i][j].copyForWrite();
for (int l=0; l<num_sg_blocks; l++) {
p_sg_vals[i][j].fastAccessCoeff(l) = (*p_sg)[l][j];
}
}
}
}
OutArgs::sg_vector_t f_sg = outArgs.get_f_sg();
OutArgs::sg_operator_t W_sg = outArgs.get_W_sg();
bool f_sg_computed = false;
// W_sg
if (W_sg != Teuchos::null) {
Stokhos::VectorOrthogPoly<Epetra_CrsMatrix> W_sg_crs(W_sg->basis(),
W_sg->map());
for (int i=0; i<W_sg->size(); i++)
W_sg_crs.setCoeffPtr(
i,
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_sg->getCoeffPtr(i)));
app->computeGlobalSGJacobian(alpha, beta, omega, curr_time,
x_dot_sg.get(), x_dotdot_sg.get(), *x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
f_sg.get(), W_sg_crs);
f_sg_computed = true;
}
// df/dp_sg
for (int i=0; i<num_param_vecs; i++) {
Teuchos::RCP< Stokhos::EpetraMultiVectorOrthogPoly > dfdp_sg
= outArgs.get_DfDp_sg(i).getMultiVector();
if (dfdp_sg != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DfDp_sg(i).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[i],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int j=0; j<p_indexes.size(); j++)
p_vec->addParam(sacado_param_vec[i][p_indexes[j]].family,
sacado_param_vec[i][p_indexes[j]].baseValue);
}
app->computeGlobalSGTangent(0.0, 0.0, 0.0, curr_time, false,
x_dot_sg.get(), x_dotdot_sg.get(),*x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
p_vec.get(), NULL, NULL, NULL, NULL,
f_sg.get(), NULL, dfdp_sg.get());
f_sg_computed = true;
}
}
if (f_sg != Teuchos::null && !f_sg_computed)
app->computeGlobalSGResidual(curr_time, x_dot_sg.get(), x_dotdot_sg.get(),*x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
*f_sg);
// Response functions
for (int i=0; i<outArgs.Ng(); i++) {
OutArgs::sg_vector_t g_sg = outArgs.get_g_sg(i);
bool g_sg_computed = false;
SGDerivative dgdx_sg = outArgs.get_DgDx_sg(i);
SGDerivative dgdxdot_sg = outArgs.get_DgDx_dot_sg(i);
SGDerivative dgdxdotdot_sg = outArgs.get_DgDx_dotdot_sg(i);
// dg/dx, dg/dxdot
if (!dgdx_sg.isEmpty() || !dgdxdot_sg.isEmpty() || !dgdxdotdot_sg.isEmpty()) {
app->evaluateSGResponseDerivative(
i, curr_time, x_dot_sg.get(), x_dotdot_sg.get(), *x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
NULL, g_sg.get(), dgdx_sg,
dgdxdot_sg, dgdxdotdot_sg, SGDerivative());
g_sg_computed = true;
}
// dg/dp
for (int j=0; j<num_param_vecs; j++) {
Teuchos::RCP< Stokhos::EpetraMultiVectorOrthogPoly > dgdp_sg =
outArgs.get_DgDp_sg(i,j).getMultiVector();
if (dgdp_sg != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DgDp_sg(i,j).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[j],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int k=0; k<p_indexes.size(); k++)
p_vec->addParam(sacado_param_vec[j][p_indexes[k]].family,
sacado_param_vec[j][p_indexes[k]].baseValue);
}
app->evaluateSGResponseTangent(i, alpha, beta, omega, curr_time, false,
x_dot_sg.get(), x_dotdot_sg.get(), *x_sg,
sacado_param_vec, p_sg_index,
p_sg_vals, p_vec.get(),
NULL, NULL, NULL, NULL, g_sg.get(),
NULL, dgdp_sg.get());
g_sg_computed = true;
}
}
if (g_sg != Teuchos::null && !g_sg_computed)
app->evaluateSGResponse(i, curr_time, x_dot_sg.get(), x_dotdot_sg.get(), *x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
*g_sg);
}
}
//
// Multi-point evaluation
//
mp_const_vector_t x_mp = inArgs.get_x_mp();
if (x_mp != Teuchos::null) {
mp_const_vector_t x_dot_mp = inArgs.get_x_dot_mp();
mp_const_vector_t x_dotdot_mp = inArgs.get_x_dotdot_mp();
if (x_dot_mp != Teuchos::null || x_dotdot_mp != Teuchos::null) {
alpha = inArgs.get_alpha();
omega = inArgs.get_omega();
beta = inArgs.get_beta();
curr_time = inArgs.get_t();
}
Teuchos::Array<int> p_mp_index;
for (int i=0; i<num_param_vecs; i++) {
mp_const_vector_t p_mp = inArgs.get_p_mp(i);
if (p_mp != Teuchos::null) {
p_mp_index.push_back(i);
for (int j=0; j<p_mp_vals[i].size(); j++) {
int num_mp_blocks = p_mp->size();
p_mp_vals[i][j].reset(num_mp_blocks);
p_mp_vals[i][j].copyForWrite();
for (int l=0; l<num_mp_blocks; l++) {
p_mp_vals[i][j].fastAccessCoeff(l) = (*p_mp)[l][j];
}
}
}
}
mp_vector_t f_mp = outArgs.get_f_mp();
mp_operator_t W_mp = outArgs.get_W_mp();
bool f_mp_computed = false;
// W_mp
if (W_mp != Teuchos::null) {
Stokhos::ProductContainer<Epetra_CrsMatrix> W_mp_crs(W_mp->map());
for (int i=0; i<W_mp->size(); i++)
W_mp_crs.setCoeffPtr(
i,
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_mp->getCoeffPtr(i)));
app->computeGlobalMPJacobian(alpha, beta, omega, curr_time,
x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
f_mp.get(), W_mp_crs);
f_mp_computed = true;
}
// df/dp_mp
for (int i=0; i<num_param_vecs; i++) {
Teuchos::RCP< Stokhos::ProductEpetraMultiVector > dfdp_mp
= outArgs.get_DfDp_mp(i).getMultiVector();
if (dfdp_mp != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DfDp_mp(i).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[i],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int j=0; j<p_indexes.size(); j++)
p_vec->addParam(sacado_param_vec[i][p_indexes[j]].family,
sacado_param_vec[i][p_indexes[j]].baseValue);
}
app->computeGlobalMPTangent(0.0, 0.0, 0.0, curr_time, false,
x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
p_vec.get(), NULL, NULL, NULL, NULL,
f_mp.get(), NULL, dfdp_mp.get());
f_mp_computed = true;
}
}
if (f_mp != Teuchos::null && !f_mp_computed)
app->computeGlobalMPResidual(curr_time, x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
*f_mp);
// Response functions
for (int i=0; i<outArgs.Ng(); i++) {
mp_vector_t g_mp = outArgs.get_g_mp(i);
bool g_mp_computed = false;
MPDerivative dgdx_mp = outArgs.get_DgDx_mp(i);
MPDerivative dgdxdot_mp = outArgs.get_DgDx_dot_mp(i);
MPDerivative dgdxdotdot_mp = outArgs.get_DgDx_dotdot_mp(i);
// dg/dx, dg/dxdot
if (!dgdx_mp.isEmpty() || !dgdxdot_mp.isEmpty() || !dgdxdotdot_mp.isEmpty() ) {
app->evaluateMPResponseDerivative(
i, curr_time, x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
NULL, g_mp.get(), dgdx_mp,
dgdxdot_mp, dgdxdotdot_mp, MPDerivative());
g_mp_computed = true;
}
// dg/dp
for (int j=0; j<num_param_vecs; j++) {
Teuchos::RCP< Stokhos::ProductEpetraMultiVector > dgdp_mp =
outArgs.get_DgDp_mp(i,j).getMultiVector();
if (dgdp_mp != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DgDp_mp(i,j).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[j],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int k=0; k<p_indexes.size(); k++)
p_vec->addParam(sacado_param_vec[j][p_indexes[k]].family,
sacado_param_vec[j][p_indexes[k]].baseValue);
}
app->evaluateMPResponseTangent(i, alpha, beta, omega, curr_time, false,
x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index,
p_mp_vals, p_vec.get(),
NULL, NULL, NULL, NULL, g_mp.get(),
NULL, dgdp_mp.get());
g_mp_computed = true;
}
}
if (g_mp != Teuchos::null && !g_mp_computed)
app->evaluateMPResponse(i, curr_time, x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
*g_mp);
}
}
#endif //ALBANY_SG_MP
}
void
Albany::ModelEvaluator::evalModel(const InArgs& inArgs,
const OutArgs& outArgs) const
{
Teuchos::TimeMonitor Timer(*timer); //start timer
//
// Get the input arguments
//
Teuchos::RCP<const Epetra_Vector> x = inArgs.get_x();
Teuchos::RCP<const Epetra_Vector> x_dot;
Teuchos::RCP<const Epetra_Vector> x_dotdot;
//create comm and node objects for Epetra -> Tpetra conversions
Teuchos::RCP<const Teuchos::Comm<int> > commT = app->getComm();
Teuchos::RCP<Epetra_Comm> comm = Albany::createEpetraCommFromTeuchosComm(commT);
//Create Tpetra copy of x, call it xT
Teuchos::RCP<const Tpetra_Vector> xT;
if (x != Teuchos::null)
xT = Petra::EpetraVector_To_TpetraVectorConst(*x, commT);
double alpha = 0.0;
double omega = 0.0;
double beta = 1.0;
double curr_time = 0.0;
if(num_time_deriv > 0)
x_dot = inArgs.get_x_dot();
if(num_time_deriv > 1)
x_dotdot = inArgs.get_x_dotdot();
//Declare and create Tpetra copy of x_dot, call it x_dotT
Teuchos::RCP<const Tpetra_Vector> x_dotT;
if (Teuchos::nonnull(x_dot))
x_dotT = Petra::EpetraVector_To_TpetraVectorConst(*x_dot, commT);
//Declare and create Tpetra copy of x_dotdot, call it x_dotdotT
Teuchos::RCP<const Tpetra_Vector> x_dotdotT;
if (Teuchos::nonnull(x_dotdot))
x_dotdotT = Petra::EpetraVector_To_TpetraVectorConst(*x_dotdot, commT);
if (Teuchos::nonnull(x_dot)){
alpha = inArgs.get_alpha();
beta = inArgs.get_beta();
curr_time = inArgs.get_t();
}
if (Teuchos::nonnull(x_dotdot)) {
omega = inArgs.get_omega();
}
for (int i=0; i<num_param_vecs; i++) {
Teuchos::RCP<const Epetra_Vector> p = inArgs.get_p(i);
if (p != Teuchos::null) {
for (unsigned int j=0; j<sacado_param_vec[i].size(); j++) {
sacado_param_vec[i][j].baseValue = (*p)[j];
}
}
}
for (int i=0; i<num_dist_param_vecs; i++) {
Teuchos::RCP<const Epetra_Vector> p = inArgs.get_p(i+num_param_vecs);
//create Tpetra copy of p
Teuchos::RCP<const Tpetra_Vector> pT;
if (p != Teuchos::null) {
pT = Petra::EpetraVector_To_TpetraVectorConst(*p, commT);
//*(distParamLib->get(dist_param_names[i])->vector()) = *p;
*(distParamLib->get(dist_param_names[i])->vector()) = *pT;
}
}
//
// Get the output arguments
//
EpetraExt::ModelEvaluator::Evaluation<Epetra_Vector> f_out = outArgs.get_f();
Teuchos::RCP<Epetra_Operator> W_out = outArgs.get_W();
// Cast W to a CrsMatrix, throw an exception if this fails
Teuchos::RCP<Epetra_CrsMatrix> W_out_crs;
#ifdef WRITE_MASS_MATRIX_TO_MM_FILE
//IK, 7/15/14: adding object to hold mass matrix to be written to matrix market file
Teuchos::RCP<Epetra_CrsMatrix> Mass;
//IK, 7/15/14: needed for writing mass matrix out to matrix market file
EpetraExt::ModelEvaluator::Evaluation<Epetra_Vector> ftmp = outArgs.get_f();
#endif
if (W_out != Teuchos::null) {
W_out_crs = Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_out, true);
#ifdef WRITE_MASS_MATRIX_TO_MM_FILE
//IK, 7/15/14: adding object to hold mass matrix to be written to matrix market file
Mass = Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_out, true);
#endif
}
int test_var = 0;
if(test_var != 0){
std::cout << "The current solution length is: " << x->MyLength() << std::endl;
x->Print(std::cout);
}
// Get preconditioner operator, if requested
Teuchos::RCP<Epetra_Operator> WPrec_out;
if (outArgs.supports(OUT_ARG_WPrec)) WPrec_out = outArgs.get_WPrec();
//
// Compute the functions
//
bool f_already_computed = false;
// W matrix
if (W_out != Teuchos::null) {
app->computeGlobalJacobian(alpha, beta, omega, curr_time, x_dot.get(), x_dotdot.get(),*x,
sacado_param_vec, f_out.get(), *W_out_crs);
#ifdef WRITE_MASS_MATRIX_TO_MM_FILE
//IK, 7/15/14: write mass matrix to matrix market file
//Warning: to read this in to MATLAB correctly, code must be run in serial.
//Otherwise Mass will have a distributed Map which would also need to be read in to MATLAB for proper
//reading in of Mass.
app->computeGlobalJacobian(1.0, 0.0, 0.0, curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, ftmp.get(), *Mass);
EpetraExt::RowMatrixToMatrixMarketFile("mass.mm", *Mass);
EpetraExt::BlockMapToMatrixMarketFile("rowmap.mm", Mass->RowMap());
EpetraExt::BlockMapToMatrixMarketFile("colmap.mm", Mass->ColMap());
Teuchos::RCP<Teuchos::FancyOStream> out = Teuchos::VerboseObjectBase::getDefaultOStream();
#endif
f_already_computed=true;
if(test_var != 0){
//std::cout << "The current rhs length is: " << f_out->MyLength() << std::endl;
//f_out->Print(std::cout);
std::cout << "The current Jacobian length is: " << W_out_crs->NumGlobalRows() << std::endl;
W_out_crs->Print(std::cout);
}
}
if (WPrec_out != Teuchos::null) {
app->computeGlobalJacobian(alpha, beta, omega, curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, f_out.get(), *Extra_W_crs);
f_already_computed=true;
if(test_var != 0){
//std::cout << "The current rhs length is: " << f_out->MyLength() << std::endl;
//f_out->Print(std::cout);
std::cout << "The current preconditioner length is: " << Extra_W_crs->NumGlobalRows() << std::endl;
Extra_W_crs->Print(std::cout);
}
app->computeGlobalPreconditioner(Extra_W_crs, WPrec_out);
}
// scalar df/dp
for (int i=0; i<num_param_vecs; i++) {
Teuchos::RCP<Epetra_MultiVector> dfdp_out =
outArgs.get_DfDp(i).getMultiVector();
if (dfdp_out != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DfDp(i).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[i],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int j=0; j<p_indexes.size(); j++)
p_vec->addParam(sacado_param_vec[i][p_indexes[j]].family,
sacado_param_vec[i][p_indexes[j]].baseValue);
}
app->computeGlobalTangent(0.0, 0.0, 0.0, curr_time, false, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, p_vec.get(),
NULL, NULL, NULL, NULL, f_out.get(), NULL,
dfdp_out.get());
f_already_computed=true;
if(test_var != 0){
std::cout << "The current rhs length is: " << f_out->MyLength() << std::endl;
f_out->Print(std::cout);
}
}
}
// distributed df/dp
for (int i=0; i<num_dist_param_vecs; i++) {
Teuchos::RCP<Epetra_Operator> dfdp_out =
outArgs.get_DfDp(i+num_param_vecs).getLinearOp();
if (dfdp_out != Teuchos::null) {
Teuchos::RCP<DistributedParameterDerivativeOp> dfdp_op =
Teuchos::rcp_dynamic_cast<DistributedParameterDerivativeOp>(dfdp_out);
dfdp_op->set(curr_time, x_dotT, x_dotdotT, xT,
Teuchos::rcp(&sacado_param_vec,false));
}
}
// f
if (app->is_adjoint) {
Derivative f_deriv(f_out, DERIV_TRANS_MV_BY_ROW);
int response_index = 0; // need to add capability for sending this in
app->evaluateResponseDerivative(response_index, curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, NULL,
NULL, f_deriv, Derivative(), Derivative(), Derivative());
}
else {
if (f_out != Teuchos::null && !f_already_computed) {
app->computeGlobalResidual(curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, *f_out);
if(test_var != 0){
std::cout << "The current rhs length is: " << f_out->MyLength() << std::endl;
f_out->Print(std::cout);
}
}
}
// Response functions
for (int i=0; i<outArgs.Ng(); i++) {
//Set curr_time to final time at which response occurs.
if(num_time_deriv > 0)
curr_time = inArgs.get_t();
Teuchos::RCP<Epetra_Vector> g_out = outArgs.get_g(i);
//Declare Tpetra_Vector copy of g_out
Teuchos::RCP<Tpetra_Vector> g_outT;
bool g_computed = false;
Derivative dgdx_out = outArgs.get_DgDx(i);
Derivative dgdxdot_out = outArgs.get_DgDx_dot(i);
Derivative dgdxdotdot_out = outArgs.get_DgDx_dotdot(i);
// dg/dx, dg/dxdot
if (!dgdx_out.isEmpty() || !dgdxdot_out.isEmpty() || !dgdxdotdot_out.isEmpty() ) {
app->evaluateResponseDerivative(i, curr_time, x_dot.get(), x_dotdot.get(), *x,
sacado_param_vec, NULL,
g_out.get(), dgdx_out,
dgdxdot_out, dgdxdotdot_out, Derivative());
g_computed = true;
}
// dg/dp
for (int j=0; j<num_param_vecs; j++) {
Teuchos::RCP<Epetra_MultiVector> dgdp_out =
outArgs.get_DgDp(i,j).getMultiVector();
//Declare Tpetra copy of dgdp_out
Teuchos::RCP<Tpetra_MultiVector> dgdp_outT;
if (dgdp_out != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DgDp(i,j).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[j],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int k=0; k<p_indexes.size(); k++)
p_vec->addParam(sacado_param_vec[j][p_indexes[k]].family,
sacado_param_vec[j][p_indexes[k]].baseValue);
}
//create Tpetra copy of g_out, call it g_outT
if (g_out != Teuchos::null)
g_outT = Petra::EpetraVector_To_TpetraVectorNonConst(*g_out, commT);
//create Tpetra copy of dgdp_out, call it dgdp_outT
if (dgdp_out != Teuchos::null)
dgdp_outT = Petra::EpetraMultiVector_To_TpetraMultiVector(*dgdp_out, commT);
app->evaluateResponseTangentT(i, alpha, beta, omega, curr_time, false,
x_dotT.get(), x_dotdotT.get(), *xT,
sacado_param_vec, p_vec.get(),
NULL, NULL, NULL, NULL, g_outT.get(), NULL,
dgdp_outT.get());
//convert g_outT to Epetra_Vector g_out
if (g_out != Teuchos::null)
Petra::TpetraVector_To_EpetraVector(g_outT, *g_out, comm);
//convert dgdp_outT to Epetra_MultiVector dgdp_out
if (dgdp_out != Teuchos::null)
Petra::TpetraMultiVector_To_EpetraMultiVector(dgdp_outT, *dgdp_out, comm);
g_computed = true;
}
}
// Need to handle dg/dp for distributed p
for(int j=0; j<num_dist_param_vecs; j++) {
Derivative dgdp_out = outArgs.get_DgDp(i,j+num_param_vecs);
if (!dgdp_out.isEmpty()) {
dgdp_out.getMultiVector()->PutScalar(0.);
app->evaluateResponseDistParamDeriv(i, curr_time, x_dot.get(), x_dotdot.get(), *x, sacado_param_vec, dist_param_names[j], dgdp_out.getMultiVector().get());
}
}
if (g_out != Teuchos::null && !g_computed) {
//create Tpetra copy of g_out, call it g_outT
g_outT = Petra::EpetraVector_To_TpetraVectorNonConst(*g_out, commT);
app->evaluateResponseT(i, curr_time, x_dotT.get(), x_dotdotT.get(), *xT, sacado_param_vec,
*g_outT);
//convert g_outT to Epetra_Vector g_out
Petra::TpetraVector_To_EpetraVector(g_outT, *g_out, comm);
}
}
//
// Stochastic Galerkin
//
#ifdef ALBANY_SG
InArgs::sg_const_vector_t x_sg = inArgs.get_x_sg();
if (x_sg != Teuchos::null) {
app->init_sg(inArgs.get_sg_basis(),
inArgs.get_sg_quadrature(),
inArgs.get_sg_expansion(),
x_sg->productComm());
InArgs::sg_const_vector_t x_dot_sg = Teuchos::null;
InArgs::sg_const_vector_t x_dot_sg = Teuchos::null;
if(num_time_deriv > 0)
x_dotdot_sg = inArgs.get_x_dotdot_sg();
if(num_time_deriv > 1)
x_dotdot_sg = inArgs.get_x_dotdot_sg();
if (x_dot_sg != Teuchos::null || x_dotdot_sg != Teuchos::null) {
alpha = inArgs.get_alpha();
beta = inArgs.get_beta();
curr_time = inArgs.get_t();
}
if (x_dotdot_sg != Teuchos::null) {
omega = inArgs.get_omega();
}
InArgs::sg_const_vector_t epetra_p_sg = inArgs.get_p_sg(0);
Teuchos::Array<int> p_sg_index;
for (int i=0; i<num_param_vecs; i++) {
InArgs::sg_const_vector_t p_sg = inArgs.get_p_sg(i);
if (p_sg != Teuchos::null) {
p_sg_index.push_back(i);
for (int j=0; j<p_sg_vals[i].size(); j++) {
int num_sg_blocks = p_sg->size();
p_sg_vals[i][j].reset(app->getStochasticExpansion(), num_sg_blocks);
p_sg_vals[i][j].copyForWrite();
for (int l=0; l<num_sg_blocks; l++) {
p_sg_vals[i][j].fastAccessCoeff(l) = (*p_sg)[l][j];
}
}
}
}
OutArgs::sg_vector_t f_sg = outArgs.get_f_sg();
OutArgs::sg_operator_t W_sg = outArgs.get_W_sg();
bool f_sg_computed = false;
// W_sg
if (W_sg != Teuchos::null) {
Stokhos::VectorOrthogPoly<Epetra_CrsMatrix> W_sg_crs(W_sg->basis(),
W_sg->map());
for (int i=0; i<W_sg->size(); i++)
W_sg_crs.setCoeffPtr(
i,
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_sg->getCoeffPtr(i)));
app->computeGlobalSGJacobian(alpha, beta, omega, curr_time,
x_dot_sg.get(), x_dotdot_sg.get(), *x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
f_sg.get(), W_sg_crs);
f_sg_computed = true;
}
// df/dp_sg
for (int i=0; i<num_param_vecs; i++) {
Teuchos::RCP< Stokhos::EpetraMultiVectorOrthogPoly > dfdp_sg
= outArgs.get_DfDp_sg(i).getMultiVector();
if (dfdp_sg != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DfDp_sg(i).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[i],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int j=0; j<p_indexes.size(); j++)
p_vec->addParam(sacado_param_vec[i][p_indexes[j]].family,
sacado_param_vec[i][p_indexes[j]].baseValue);
}
app->computeGlobalSGTangent(0.0, 0.0, 0.0, curr_time, false,
x_dot_sg.get(), x_dotdot_sg.get(),*x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
p_vec.get(), NULL, NULL, NULL, NULL,
f_sg.get(), NULL, dfdp_sg.get());
f_sg_computed = true;
}
}
if (f_sg != Teuchos::null && !f_sg_computed)
app->computeGlobalSGResidual(curr_time, x_dot_sg.get(), x_dotdot_sg.get(),*x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
*f_sg);
// Response functions
for (int i=0; i<outArgs.Ng(); i++) {
OutArgs::sg_vector_t g_sg = outArgs.get_g_sg(i);
bool g_sg_computed = false;
SGDerivative dgdx_sg = outArgs.get_DgDx_sg(i);
SGDerivative dgdxdot_sg = outArgs.get_DgDx_dot_sg(i);
SGDerivative dgdxdotdot_sg = outArgs.get_DgDx_dotdot_sg(i);
// dg/dx, dg/dxdot
if (!dgdx_sg.isEmpty() || !dgdxdot_sg.isEmpty() || !dgdxdotdot_sg.isEmpty()) {
app->evaluateSGResponseDerivative(
i, curr_time, x_dot_sg.get(), x_dotdot_sg.get(), *x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
NULL, g_sg.get(), dgdx_sg,
dgdxdot_sg, dgdxdotdot_sg, SGDerivative());
g_sg_computed = true;
}
// dg/dp
for (int j=0; j<num_param_vecs; j++) {
Teuchos::RCP< Stokhos::EpetraMultiVectorOrthogPoly > dgdp_sg =
outArgs.get_DgDp_sg(i,j).getMultiVector();
if (dgdp_sg != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DgDp_sg(i,j).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[j],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int k=0; k<p_indexes.size(); k++)
p_vec->addParam(sacado_param_vec[j][p_indexes[k]].family,
sacado_param_vec[j][p_indexes[k]].baseValue);
}
app->evaluateSGResponseTangent(i, alpha, beta, omega, curr_time, false,
x_dot_sg.get(), x_dotdot_sg.get(), *x_sg,
sacado_param_vec, p_sg_index,
p_sg_vals, p_vec.get(),
NULL, NULL, NULL, NULL, g_sg.get(),
NULL, dgdp_sg.get());
g_sg_computed = true;
}
}
if (g_sg != Teuchos::null && !g_sg_computed)
app->evaluateSGResponse(i, curr_time, x_dot_sg.get(), x_dotdot_sg.get(), *x_sg,
sacado_param_vec, p_sg_index, p_sg_vals,
*g_sg);
}
}
#endif
#ifdef ALBANY_ENSEMBLE
//
// Multi-point evaluation
//
mp_const_vector_t x_mp = inArgs.get_x_mp();
if (x_mp != Teuchos::null) {
mp_const_vector_t x_dot_mp = Teuchos::null;
mp_const_vector_t x_dotdot_mp = Teuchos::null;
if(num_time_deriv > 0)
x_dot_mp = inArgs.get_x_dot_mp();
if(num_time_deriv > 1)
x_dotdot_mp = inArgs.get_x_dotdot_mp();
if (x_dot_mp != Teuchos::null || x_dotdot_mp != Teuchos::null) {
alpha = inArgs.get_alpha();
//omega = inArgs.get_omega();
beta = inArgs.get_beta();
curr_time = inArgs.get_t();
}
if (x_dotdot_mp != Teuchos::null) {
omega = inArgs.get_omega();
}
Teuchos::Array<int> p_mp_index;
for (int i=0; i<num_param_vecs; i++) {
mp_const_vector_t p_mp = inArgs.get_p_mp(i);
if (p_mp != Teuchos::null) {
p_mp_index.push_back(i);
for (int j=0; j<p_mp_vals[i].size(); j++) {
int num_mp_blocks = p_mp->size();
p_mp_vals[i][j].reset(num_mp_blocks);
p_mp_vals[i][j].copyForWrite();
for (int l=0; l<num_mp_blocks; l++) {
p_mp_vals[i][j].fastAccessCoeff(l) = (*p_mp)[l][j];
}
}
}
}
mp_vector_t f_mp = outArgs.get_f_mp();
mp_operator_t W_mp = outArgs.get_W_mp();
bool f_mp_computed = false;
// W_mp
if (W_mp != Teuchos::null) {
Stokhos::ProductContainer<Epetra_CrsMatrix> W_mp_crs(W_mp->map());
for (int i=0; i<W_mp->size(); i++)
W_mp_crs.setCoeffPtr(
i,
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_mp->getCoeffPtr(i)));
app->computeGlobalMPJacobian(alpha, beta, omega, curr_time,
x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
f_mp.get(), W_mp_crs);
f_mp_computed = true;
}
// df/dp_mp
for (int i=0; i<num_param_vecs; i++) {
Teuchos::RCP< Stokhos::ProductEpetraMultiVector > dfdp_mp
= outArgs.get_DfDp_mp(i).getMultiVector();
if (dfdp_mp != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DfDp_mp(i).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[i],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int j=0; j<p_indexes.size(); j++)
p_vec->addParam(sacado_param_vec[i][p_indexes[j]].family,
sacado_param_vec[i][p_indexes[j]].baseValue);
}
app->computeGlobalMPTangent(0.0, 0.0, 0.0, curr_time, false,
x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
p_vec.get(), NULL, NULL, NULL, NULL,
f_mp.get(), NULL, dfdp_mp.get());
f_mp_computed = true;
}
}
if (f_mp != Teuchos::null && !f_mp_computed)
app->computeGlobalMPResidual(curr_time, x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
*f_mp);
// Response functions
for (int i=0; i<outArgs.Ng(); i++) {
mp_vector_t g_mp = outArgs.get_g_mp(i);
bool g_mp_computed = false;
MPDerivative dgdx_mp = outArgs.get_DgDx_mp(i);
MPDerivative dgdxdot_mp = outArgs.get_DgDx_dot_mp(i);
MPDerivative dgdxdotdot_mp = outArgs.get_DgDx_dotdot_mp(i);
// dg/dx, dg/dxdot
if (!dgdx_mp.isEmpty() || !dgdxdot_mp.isEmpty() || !dgdxdotdot_mp.isEmpty() ) {
app->evaluateMPResponseDerivative(
i, curr_time, x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
NULL, g_mp.get(), dgdx_mp,
dgdxdot_mp, dgdxdotdot_mp, MPDerivative());
g_mp_computed = true;
}
// dg/dp
for (int j=0; j<num_param_vecs; j++) {
Teuchos::RCP< Stokhos::ProductEpetraMultiVector > dgdp_mp =
outArgs.get_DgDp_mp(i,j).getMultiVector();
if (dgdp_mp != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DgDp_mp(i,j).getDerivativeMultiVector().getParamIndexes();
Teuchos::RCP<ParamVec> p_vec;
if (p_indexes.size() == 0)
p_vec = Teuchos::rcp(&sacado_param_vec[j],false);
else {
p_vec = Teuchos::rcp(new ParamVec);
for (int k=0; k<p_indexes.size(); k++)
p_vec->addParam(sacado_param_vec[j][p_indexes[k]].family,
sacado_param_vec[j][p_indexes[k]].baseValue);
}
app->evaluateMPResponseTangent(i, alpha, beta, omega, curr_time, false,
x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index,
p_mp_vals, p_vec.get(),
NULL, NULL, NULL, NULL, g_mp.get(),
NULL, dgdp_mp.get());
g_mp_computed = true;
}
}
if (g_mp != Teuchos::null && !g_mp_computed)
app->evaluateMPResponse(i, curr_time, x_dot_mp.get(), x_dotdot_mp.get(), *x_mp,
sacado_param_vec, p_mp_index, p_mp_vals,
*g_mp);
}
}
#endif
}
void InitialConditions(const Teuchos::RCP<Epetra_Vector>& soln,
const Teuchos::ArrayRCP<Teuchos::ArrayRCP<Teuchos::ArrayRCP<Teuchos::ArrayRCP<int> > > >& wsElNodeEqID,
const Teuchos::ArrayRCP<std::string>& wsEBNames,
const Teuchos::ArrayRCP<Teuchos::ArrayRCP<Teuchos::ArrayRCP<double*> > > coords,
const int neq, const int numDim,
Teuchos::ParameterList& icParams, const bool hasRestartSolution) {
// Called twice, with x and xdot. Different param lists are sent in.
icParams.validateParameters(*AAdapt::getValidInitialConditionParameters(wsEBNames), 0);
// Default function is Constant, unless a Restart solution vector
// was used, in which case the Init COnd defaults to Restart.
std::string name;
if(!hasRestartSolution) name = icParams.get("Function", "Constant");
else name = icParams.get("Function", "Restart");
if(name == "Restart") return;
// Handle element block specific constant data
if(name == "EBPerturb" || name == "EBPerturbGaussian" || name == "EBConstant") {
bool perturb_values = false;
Teuchos::Array<double> defaultData(neq);
Teuchos::Array<double> perturb_mag;
// Only perturb if the user has told us by how much to perturb
if(name != "EBConstant" && icParams.isParameter("Perturb IC")) {
perturb_values = true;
perturb_mag = icParams.get("Perturb IC", defaultData);
}
/* The element block-based IC specification here is currently a hack. It assumes the initial value is constant
* within each element across the element block (or optionally perturbed somewhat element by element). The
* proper way to do this would be to project the element integration point values to the nodes using the basis
* functions and a consistent mass matrix.
*
* The current implementation uses a single integration point per element - this integration point value for this
* element within the element block is specified in the input file (and optionally perturbed). An approximation
* of the load vector is obtained by accumulating the resulting (possibly perturbed) value into the nodes. Then,
* a lumped version of the mass matrix is inverted and used to solve for the approximate nodal point initial
* conditions.
*/
// Use an Epetra_Vector to hold the lumped mass matrix (has entries only on the diagonal). Zero-ed out.
Epetra_Vector lumpedMM(soln->Map(), true);
// Make sure soln is zeroed - we are accumulating into it
for(int i = 0; i < soln->MyLength(); i++)
(*soln)[i] = 0;
// Loop over all worksets, elements, all local nodes: compute soln as a function of coord and wsEBName
Teuchos::RCP<AAdapt::AnalyticFunction> initFunc;
for(int ws = 0; ws < wsElNodeEqID.size(); ws++) { // loop over worksets
Teuchos::Array<double> data = icParams.get(wsEBNames[ws], defaultData);
// Call factory method from library of initial condition functions
if(perturb_values) {
if(name == "EBPerturb")
initFunc = Teuchos::rcp(new AAdapt::ConstantFunctionPerturbed(neq, numDim, ws, data, perturb_mag));
else // name == EBGaussianPerturb
initFunc = Teuchos::rcp(new
AAdapt::ConstantFunctionGaussianPerturbed(neq, numDim, ws, data, perturb_mag));
}
else
initFunc = Teuchos::rcp(new AAdapt::ConstantFunction(neq, numDim, data));
std::vector<double> X(neq);
std::vector<double> x(neq);
for(int el = 0; el < wsElNodeEqID[ws].size(); el++) { // loop over elements in workset
for(int i = 0; i < neq; i++)
X[i] = 0;
for(int ln = 0; ln < wsElNodeEqID[ws][el].size(); ln++) // loop over node local to the element
for(int i = 0; i < neq; i++)
X[i] += coords[ws][el][ln][i]; // nodal coords
for(int i = 0; i < neq; i++)
X[i] /= (double)neq;
initFunc->compute(&x[0], &X[0]);
for(int ln = 0; ln < wsElNodeEqID[ws][el].size(); ln++) { // loop over node local to the element
Teuchos::ArrayRCP<int> lid = wsElNodeEqID[ws][el][ln]; // local node ids
for(int i = 0; i < neq; i++) {
(*soln)[lid[i]] += x[i];
// (*soln)[lid[i]] += X[i]; // Test with coord values
lumpedMM[lid[i]] += 1.0;
}
}
}
}
// Apply the inverted lumped mass matrix to get the final nodal projection
for(int i = 0; i < soln->MyLength(); i++)
(*soln)[i] /= lumpedMM[i];
return;
}
if(name == "Coordinates") {
// Place the coordinate locations of the nodes into the solution vector for an initial guess
int numDOFsPerDim = neq / numDim;
for(int ws = 0; ws < wsElNodeEqID.size(); ws++) {
for(int el = 0; el < wsElNodeEqID[ws].size(); el++) {
for(int ln = 0; ln < wsElNodeEqID[ws][el].size(); ln++) {
const double* X = coords[ws][el][ln];
Teuchos::ArrayRCP<int> lid = wsElNodeEqID[ws][el][ln];
/*
numDim = 3; numDOFSsPerDim = 2 (coord soln, tgt soln)
X[0] = x;
X[1] = y;
X[2] = z;
lid[0] = DOF[0],eq[0] (x eqn)
lid[1] = DOF[0],eq[1] (y eqn)
lid[2] = DOF[0],eq[2] (z eqn)
lid[3] = DOF[1],eq[0] (x eqn)
lid[4] = DOF[1],eq[1] (y eqn)
lid[5] = DOF[1],eq[2] (z eqn)
*/
for(int j = 0; j < numDOFsPerDim; j++)
for(int i = 0; i < numDim; i++)
(*soln)[lid[j * numDim + i]] = X[i];
}
}
}
}
else {
Teuchos::Array<double> defaultData(neq);
Teuchos::Array<double> data = icParams.get("Function Data", defaultData);
// Call factory method from library of initial condition functions
Teuchos::RCP<AAdapt::AnalyticFunction> initFunc
= createAnalyticFunction(name, neq, numDim, data);
// Loop over all worksets, elements, all local nodes: compute soln as a function of coord
std::vector<double> x(neq);
for(int ws = 0; ws < wsElNodeEqID.size(); ws++) {
for(int el = 0; el < wsElNodeEqID[ws].size(); el++) {
for(int ln = 0; ln < wsElNodeEqID[ws][el].size(); ln++) {
const double* X = coords[ws][el][ln];
Teuchos::ArrayRCP<int> lid = wsElNodeEqID[ws][el][ln];
for(int i = 0; i < neq; i++) x[i] = (*soln)[lid[i]];
initFunc->compute(&x[0], X);
for(int i = 0; i < neq; i++)(*soln)[lid[i]] = x[i];
}
}
}
}
}
int
RestrictedMultiVectorWrapper::
restrict_comm (Teuchos::RCP<Epetra_MultiVector> input_mv)
{
using Teuchos::rcp;
input_mv_ = input_mv;
// Extract the input MV's communicator and Map.
const Epetra_MpiComm *InComm =
dynamic_cast<const Epetra_MpiComm*> (& (input_mv_->Comm ()));
const Epetra_BlockMap *InMap =
dynamic_cast<const Epetra_BlockMap*> (& (input_mv_->Map ()));
if (! InComm || ! InMap) {
return -1; // At least one dynamic cast failed.
}
if (! subcomm_is_set) {
/* Build the Split Communicators, If Needed */
int color;
if (InMap->NumMyElements()) {
color = 1;
}
else {
color = MPI_UNDEFINED;
}
const int err =
MPI_Comm_split (InComm->Comm(), color, InComm->MyPID(), &MPI_SubComm_);
if (err != MPI_SUCCESS) {
return -2;
}
}
else {
/* Sanity check user-provided subcomm - drop an error if the MPISubComm
does not include a processor with data. */
if (input_mv->MyLength() && MPI_SubComm_ == MPI_COMM_NULL) {
return -2;
}
}
/* Mark active processors */
if (MPI_SubComm_ == MPI_COMM_NULL) {
proc_is_active = false;
}
else {
proc_is_active = true;
}
if (proc_is_active) {
#ifndef EPETRA_NO_32BIT_GLOBAL_INDICES
if(InMap->GlobalIndicesInt()) {
int Nrows = InMap->NumGlobalElements ();
RestrictedComm_ = new Epetra_MpiComm (MPI_SubComm_);
// Build the restricted Maps
ResMap_ = new Epetra_BlockMap (Nrows, InMap->NumMyElements(),
InMap->MyGlobalElements(),
InMap->ElementSizeList(),
InMap->IndexBase(), *RestrictedComm_);
}
else
#endif
#ifndef EPETRA_NO_64BIT_GLOBAL_INDICES
if(InMap->GlobalIndicesLongLong()) {
long long Nrows = InMap->NumGlobalElements64 ();
RestrictedComm_ = new Epetra_MpiComm (MPI_SubComm_);
// Build the restricted Maps
ResMap_ = new Epetra_BlockMap (Nrows, InMap->NumMyElements(),
InMap->MyGlobalElements64(),
InMap->ElementSizeList(),
InMap->IndexBase64(), *RestrictedComm_);
}
else
#endif
throw "EpetraExt::RestrictedMultiVectorWrapper::restrict_comm ERROR: GlobalIndices type unknown";
// Allocate the restricted matrix
double *A;
int LDA;
input_mv_->ExtractView (&A,&LDA);
restricted_mv_ = rcp (new Epetra_MultiVector (View, *ResMap_, A, LDA,
input_mv_->NumVectors ()));
}
return 0; // Success!
}/*end restrict_comm*/
TEUCHOS_UNIT_TEST(initial_condition_control, control)
{
using Teuchos::RCP;
using Teuchos::rcp;
Teuchos::RCP<const Epetra_Comm> comm = Teuchos::rcp(new Epetra_MpiComm(MPI_COMM_WORLD));
// setup mesh
/////////////////////////////////////////////
RCP<panzer_stk_classic::STK_Interface> mesh;
{
RCP<Teuchos::ParameterList> pl = rcp(new Teuchos::ParameterList);
pl->set<int>("X Elements",2);
pl->set<int>("Y Elements",2);
pl->set<int>("X Blocks",2);
pl->set<int>("Y Blocks",1);
panzer_stk_classic::SquareQuadMeshFactory mesh_factory;
mesh_factory.setParameterList(pl);
mesh = mesh_factory.buildMesh(MPI_COMM_WORLD);
mesh->writeToExodus("test.exo");
}
RCP<const shards::CellTopology> ct = mesh->getCellTopology("eblock-0_0");
panzer::CellData cellData(4,ct);
RCP<panzer::IntegrationRule> int_rule = rcp(new panzer::IntegrationRule(2,cellData));
ICFieldDescriptor densDesc;
densDesc.fieldName = "DENSITY";
densDesc.basisName = "Const";
densDesc.basisOrder = 0;
ICFieldDescriptor condDesc;
condDesc.fieldName = "CONDUCTIVITY";
condDesc.basisName = "HGrad";
condDesc.basisOrder = 1;
RCP<panzer::PureBasis> const_basis = rcp(new panzer::PureBasis(densDesc.basisName,densDesc.basisOrder,cellData));
RCP<panzer::PureBasis> hgrad_basis = rcp(new panzer::PureBasis(condDesc.basisName,condDesc.basisOrder,cellData));
RCP<const panzer::FieldPattern> constFP = rcp(new panzer::Intrepid2FieldPattern(const_basis->getIntrepid2Basis()));
RCP<const panzer::FieldPattern> hgradFP = rcp(new panzer::Intrepid2FieldPattern(hgrad_basis->getIntrepid2Basis()));
// setup DOF manager
/////////////////////////////////////////////
RCP<panzer::ConnManager<int,int> > conn_manager
= Teuchos::rcp(new panzer_stk_classic::STKConnManager<int>(mesh));
RCP<panzer::DOFManager<int,int> > dofManager
= rcp(new panzer::DOFManager<int,int>(conn_manager,MPI_COMM_WORLD));
dofManager->addField(densDesc.fieldName, constFP);
dofManager->addField(condDesc.fieldName, hgradFP);
dofManager->buildGlobalUnknowns();
Teuchos::RCP<panzer::EpetraLinearObjFactory<panzer::Traits,int> > elof
= Teuchos::rcp(new panzer::EpetraLinearObjFactory<panzer::Traits,int>(comm.getConst(),dofManager));
Teuchos::RCP<panzer::LinearObjFactory<panzer::Traits> > lof = elof;
// setup worksets
/////////////////////////////////////////////
std::map<std::string,panzer::WorksetNeeds> needs;
needs["eblock-0_0"].cellData = cellData;
needs["eblock-0_0"].int_rules.push_back(int_rule);
needs["eblock-0_0"].bases = { const_basis, hgrad_basis};
needs["eblock-0_0"].rep_field_name = { densDesc.fieldName, condDesc.fieldName};
needs["eblock-1_0"].cellData = cellData;
needs["eblock-1_0"].int_rules.push_back(int_rule);
needs["eblock-1_0"].bases = { const_basis, hgrad_basis};
needs["eblock-1_0"].rep_field_name = { densDesc.fieldName, condDesc.fieldName};
Teuchos::RCP<panzer_stk_classic::WorksetFactory> wkstFactory
= Teuchos::rcp(new panzer_stk_classic::WorksetFactory(mesh)); // build STK workset factory
Teuchos::RCP<panzer::WorksetContainer> wkstContainer // attach it to a workset container (uses lazy evaluation)
= Teuchos::rcp(new panzer::WorksetContainer(wkstFactory,needs));
// setup field manager builder
/////////////////////////////////////////////
// Add in the application specific closure model factory
panzer::ClosureModelFactory_TemplateManager<panzer::Traits> cm_factory;
user_app::STKModelFactory_TemplateBuilder cm_builder;
cm_factory.buildObjects(cm_builder);
Teuchos::ParameterList user_data("User Data");
Teuchos::ParameterList ic_closure_models("Initial Conditions");
ic_closure_models.sublist("eblock-0_0").sublist(densDesc.fieldName).set<double>("Value",3.0);
ic_closure_models.sublist("eblock-0_0").sublist(condDesc.fieldName).set<double>("Value",9.0);
ic_closure_models.sublist("eblock-1_0").sublist(densDesc.fieldName).set<double>("Value",3.0);
ic_closure_models.sublist("eblock-1_0").sublist(condDesc.fieldName).set<double>("Value",9.0);
std::map<std::string,Teuchos::RCP<const shards::CellTopology> > block_ids_to_cell_topo;
block_ids_to_cell_topo["eblock-0_0"] = mesh->getCellTopology("eblock-0_0");
block_ids_to_cell_topo["eblock-1_0"] = mesh->getCellTopology("eblock-1_0");
std::map<std::string,std::vector<ICFieldDescriptor> > block_ids_to_fields;
block_ids_to_fields["eblock-0_0"] = {densDesc,condDesc};
block_ids_to_fields["eblock-1_0"] = {densDesc,condDesc};
int workset_size = 4;
Teuchos::RCP<panzer::LinearObjContainer> loc = lof->buildLinearObjContainer();
lof->initializeContainer(panzer::LinearObjContainer::X,*loc);
Teuchos::RCP<panzer::EpetraLinearObjContainer> eloc = Teuchos::rcp_dynamic_cast<EpetraLinearObjContainer>(loc);
Teuchos::RCP<Thyra::VectorBase<double> > vec = eloc->get_x_th();
// this is the Function under test
panzer::setupControlInitialCondition(block_ids_to_cell_topo,
block_ids_to_fields,
*wkstContainer,
*lof,cm_factory,ic_closure_models,user_data,
workset_size,
0.0, // t0
vec);
Teuchos::RCP<Epetra_Vector> x = eloc->get_x();
out << x->GlobalLength() << " " << x->MyLength() << std::endl;
for (int i=0; i < x->MyLength(); ++i) {
double v = (*x)[i];
TEST_ASSERT(v==3.0 || v==9.0);
}
}
int main(int narg, char *arg[])
{
using std::cout;
#ifdef EPETRA_MPI
// Initialize MPI
MPI_Init(&narg,&arg);
Epetra_MpiComm Comm( MPI_COMM_WORLD );
#else
Epetra_SerialComm Comm;
#endif
int MyPID = Comm.MyPID();
bool verbose = true;
int verbosity = 1;
bool testEpetra64 = true;
// Matrix properties
bool isHermitian = true;
// Multivector properties
std::string initvec = "random";
// Eigenvalue properties
std::string which = "SR";
std::string method = "LOBPCG";
std::string precond = "none";
std::string ortho = "SVQB";
bool lock = true;
bool relconvtol = false;
bool rellocktol = false;
int nev = 5;
// Block-Arnoldi properties
int blockSize = -1;
int numblocks = -1;
int maxrestarts = -1;
int maxiterations = -1;
int extrablocks = 0;
int gensize = 25; // Needs to be long long to test with > INT_MAX rows
double tol = 1.0e-5;
// Echo the command line
if (MyPID == 0) {
for (int i = 0; i < narg; i++)
cout << arg[i] << " ";
cout << endl;
}
// Command-line processing
Teuchos::CommandLineProcessor cmdp(false,true);
cmdp.setOption("Epetra64", "no-Epetra64", &testEpetra64,
"Force code to use Epetra64, even if the problem size does "
"not require it. (Epetra64 will be used automatically for "
"sufficiently large problems, or not used if Epetra does not have built in support.)");
cmdp.setOption("gen",&gensize,
"Generate a simple Laplacian matrix of size n.");
cmdp.setOption("verbosity", &verbosity, "0=quiet, 1=low, 2=medium, 3=high.");
cmdp.setOption("method",&method,
"Solver method to use: LOBPCG, BD, BKS or IRTR.");
cmdp.setOption("nev",&nev,"Number of eigenvalues to find.");
cmdp.setOption("which",&which,"Targetted eigenvalues (SM,LM,SR,or LR).");
cmdp.setOption("tol",&tol,"Solver convergence tolerance.");
cmdp.setOption("blocksize",&blockSize,"Block size to use in solver.");
cmdp.setOption("numblocks",&numblocks,"Number of blocks to allocate.");
cmdp.setOption("extrablocks",&extrablocks,
"Number of extra NEV blocks to allocate in BKS.");
cmdp.setOption("maxrestarts",&maxrestarts,
"Maximum number of restarts in BKS or BD.");
cmdp.setOption("maxiterations",&maxiterations,
"Maximum number of iterations in LOBPCG.");
cmdp.setOption("lock","no-lock",&lock,
"Use Locking parameter (deflate for converged eigenvalues)");
cmdp.setOption("initvec", &initvec,
"Initial vectors (random, unit, zero, random2)");
cmdp.setOption("ortho", &ortho,
"Orthogonalization method (DGKS, SVQB, TSQR).");
cmdp.setOption("relative-convergence-tol","no-relative-convergence-tol",
&relconvtol,
"Use Relative convergence tolerance "
"(normalized by eigenvalue)");
cmdp.setOption("relative-lock-tol","no-relative-lock-tol",&rellocktol,
"Use Relative locking tolerance (normalized by eigenvalue)");
if (cmdp.parse(narg,arg)!=Teuchos::CommandLineProcessor::PARSE_SUCCESSFUL) {
FINALIZE;
return -1;
}
// Print the most essential options (not in the MyPL parameters later)
verbose = (verbosity>0);
if (verbose && MyPID==0){
cout << "verbosity = " << verbosity << endl;
cout << "method = " << method << endl;
cout << "initvec = " << initvec << endl;
cout << "nev = " << nev << endl;
}
// We need blockSize to be set so we can allocate memory with it.
// If it wasn't set on the command line, set it to the Anasazi defaults here.
// Defaults are those given in the documentation.
if (blockSize < 0)
if (method == "BKS")
blockSize = 1;
else // other methods: LOBPCG, BD, IRTR
blockSize = nev;
// Make sure Epetra was built with 64-bit global indices enabled.
#ifdef EPETRA_NO_64BIT_GLOBAL_INDICES
if (testEpetra64)
testEpetra64 = false;
#endif
Epetra_CrsMatrix *K = NULL;
// Read matrix from file or generate a matrix
if ((gensize > 0 && testEpetra64)) {
// Generate the matrix using long long for global indices
build_simple_matrix<long long>(Comm, K, (long long)gensize, true, verbose);
}
else if (gensize) {
// Generate the matrix using int for global indices
build_simple_matrix<int>(Comm, K, gensize, false, verbose);
}
else {
printf("YOU SHOULDN'T BE HERE \n");
exit(-1);
}
if (verbose && (K->NumGlobalRows64() < TINYMATRIX)) {
if (MyPID == 0) cout << "Input matrix: " << endl;
K->Print(cout);
}
Teuchos::RCP<Epetra_CrsMatrix> rcpK = Teuchos::rcp( K );
// Set Anasazi verbosity level
if (MyPID == 0) cout << "Setting up the problem..." << endl;
int anasazi_verbosity = Anasazi::Errors + Anasazi::Warnings;
if (verbosity >= 1) // low
anasazi_verbosity += Anasazi::FinalSummary + Anasazi::TimingDetails;
if (verbosity >= 2) // medium
anasazi_verbosity += Anasazi::IterationDetails;
if (verbosity >= 3) // high
anasazi_verbosity += Anasazi::StatusTestDetails
+ Anasazi::OrthoDetails
+ Anasazi::Debug;
// Create parameter list to pass into solver
Teuchos::ParameterList MyPL;
MyPL.set("Verbosity", anasazi_verbosity);
MyPL.set("Which", which);
MyPL.set("Convergence Tolerance", tol);
MyPL.set("Relative Convergence Tolerance", relconvtol);
MyPL.set("Orthogonalization", ortho);
// For the following, use Anasazi's defaults unless explicitly specified.
if (numblocks > 0) MyPL.set( "Num Blocks", numblocks);
if (maxrestarts > 0) MyPL.set( "Maximum Restarts", maxrestarts);
if (maxiterations > 0) MyPL.set( "Maximum Iterations", maxiterations);
if (blockSize > 0) MyPL.set( "Block Size", blockSize );
typedef Epetra_MultiVector MV;
typedef Epetra_Operator OP;
typedef Anasazi::MultiVecTraits<double, MV> MVT;
typedef Anasazi::OperatorTraits<double, MV, OP> OPT;
// Create the eigenproblem to be solved.
// Dummy initial vectors - will be set later.
Teuchos::RCP<Epetra_MultiVector> ivec =
Teuchos::rcp(new Epetra_MultiVector(K->Map(), blockSize));
Teuchos::RCP<Anasazi::BasicEigenproblem<double, MV, OP> > MyProblem;
MyProblem =
Teuchos::rcp(new Anasazi::BasicEigenproblem<double, MV, OP>(rcpK, ivec) );
// Inform the eigenproblem whether K is Hermitian
MyProblem->setHermitian(isHermitian);
// Set the number of eigenvalues requested
MyProblem->setNEV(nev);
// Loop to solve the same eigenproblem numtrial times (different initial vectors)
int numfailed = 0;
int iter = 0;
double solvetime = 0;
// Set random seed to have consistent initial vectors between
// experiments. Different seed in each loop iteration.
ivec->SetSeed(2*(MyPID) +1); // Odd seed
// Set up initial vectors
// Using random values as the initial guess.
if (initvec == "random"){
MVT::MvRandom(*ivec);
}
else if (initvec == "zero"){
// All zero initial vector should be essentially the same,
// but appears slightly worse in practice.
ivec->PutScalar(0.);
}
else if (initvec == "unit"){
// Orthogonal unit initial vectors.
ivec->PutScalar(0.);
for (int i = 0; i < blockSize; i++)
ivec->ReplaceGlobalValue(i,i,1.);
}
else if (initvec == "random2"){
// Partially random but orthogonal (0,1) initial vectors.
// ivec(i,*) is zero in all but one column (for each i)
// Inefficient implementation but this is only done once...
double rowmax;
int col;
ivec->Random();
for (int i = 0; i < ivec->MyLength(); i++){
rowmax = -1;
col = -1;
for (int j = 0; j < blockSize; j++){
// Make ivec(i,j) = 1 for largest random value in row i
if ((*ivec)[j][i] > rowmax){
rowmax = (*ivec)[j][i];
col = j;
}
ivec->ReplaceMyValue(i,j,0.);
}
ivec->ReplaceMyValue(i,col,1.);
}
}
else
cout << "ERROR: Unknown value for initial vectors." << endl;
if (verbose && (ivec->GlobalLength64() < TINYMATRIX))
ivec->Print(std::cout);
// Inform the eigenproblem that you are finished passing it information
bool boolret = MyProblem->setProblem();
if (boolret != true) {
if (verbose && MyPID == 0) {
cout << "Anasazi::BasicEigenproblem::setProblem() returned with error."
<< endl;
}
FINALIZE;
return -1;
}
Teuchos::RCP<Anasazi::SolverManager<double, MV, OP> > MySolverMgr;
if (method == "BKS") {
// Initialize the Block Arnoldi solver
MyPL.set("Extra NEV Blocks", extrablocks);
MySolverMgr = Teuchos::rcp( new Anasazi::BlockKrylovSchurSolMgr<double, MV, OP>(MyProblem,MyPL) );
}
else if (method == "BD") {
// Initialize the Block Davidson solver
MyPL.set("Use Locking", lock);
MyPL.set("Relative Locking Tolerance", rellocktol);
MySolverMgr = Teuchos::rcp( new Anasazi::BlockDavidsonSolMgr<double, MV, OP>(MyProblem, MyPL) );
}
else if (method == "LOBPCG") {
// Initialize the LOBPCG solver
MyPL.set("Use Locking", lock);
MyPL.set("Relative Locking Tolerance", rellocktol);
MySolverMgr = Teuchos::rcp( new Anasazi::LOBPCGSolMgr<double, MV, OP>(MyProblem, MyPL) );
}
else if (method == "IRTR") {
// Initialize the IRTR solver
MySolverMgr = Teuchos::rcp( new Anasazi::RTRSolMgr<double, MV, OP>(MyProblem, MyPL) );
}
else
cout << "Unknown solver method!" << endl;
if (verbose && MyPID==0) MyPL.print(cout);
// Solve the problem to the specified tolerances or length
if (MyPID == 0) cout << "Beginning the " << method << " solve..." << endl;
Anasazi::ReturnType returnCode = MySolverMgr->solve();
if (returnCode != Anasazi::Converged && MyPID==0) {
++numfailed;
cout << "Anasazi::SolverManager::solve() returned unconverged." << endl;
}
iter = MySolverMgr->getNumIters();
solvetime = (MySolverMgr->getTimers()[0])->totalElapsedTime();
if (MyPID == 0) {
cout << "Iterations in this solve: " << iter << endl;
cout << "Solve complete; beginning post-processing..."<< endl;
}
// Get the eigenvalues and eigenvectors from the eigenproblem
Anasazi::Eigensolution<double,MV> sol = MyProblem->getSolution();
std::vector<Anasazi::Value<double> > evals = sol.Evals;
Teuchos::RCP<MV> evecs = sol.Evecs;
std::vector<int> index = sol.index;
int numev = sol.numVecs;
// Compute residuals.
if (numev > 0) {
Teuchos::LAPACK<int,double> lapack;
std::vector<double> normR(numev);
if (MyProblem->isHermitian()) {
// Get storage
Epetra_MultiVector Kevecs(K->Map(),numev);
Teuchos::RCP<Epetra_MultiVector> Mevecs;
Teuchos::SerialDenseMatrix<int,double> B(numev,numev);
B.putScalar(0.0);
for (int i=0; i<numev; i++) {B(i,i) = evals[i].realpart;}
// Compute A*evecs
OPT::Apply( *rcpK, *evecs, Kevecs );
Mevecs = evecs;
// Compute A*evecs - lambda*evecs and its norm
MVT::MvTimesMatAddMv( -1.0, *Mevecs, B, 1.0, Kevecs );
MVT::MvNorm( Kevecs, normR );
// Scale the norms by the eigenvalue if relative convergence tol was used
if (relconvtol) {
for (int i=0; i<numev; i++)
normR[i] /= Teuchos::ScalarTraits<double>::magnitude(evals[i].realpart);
}
} else {
printf("The problem isn't non-Hermitian; sorry.\n");
exit(-1);
}
if (verbose && MyPID==0) {
cout.setf(std::ios_base::right, std::ios_base::adjustfield);
cout<<endl<< "Actual Results"<<endl;
if (MyProblem->isHermitian()) {
cout<< std::setw(16) << "Eigenvalue "
<< std::setw(20) << "Direct Residual"
<< (relconvtol?" (normalized by eigenvalue)":" (no normalization)")
<< endl;
cout<<"--------------------------------------------------------"<<endl;
for (int i=0; i<numev; i++) {
cout<< "EV" << i << std::setw(16) << evals[i].realpart
<< std::setw(20) << normR[i] << endl;
}
cout<<"--------------------------------------------------------"<<endl;
}
else {
cout<< std::setw(16) << "Real Part"
<< std::setw(16) << "Imag Part"
<< std::setw(20) << "Direct Residual"<< endl;
cout<<"--------------------------------------------------------"<<endl;
for (int i=0; i<numev; i++) {
cout<< std::setw(16) << evals[i].realpart
<< std::setw(16) << evals[i].imagpart
<< std::setw(20) << normR[i] << endl;
}
cout<<"--------------------------------------------------------"<<endl;
}
}
}
// Summarize iteration counts and solve time
if (MyPID == 0) {
cout << endl;
cout << "DRIVER SUMMARY" << endl;
cout << "Failed to converge: " << numfailed << endl;
cout << "Solve time: " << solvetime << endl;
}
FINALIZE;
if (numfailed) {
if (MyPID == 0) {
cout << "End Result: TEST FAILED" << endl;
}
return -1;
}
//
// Default return value
//
if (MyPID == 0) {
cout << "End Result: TEST PASSED" << endl;
}
return 0;
}
TEUCHOS_UNIT_TEST(PdQuickGridDiscretization_MPI_np2, SimpleTensorProductMeshTest) {
Teuchos::RCP<Epetra_Comm> comm;
comm = rcp(new Epetra_MpiComm(MPI_COMM_WORLD));
int numProcs = comm->NumProc();
int rank = comm->MyPID();
TEST_COMPARE(numProcs, ==, 2);
if(numProcs != 2){
std::cerr << "Unit test runtime ERROR: utPeridigm_PdQuickGridDiscretization_MPI_np2 only makes sense on 2 processors" << std::endl;
return;
}
RCP<ParameterList> discParams = rcp(new ParameterList);
// create a 2x2x2 discretization
// specify a spherical neighbor search with the horizon a tad longer than the mesh spacing
discParams->set("Type", "PdQuickGrid");
discParams->set("NeighborhoodType", "Spherical");
ParameterList& quickGridParams = discParams->sublist("TensorProduct3DMeshGenerator");
quickGridParams.set("Type", "PdQuickGrid");
quickGridParams.set("X Origin", 0.0);
quickGridParams.set("Y Origin", 0.0);
quickGridParams.set("Z Origin", 0.0);
quickGridParams.set("X Length", 1.0);
quickGridParams.set("Y Length", 1.0);
quickGridParams.set("Z Length", 1.0);
quickGridParams.set("Number Points X", 2);
quickGridParams.set("Number Points Y", 2);
quickGridParams.set("Number Points Z", 2);
// initialize the horizon manager and set the horizon to 0.501
ParameterList blockParameterList;
ParameterList& blockParams = blockParameterList.sublist("My Block");
blockParams.set("Block Names", "block_1");
blockParams.set("Horizon", 0.501);
PeridigmNS::HorizonManager::self().loadHorizonInformationFromBlockParameters(blockParameterList);
// create the discretization
RCP<PdQuickGridDiscretization> discretization =
rcp(new PdQuickGridDiscretization(comm, discParams));
// sanity check, calling with a dimension other than 1 or 3 should throw an exception
TEST_THROW(discretization->getGlobalOwnedMap(0), Teuchos::Exceptions::InvalidParameter);
TEST_THROW(discretization->getGlobalOwnedMap(2), Teuchos::Exceptions::InvalidParameter);
TEST_THROW(discretization->getGlobalOwnedMap(4), Teuchos::Exceptions::InvalidParameter);
// basic checks on the 1d map
Teuchos::RCP<const Epetra_BlockMap> map = discretization->getGlobalOwnedMap(1);
TEST_ASSERT(map->NumGlobalElements() == 8);
TEST_ASSERT(map->NumMyElements() == 4);
TEST_ASSERT(map->ElementSize() == 1);
TEST_ASSERT(map->IndexBase() == 0);
TEST_ASSERT(map->UniqueGIDs() == true);
int* myGlobalElements = map->MyGlobalElements();
if(rank == 0){
TEST_ASSERT(myGlobalElements[0] == 0);
TEST_ASSERT(myGlobalElements[1] == 2);
TEST_ASSERT(myGlobalElements[2] == 4);
TEST_ASSERT(myGlobalElements[3] == 6);
}
if(rank == 1){
TEST_ASSERT(myGlobalElements[0] == 5);
TEST_ASSERT(myGlobalElements[1] == 7);
TEST_ASSERT(myGlobalElements[2] == 1);
TEST_ASSERT(myGlobalElements[3] == 3);
}
// check the 1d overlap map
// for this simple discretization, everything should be ghosted on both processors
Teuchos::RCP<const Epetra_BlockMap> overlapMap = discretization->getGlobalOverlapMap(1);
TEST_ASSERT(overlapMap->NumGlobalElements() == 16);
TEST_ASSERT(overlapMap->NumMyElements() == 8);
TEST_ASSERT(overlapMap->ElementSize() == 1);
TEST_ASSERT(overlapMap->IndexBase() == 0);
TEST_ASSERT(overlapMap->UniqueGIDs() == false);
myGlobalElements = overlapMap->MyGlobalElements();
if(rank == 0){
TEST_ASSERT(myGlobalElements[0] == 0);
TEST_ASSERT(myGlobalElements[1] == 2);
TEST_ASSERT(myGlobalElements[2] == 4);
TEST_ASSERT(myGlobalElements[3] == 6);
TEST_ASSERT(myGlobalElements[4] == 1);
TEST_ASSERT(myGlobalElements[5] == 3);
TEST_ASSERT(myGlobalElements[6] == 5);
TEST_ASSERT(myGlobalElements[7] == 7);
}
if(rank == 1){
TEST_ASSERT(myGlobalElements[0] == 5);
TEST_ASSERT(myGlobalElements[1] == 7);
TEST_ASSERT(myGlobalElements[2] == 1);
TEST_ASSERT(myGlobalElements[3] == 3);
TEST_ASSERT(myGlobalElements[4] == 0);
TEST_ASSERT(myGlobalElements[5] == 2);
TEST_ASSERT(myGlobalElements[6] == 4);
TEST_ASSERT(myGlobalElements[7] == 6);
}
// same checks for 3d map
map = discretization->getGlobalOwnedMap(3);
TEST_ASSERT(map->NumGlobalElements() == 8);
TEST_ASSERT(map->NumMyElements() == 4);
TEST_ASSERT(map->ElementSize() == 3);
TEST_ASSERT(map->IndexBase() == 0);
TEST_ASSERT(map->UniqueGIDs() == true);
myGlobalElements = map->MyGlobalElements();
if(rank == 0){
TEST_ASSERT(myGlobalElements[0] == 0);
TEST_ASSERT(myGlobalElements[1] == 2);
TEST_ASSERT(myGlobalElements[2] == 4);
TEST_ASSERT(myGlobalElements[3] == 6);
}
if(rank == 1){
TEST_ASSERT(myGlobalElements[0] == 5);
TEST_ASSERT(myGlobalElements[1] == 7);
TEST_ASSERT(myGlobalElements[2] == 1);
TEST_ASSERT(myGlobalElements[3] == 3);
}
// check the 3d overlap map
// for this simple discretization, everything should be ghosted on both processors
overlapMap = discretization->getGlobalOverlapMap(3);
TEST_ASSERT(overlapMap->NumGlobalElements() == 16);
TEST_ASSERT(overlapMap->NumMyElements() == 8);
TEST_ASSERT(overlapMap->ElementSize() == 3);
TEST_ASSERT(overlapMap->IndexBase() == 0);
TEST_ASSERT(overlapMap->UniqueGIDs() == false);
myGlobalElements = overlapMap->MyGlobalElements();
if(rank == 0){
TEST_ASSERT(myGlobalElements[0] == 0);
TEST_ASSERT(myGlobalElements[1] == 2);
TEST_ASSERT(myGlobalElements[2] == 4);
TEST_ASSERT(myGlobalElements[3] == 6);
TEST_ASSERT(myGlobalElements[4] == 1);
TEST_ASSERT(myGlobalElements[5] == 3);
TEST_ASSERT(myGlobalElements[6] == 5);
TEST_ASSERT(myGlobalElements[7] == 7);
}
if(rank == 1){
TEST_ASSERT(myGlobalElements[0] == 5);
TEST_ASSERT(myGlobalElements[1] == 7);
TEST_ASSERT(myGlobalElements[2] == 1);
TEST_ASSERT(myGlobalElements[3] == 3);
TEST_ASSERT(myGlobalElements[4] == 0);
TEST_ASSERT(myGlobalElements[5] == 2);
TEST_ASSERT(myGlobalElements[6] == 4);
TEST_ASSERT(myGlobalElements[7] == 6);
}
// check the bond map
// the horizon was chosen such that each point should have three neighbors
// note that if the NeighborhoodType parameter is not set to Spherical, this will fail
Teuchos::RCP<const Epetra_BlockMap> bondMap = discretization->getGlobalBondMap();
TEST_ASSERT(bondMap->NumGlobalElements() == 8);
TEST_ASSERT(bondMap->NumMyElements() == 4);
TEST_ASSERT(bondMap->IndexBase() == 0);
TEST_ASSERT(bondMap->UniqueGIDs() == true);
myGlobalElements = bondMap->MyGlobalElements();
if(rank == 0){
TEST_ASSERT(myGlobalElements[0] == 0);
TEST_ASSERT(myGlobalElements[1] == 2);
TEST_ASSERT(myGlobalElements[2] == 4);
TEST_ASSERT(myGlobalElements[3] == 6);
}
if(rank == 1){
TEST_ASSERT(myGlobalElements[0] == 5);
TEST_ASSERT(myGlobalElements[1] == 7);
TEST_ASSERT(myGlobalElements[2] == 1);
TEST_ASSERT(myGlobalElements[3] == 3);
}
TEST_ASSERT(discretization->getNumBonds() == 4*3);
// check the initial positions
// all three coordinates are contained in a single vector
Teuchos::RCP<Epetra_Vector> initialX = discretization->getInitialX();
TEST_ASSERT(initialX->MyLength() == 4*3);
TEST_ASSERT(initialX->GlobalLength() == 8*3);
if(rank == 0){
TEST_FLOATING_EQUALITY((*initialX)[0], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[1], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[2], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[3], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[4], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[5], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[6], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[7], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[8], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[9], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[10], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[11], 0.75, 1.0e-16);
}
if(rank == 1){
TEST_FLOATING_EQUALITY((*initialX)[0], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[1], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[2], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[3], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[4], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[5], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[6], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[7], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[8], 0.25, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[9], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[10], 0.75, 1.0e-16);
TEST_FLOATING_EQUALITY((*initialX)[11], 0.25, 1.0e-16);
}
// check cell volumes
Teuchos::RCP<Epetra_Vector> volume = discretization->getCellVolume();
TEST_ASSERT(volume->MyLength() == 4);
TEST_ASSERT(volume->GlobalLength() == 8);
for(int i=0 ; i<volume->MyLength() ; ++i)
TEST_FLOATING_EQUALITY((*volume)[i], 0.125, 1.0e-16);
// check the neighbor lists
Teuchos::RCP<PeridigmNS::NeighborhoodData> neighborhoodData = discretization->getNeighborhoodData();
TEST_ASSERT(neighborhoodData->NumOwnedPoints() == 4);
int* ownedIds = neighborhoodData->OwnedIDs();
TEST_ASSERT(ownedIds[0] == 0);
TEST_ASSERT(ownedIds[1] == 1);
TEST_ASSERT(ownedIds[2] == 2);
TEST_ASSERT(ownedIds[3] == 3);
TEST_ASSERT(neighborhoodData->NeighborhoodListSize() == 16);
int* neighborhood = neighborhoodData->NeighborhoodList();
int* neighborhoodPtr = neighborhoodData->NeighborhoodPtr();
// remember, these are local IDs on each processor,
// which includes both owned and ghost nodes (confusing!)
if(rank == 0){
TEST_ASSERT(neighborhoodPtr[0] == 0);
TEST_ASSERT(neighborhood[0] == 3);
TEST_ASSERT(neighborhood[1] == 4);
TEST_ASSERT(neighborhood[2] == 1);
TEST_ASSERT(neighborhood[3] == 2);
TEST_ASSERT(neighborhoodPtr[1] == 4);
TEST_ASSERT(neighborhood[4] == 3);
TEST_ASSERT(neighborhood[5] == 0);
TEST_ASSERT(neighborhood[6] == 5);
TEST_ASSERT(neighborhood[7] == 3);
TEST_ASSERT(neighborhoodPtr[2] == 8);
TEST_ASSERT(neighborhood[8] == 3);
TEST_ASSERT(neighborhood[9] == 0);
TEST_ASSERT(neighborhood[10] == 6);
TEST_ASSERT(neighborhood[11] == 3);
TEST_ASSERT(neighborhoodPtr[3] == 12);
TEST_ASSERT(neighborhood[12] == 3);
TEST_ASSERT(neighborhood[13] == 1);
TEST_ASSERT(neighborhood[14] == 2);
TEST_ASSERT(neighborhood[15] == 7);
}
if(rank == 1){
TEST_ASSERT(neighborhoodPtr[0] == 0);
TEST_ASSERT(neighborhood[0] == 3);
TEST_ASSERT(neighborhood[1] == 2);
TEST_ASSERT(neighborhood[2] == 6);
TEST_ASSERT(neighborhood[3] == 1);
TEST_ASSERT(neighborhoodPtr[1] == 4);
TEST_ASSERT(neighborhood[4] == 3);
TEST_ASSERT(neighborhood[5] == 3);
TEST_ASSERT(neighborhood[6] == 0);
TEST_ASSERT(neighborhood[7] == 7);
TEST_ASSERT(neighborhoodPtr[2] == 8);
TEST_ASSERT(neighborhood[8] == 3);
TEST_ASSERT(neighborhood[9] == 4);
TEST_ASSERT(neighborhood[10] == 3);
TEST_ASSERT(neighborhood[11] == 0);
TEST_ASSERT(neighborhoodPtr[3] == 12);
TEST_ASSERT(neighborhood[12] == 3);
TEST_ASSERT(neighborhood[13] == 2);
TEST_ASSERT(neighborhood[14] == 5);
TEST_ASSERT(neighborhood[15] == 1);
}
}
TEUCHOS_UNIT_TEST(initial_condition_builder2, block_structure)
{
using Teuchos::RCP;
panzer_stk::STK_ExodusReaderFactory mesh_factory;
Teuchos::RCP<user_app::MyFactory> eqset_factory = Teuchos::rcp(new user_app::MyFactory);
user_app::BCFactory bc_factory;
const std::size_t workset_size = 20;
panzer::FieldManagerBuilder fmb;
// setup mesh
/////////////////////////////////////////////
RCP<panzer_stk::STK_Interface> mesh;
{
RCP<Teuchos::ParameterList> pl = rcp(new Teuchos::ParameterList);
pl->set("File Name","block-decomp.exo");
mesh_factory.setParameterList(pl);
mesh = mesh_factory.buildMesh(MPI_COMM_WORLD);
mesh->writeToExodus("test.exo");
}
// setup physic blocks
/////////////////////////////////////////////
Teuchos::RCP<Teuchos::ParameterList> ipb = Teuchos::parameterList("Physics Blocks");
std::vector<panzer::BC> bcs;
std::vector<Teuchos::RCP<panzer::PhysicsBlock> > physics_blocks;
{
testInitialzation_blockStructure(ipb, bcs);
std::map<std::string,std::string> block_ids_to_physics_ids;
block_ids_to_physics_ids["eblock-0_0"] = "PB A";
block_ids_to_physics_ids["eblock-1_0"] = "PB B";
std::map<std::string,Teuchos::RCP<const shards::CellTopology> > block_ids_to_cell_topo;
block_ids_to_cell_topo["eblock-0_0"] = mesh->getCellTopology("eblock-0_0");
block_ids_to_cell_topo["eblock-1_0"] = mesh->getCellTopology("eblock-1_0");
Teuchos::RCP<panzer::GlobalData> gd = panzer::createGlobalData();
int default_integration_order = 1;
panzer::buildPhysicsBlocks(block_ids_to_physics_ids,
block_ids_to_cell_topo,
ipb,
default_integration_order,
workset_size,
eqset_factory,
gd,
false,
physics_blocks);
}
// setup worksets
/////////////////////////////////////////////
Teuchos::RCP<panzer_stk::WorksetFactory> wkstFactory
= Teuchos::rcp(new panzer_stk::WorksetFactory(mesh)); // build STK workset factory
Teuchos::RCP<panzer::WorksetContainer> wkstContainer // attach it to a workset container (uses lazy evaluation)
= Teuchos::rcp(new panzer::WorksetContainer(wkstFactory,physics_blocks,workset_size));
// get vector of element blocks
std::vector<std::string> elementBlocks;
mesh->getElementBlockNames(elementBlocks);
// build volume worksets from container
std::map<panzer::BC,Teuchos::RCP<std::map<unsigned,panzer::Workset> >,panzer::LessBC> bc_worksets;
panzer::getSideWorksetsFromContainer(*wkstContainer,bcs,bc_worksets);
// setup DOF manager
/////////////////////////////////////////////
const Teuchos::RCP<panzer::ConnManager<int,int> > conn_manager
= Teuchos::rcp(new panzer_stk::STKConnManager<int>(mesh));
Teuchos::RCP<const panzer::UniqueGlobalIndexerFactory<int,int,int,int> > indexerFactory
= Teuchos::rcp(new panzer::DOFManagerFactory<int,int>);
const Teuchos::RCP<panzer::UniqueGlobalIndexer<int,int> > dofManager
= indexerFactory->buildUniqueGlobalIndexer(Teuchos::opaqueWrapper(MPI_COMM_WORLD),physics_blocks,conn_manager);
// and linear object factory
Teuchos::RCP<const Teuchos::MpiComm<int> > tComm = Teuchos::rcp(new Teuchos::MpiComm<int>(MPI_COMM_WORLD));
Teuchos::RCP<panzer::EpetraLinearObjFactory<panzer::Traits,int> > elof
= Teuchos::rcp(new panzer::EpetraLinearObjFactory<panzer::Traits,int>(tComm.getConst(),dofManager));
Teuchos::RCP<panzer::LinearObjFactory<panzer::Traits> > lof = elof;
// setup field manager builder
/////////////////////////////////////////////
// Add in the application specific closure model factory
panzer::ClosureModelFactory_TemplateManager<panzer::Traits> cm_factory;
user_app::STKModelFactory_TemplateBuilder cm_builder;
cm_factory.buildObjects(cm_builder);
Teuchos::ParameterList closure_models("Closure Models");
closure_models.sublist("solid").sublist("SOURCE_TEMPERATURE").set<double>("Value",1.0);
closure_models.sublist("solid").sublist("SOURCE_ELECTRON_TEMPERATURE").set<double>("Value",1.0);
closure_models.sublist("ion solid").sublist("SOURCE_ION_TEMPERATURE").set<double>("Value",1.0);
Teuchos::ParameterList user_data("User Data");
user_data.sublist("Panzer Data").set("Mesh", mesh);
user_data.sublist("Panzer Data").set("DOF Manager", dofManager);
user_data.sublist("Panzer Data").set("Linear Object Factory", lof);
fmb.setWorksetContainer(wkstContainer);
fmb.setupVolumeFieldManagers(physics_blocks,cm_factory,closure_models,*elof,user_data);
fmb.setupBCFieldManagers(bcs,physics_blocks,*eqset_factory,cm_factory,bc_factory,closure_models,*elof,user_data);
Teuchos::ParameterList ic_closure_models("Initial Conditions");
ic_closure_models.sublist("eblock-0_0").sublist("TEMPERATURE").set<double>("Value",3.0);
ic_closure_models.sublist("eblock-0_0").sublist("ELECTRON_TEMPERATURE").set<double>("Value",3.0);
ic_closure_models.sublist("eblock-1_0").sublist("TEMPERATURE").set<double>("Value",3.0);
ic_closure_models.sublist("eblock-1_0").sublist("ION_TEMPERATURE").set<double>("Value",3.0);
std::map<std::string, Teuchos::RCP< PHX::FieldManager<panzer::Traits> > > phx_ic_field_managers;
panzer::setupInitialConditionFieldManagers(*wkstContainer,
physics_blocks,
cm_factory,
ic_closure_models,
*elof,
user_data,
true,
"initial_condition_test",
phx_ic_field_managers);
Teuchos::RCP<panzer::LinearObjContainer> loc = elof->buildLinearObjContainer();
elof->initializeContainer(panzer::EpetraLinearObjContainer::X,*loc);
Teuchos::RCP<panzer::EpetraLinearObjContainer> eloc = Teuchos::rcp_dynamic_cast<EpetraLinearObjContainer>(loc);
eloc->get_x()->PutScalar(0.0);
panzer::evaluateInitialCondition(*wkstContainer, phx_ic_field_managers, loc, *elof, 0.0);
Teuchos::RCP<Epetra_Vector> x = eloc->get_x();
out << x->GlobalLength() << " " << x->MyLength() << std::endl;
for (int i=0; i < x->MyLength(); ++i)
TEST_FLOATING_EQUALITY((*x)[i], 3.0, 1.0e-10);
}