void Simple_ModelEval::evalModel( const InArgs& inArgs,
const OutArgs& outArgs ) const
{
// Parse InArgs
Teuchos::RCP<const Epetra_Vector> p_in = inArgs.get_p(0);
if (!p_in.get()) cout << "ERROR: Simple_ModelEval requires p as inargs" << endl;
int numParameters = p_in->GlobalLength();
// Parse OutArgs
Teuchos::RCP<Epetra_Vector> g_out = outArgs.get_g(0);
// Parse out-args for sensitivity calculation
Teuchos::RCP<Epetra_MultiVector> dgdp_out;
dgdp_out = outArgs.get_DgDp(0,0).getMultiVector();
if (!is_null(g_out)) {
(*g_out)[0] = 1.0 - (*p_in)[0];
(*g_out)[1] = 1.2 - (*p_in)[1];
(*g_out)[2] = 4.0 - (*p_in)[2] - 0.5* (1.0 - (*p_in)[0]);
}
if (dgdp_out != Teuchos::null) {
// Must initialize since Thyra will init with NaN
dgdp_out->PutScalar(0.0);
// Set gradient of above g equations (derived by hand)
for (int i=0; i<numParameters; i++) {
(*dgdp_out)[i][i] = -1.0;
}
(*dgdp_out)[0][2] = 0.5; //DERIV_BY_COL: [p][g]
}
}
void
Stokhos::MPInverseModelEvaluator::evalModel(const InArgs& inArgs,
const OutArgs& outArgs) const
{
// Create underlying inargs
InArgs me_inargs = me->createInArgs();
// Pass parameters
for (int i=0; i<num_p; i++)
me_inargs.set_p(i, inArgs.get_p(i));
// Pass MP parameters
for (int i=0; i<num_p_mp; i++) {
mp_const_vector_t p_mp = inArgs.get_p_mp(mp_p_index_map[i]);
if (p_mp != Teuchos::null) {
me_inargs.set_p(i+num_p, p_mp->getBlockVector());
}
}
// Create underlying outargs
OutArgs me_outargs = me->createOutArgs();
// MP Responses
for (int i=0; i<num_g_mp; i++) {
int ii = mp_g_index_map[i];
// g
mp_vector_t g_mp = outArgs.get_g_mp(ii);
if (g_mp != Teuchos::null) {
me_outargs.set_g(i, Teuchos::rcp_dynamic_cast<Epetra_Vector>(g_mp->getBlockVector()));
}
// dg/dp
for (int j=0; j<num_p; j++) {
if (!outArgs.supports(OUT_ARG_DgDp_mp, ii, j).none()) {
MPDerivative dgdp_mp = outArgs.get_DgDp_mp(ii,j);
Teuchos::RCP<Stokhos::ProductEpetraMultiVector> dgdp_mp_mv =
dgdp_mp.getMultiVector();
Teuchos::RCP<Epetra_Operator> dgdp_mp_op =
dgdp_mp.getLinearOp();
if (dgdp_mp_mv != Teuchos::null) {
me_outargs.set_DgDp(
i, j, Derivative(dgdp_mp_mv->getBlockMultiVector(),
dgdp_mp.getMultiVectorOrientation()));
}
else if (dgdp_mp_op != Teuchos::null) {
me_outargs.set_DgDp(i, j, Derivative(dgdp_mp_op));
}
}
}
}
// Compute the functions
me->evalModel(me_inargs, me_outargs);
}
void Piro::Epetra::MatrixFreeDecorator::evalModel( const InArgs& inArgs,
const OutArgs& outArgs ) const
{
using Teuchos::RCP;
using Teuchos::rcp;
RCP<Epetra_Operator> W_out = outArgs.get_W();
if (W_out == Teuchos::null) {
// Just pass through as is: nothing to Decorate
model->evalModel(inArgs, outArgs);
}
else {
RCP<Piro::Epetra::MatrixFreeOperator> W_mfo =
Teuchos::rcp_dynamic_cast<Piro::Epetra::MatrixFreeOperator>(W_out);
TEUCHOS_TEST_FOR_EXCEPTION(W_mfo==Teuchos::null, std::logic_error,
"Epetra_Operator sent as W to Piro::Epetra::MatrixFreeDecorator\n"
"be of type Piro::Epetra::MatrixFreeOperator");
// Do base case for MatrixFree: set f instead of W
OutArgs modelOutArgs(outArgs);
InArgs modelInArgs(inArgs);
// Store f_out in case it was also requested
RCP<Epetra_Vector> f_out = outArgs.get_f();
modelOutArgs.set_f(fBase);
modelOutArgs.set_W(Teuchos::null);
//Evaluate the underlying model
model->evalModel(modelInArgs, modelOutArgs);
// If f_out was requested, return it.
if (f_out != Teuchos::null) *f_out = *fBase;
// Save unperturbed solution (deep copy inArgs, shallow f)
InArgs clonedInArgs = inArgs;
for (int l = 0; l < inArgs.Np(); ++l) {
const RCP<const Epetra_Vector> p_l = inArgs.get_p(l);
if (nonnull(p_l))
clonedInArgs.set_p(l, Teuchos::rcp(new Epetra_Vector(*p_l)));
}
clonedInArgs.set_x(Teuchos::rcp(new Epetra_Vector(*inArgs.get_x())));
bool haveXdot = false;
if (inArgs.supports(IN_ARG_x_dot)) {
RCP<const Epetra_Vector> xdot = inArgs.get_x_dot();
if (nonnull(xdot)) {
clonedInArgs.set_x_dot(Teuchos::rcp(new Epetra_Vector(*inArgs.get_x_dot())));
haveXdot = true;
}
}
W_mfo->setBase(clonedInArgs, fBase, haveXdot);
}
}
void
twoD_diffusion_ME::
evalModel(const InArgs& inArgs, const OutArgs& outArgs) const
{
//
// Determinisic calculation
//
// Solution vector
Teuchos::RCP<const Epetra_Vector> det_x = inArgs.get_x();
// Parameters
Teuchos::RCP<const Epetra_Vector> p = inArgs.get_p(0);
if (p == Teuchos::null)
p = p_init;
Teuchos::RCP<Epetra_Vector> f = outArgs.get_f();
Teuchos::RCP<Epetra_Operator> W = outArgs.get_W();
Teuchos::RCP<Epetra_Operator> WPrec = outArgs.get_WPrec();
if (f != Teuchos::null || W != Teuchos::null || WPrec != Teuchos::null) {
if (basis != Teuchos::null) {
for (int i=0; i<point.size(); i++)
point[i] = (*p)[i];
basis->evaluateBases(point, basis_vals);
A->PutScalar(0.0);
for (int k=0;k<A_k.size();k++)
EpetraExt::MatrixMatrix::Add((*A_k[k]), false, basis_vals[k], *A, 1.0);
}
else {
*A = *(A_k[0]);
for (int k=1;k<A_k.size();k++)
EpetraExt::MatrixMatrix::Add((*A_k[k]), false, (*p)[k-1], *A, 1.0);
}
A->FillComplete();
A->OptimizeStorage();
}
// Residual
if (f != Teuchos::null) {
Teuchos::RCP<Epetra_Vector> kx = Teuchos::rcp(new Epetra_Vector(*x_map));
A->Apply(*det_x,*kx);
f->Update(1.0,*kx,-1.0, *b, 0.0);
}
// Jacobian
if (W != Teuchos::null) {
Teuchos::RCP<Epetra_CrsMatrix> jac =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W, true);
*jac = *A;
jac->FillComplete();
jac->OptimizeStorage();
}
// Preconditioner
if (WPrec != Teuchos::null)
precFactory->recompute(A, WPrec);
// Responses (mean value)
Teuchos::RCP<Epetra_Vector> g = outArgs.get_g(0);
if (g != Teuchos::null) {
(det_x->MeanValue(&(*g)[0]));
(*g)[0] *= double(det_x->GlobalLength()) / double(mesh.size());
}
//
// Stochastic Galerkin calculation
//
// Stochastic solution vector
InArgs::sg_const_vector_t x_sg = inArgs.get_x_sg();
// Stochastic parameters
InArgs::sg_const_vector_t p_sg = inArgs.get_p_sg(0);
// Stochastic residual
OutArgs::sg_vector_t f_sg = outArgs.get_f_sg();
if (f_sg != Teuchos::null) {
// Get stochastic expansion data
Teuchos::RCP<Stokhos::OrthogPolyExpansion<int,double> > expn =
inArgs.get_sg_expansion();
typedef Stokhos::Sparse3Tensor<int,double> Cijk_type;
Teuchos::RCP<const Cijk_type> Cijk = expn->getTripleProduct();
const Teuchos::Array<double>& norms = basis->norm_squared();
if (sg_kx_vec_all.size() != basis->size()) {
sg_kx_vec_all.resize(basis->size());
for (int i=0;i<basis->size();i++) {
sg_kx_vec_all[i] = Teuchos::rcp(new Epetra_Vector(*x_map));
}
}
f_sg->init(0.0);
Cijk_type::k_iterator k_begin = Cijk->k_begin();
Cijk_type::k_iterator k_end = Cijk->k_end();
for (Cijk_type::k_iterator k_it=k_begin; k_it!=k_end; ++k_it) {
int k = Stokhos::index(k_it);
for (Cijk_type::kj_iterator j_it = Cijk->j_begin(k_it);
j_it != Cijk->j_end(k_it); ++j_it) {
int j = Stokhos::index(j_it);
A_k[k]->Apply((*x_sg)[j],*(sg_kx_vec_all[j]));
}
for (Cijk_type::kj_iterator j_it = Cijk->j_begin(k_it);
j_it != Cijk->j_end(k_it); ++j_it) {
int j = Stokhos::index(j_it);
for (Cijk_type::kji_iterator i_it = Cijk->i_begin(j_it);
i_it != Cijk->i_end(j_it); ++i_it) {
int i = Stokhos::index(i_it);
double c = Stokhos::value(i_it); // C(i,j,k)
(*f_sg)[i].Update(1.0*c/norms[i],*(sg_kx_vec_all[j]),1.0);
}
}
} //End
(*f_sg)[0].Update(-1.0,*b,1.0);
}
// Stochastic Jacobian
OutArgs::sg_operator_t W_sg = outArgs.get_W_sg();
if (W_sg != Teuchos::null) {
for (int i=0; i<W_sg->size(); i++) {
Teuchos::RCP<Epetra_CrsMatrix> jac =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_sg->getCoeffPtr(i), true);
*jac = *A_k[i];
jac->FillComplete();
jac->OptimizeStorage();
}
}
// Stochastic responses
Teuchos::RCP< Stokhos::EpetraVectorOrthogPoly > g_sg =
outArgs.get_g_sg(0);
if (g_sg != Teuchos::null) {
int sz = x_sg->size();
for (int i=0; i<sz; i++) {
(*x_sg)[i].MeanValue(&(*g_sg)[i][0]);
(*g_sg)[i][0] *= double((*x_sg)[i].GlobalLength()) / double(mesh.size());
}
}
//
// Multi-point calculation
//
// Stochastic solution vector
mp_const_vector_t x_mp = inArgs.get_x_mp();
// Stochastic parameters
mp_const_vector_t p_mp = inArgs.get_p_mp(0);
// Stochastic residual
mp_vector_t f_mp = outArgs.get_f_mp();
mp_operator_t W_mp = outArgs.get_W_mp();
if (f_mp != Teuchos::null || W_mp != Teuchos::null) {
int num_mp = x_mp->size();
for (int i=0; i<num_mp; i++) {
// Compute operator
if (basis != Teuchos::null) {
for (int k=0; k<point.size(); k++)
point[k] = (*p_mp)[i][k];
basis->evaluateBases(point, basis_vals);
A->PutScalar(0.0);
for (int k=0;k<A_k.size();k++)
EpetraExt::MatrixMatrix::Add((*A_k[k]), false, basis_vals[k], *A,
1.0);
}
else {
*A = *(A_k[0]);
for (int k=1;k<A_k.size();k++)
EpetraExt::MatrixMatrix::Add((*A_k[k]), false, (*p_mp)[i][k-1], *A,
1.0);
}
A->FillComplete();
A->OptimizeStorage();
// Compute residual
if (f_mp != Teuchos::null) {
A->Apply((*x_mp)[i], (*f_mp)[i]);
(*f_mp)[i].Update(-1.0, *b, 1.0);
}
// Copy operator
if (W_mp != Teuchos::null) {
Teuchos::RCP<Epetra_CrsMatrix> jac =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_mp->getCoeffPtr(i),
true);
*jac = *A;
jac->FillComplete();
jac->OptimizeStorage();
}
}
}
// Multipoint responses
mp_vector_t g_mp = outArgs.get_g_mp(0);
if (g_mp != Teuchos::null) {
int sz = x_mp->size();
for (int i=0; i<sz; i++) {
(*x_mp)[i].MeanValue(&(*g_mp)[i][0]);
(*g_mp)[i][0] *= double((*x_mp)[i].GlobalLength()) / double(mesh.size());
}
}
}
void MockModelEval_A::evalModel( const InArgs& inArgs,
const OutArgs& outArgs ) const
{
// Parse InArgs
RCP<const Epetra_Vector> p_in = inArgs.get_p(0);
if (!p_in.get()) cout << "ERROR: MockModelEval_A requires p as inargs" << endl;
//int numParameters = p_in->GlobalLength();
RCP<const Epetra_Vector> x_in = inArgs.get_x();
if (!x_in.get()) cout << "ERROR: MockModelEval_A requires x as inargs" << endl;
int vecLength = x_in->GlobalLength();
int myVecLength = x_in->MyLength();
// Parse OutArgs
RCP<Epetra_Vector> f_out = outArgs.get_f();
RCP<Epetra_Vector> g_out = outArgs.get_g(0);
Teuchos::RCP<Epetra_Operator> W_out = outArgs.get_W();
Teuchos::RCP<Epetra_MultiVector> dfdp_out;
if (outArgs.Np() > 0)
dfdp_out = outArgs.get_DfDp(0).getMultiVector();
RCP<Epetra_MultiVector> dgdp_out;
dgdp_out = outArgs.get_DgDp(0,0).getMultiVector();
RCP<Epetra_MultiVector> dgdx_out;
dgdx_out = outArgs.get_DgDx(0).getMultiVector();
if (f_out != Teuchos::null) {
for (int i=0; i<myVecLength; i++) {
int gid = x_in->Map().GID(i);
if (gid==0) // x_0^2 = p_0
(*f_out)[i] = (*x_in)[i] * (*x_in)[i] - (*p_in)[i];
else // x^2 = (i+p_1)^2
(*f_out)[i] = (*x_in)[i] * (*x_in)[i] - (gid + (*p_in)[1])*(gid + (*p_in)[1]);
}
}
if (W_out != Teuchos::null) {
Teuchos::RCP<Epetra_CrsMatrix> W_out_crs =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_out, true);
W_out_crs->PutScalar(0.0);
double diag=0.0;
for (int i=0; i<myVecLength; i++) {
diag = 2.0 * (*x_in)[i];
W_out_crs->ReplaceMyValues(i, 1, &diag, &i);
}
}
if (dfdp_out != Teuchos::null) {
dfdp_out->PutScalar(0.0);
for (int i=0; i<myVecLength; i++) {
int gid = x_in->Map().GID(i);
if (gid==0) (*dfdp_out)[0][i] = -1.0;
else (*dfdp_out)[1][i] = -2.0* (gid + (*p_in)[1]);
}
}
// ObjFn = 0.5*(Sum(x)-Sum(p)-12)^2 + 0.5*(p0-1)^2: min at 1,3
double term1, term2;
x_in->MeanValue(&term1);
term1 = vecLength * term1 - ((*p_in)[0] + (*p_in)[1]) - 12.0;
term2 = (*p_in)[0] - 1.0;
if (!is_null(g_out)) {
(*g_out)[0] = 0.5*term1*term1 + 0.5*term2*term2;
}
if (dgdx_out != Teuchos::null) {
dgdx_out->PutScalar(term1);
}
if (dgdp_out != Teuchos::null) {
dgdp_out->PutScalar(0.0);
(*dgdp_out)[0][0] = -term1 + term2;
(*dgdp_out)[0][1] = -term1;
}
// Modify for time dependent (implicit timeintegration or eigensolves
// Check if time dependent
RCP<const Epetra_Vector> x_dot = inArgs.get_x_dot();
if (x_dot.get()) {
double alpha = inArgs.get_alpha();
double beta = inArgs.get_beta();
if (alpha==0.0 && beta==0.0) {
cout << "MockModelEval Warning: alpha=beta=0 -- setting beta=1" << endl;
beta = 1.0;
}
if (f_out != Teuchos::null) {
for (int i=0; i<myVecLength; i++) {
(*f_out)[i] = -alpha*(*x_dot)[i] + beta * (*f_out)[i];
}
}
if (dfdp_out != Teuchos::null) {
dfdp_out->Scale(beta);
}
if (W_out != Teuchos::null) {
Teuchos::RCP<Epetra_CrsMatrix> W_out_crs =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_out, true);
W_out_crs->Scale(beta);
double diag = -alpha;
for (int i=0; i<myVecLength; i++) {
W_out_crs->SumIntoMyValues(i, 1, &diag, &i);
}
cout << " W_crs = " << *W_out_crs << endl;
}
}
}
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
Stokhos::SGQuadModelEvaluator::
evalModel(const InArgs& inArgs, const OutArgs& outArgs) const
{
// Create underlying inargs
InArgs me_inargs = me->createInArgs();
if (me_inargs.supports(IN_ARG_x))
me_inargs.set_x(inArgs.get_x());
if (me_inargs.supports(IN_ARG_x_dot))
me_inargs.set_x_dot(inArgs.get_x_dot());
if (me_inargs.supports(IN_ARG_alpha))
me_inargs.set_alpha(inArgs.get_alpha());
if (me_inargs.supports(IN_ARG_beta))
me_inargs.set_beta(inArgs.get_beta());
if (me_inargs.supports(IN_ARG_t))
me_inargs.set_t(inArgs.get_t());
for (int i=0; i<num_p; i++)
me_inargs.set_p(i, inArgs.get_p(i));
// Create underlying outargs
OutArgs me_outargs = me->createOutArgs();
if (me_outargs.supports(OUT_ARG_f))
me_outargs.set_f(outArgs.get_f());
if (me_outargs.supports(OUT_ARG_W))
me_outargs.set_W(outArgs.get_W());
for (int j=0; j<num_p; j++)
if (!outArgs.supports(OUT_ARG_DfDp, j).none())
me_outargs.set_DfDp(j, outArgs.get_DfDp(j));
for (int i=0; i<num_g; i++) {
me_outargs.set_g(i, outArgs.get_g(i));
if (!outArgs.supports(OUT_ARG_DgDx, i).none())
me_outargs.set_DgDx(i, outArgs.get_DgDx(i));
if (!outArgs.supports(OUT_ARG_DgDx_dot, i).none())
me_outargs.set_DgDx(i, outArgs.get_DgDx_dot(i));
for (int j=0; j<num_p; j++)
if (!outArgs.supports(OUT_ARG_DgDp, i, j).none())
me_outargs.set_DgDp(i, j, outArgs.get_DgDp(i,j));
}
bool do_quad = false;
InArgs::sg_const_vector_t x_sg;
InArgs::sg_const_vector_t x_dot_sg;
Teuchos::Array<InArgs::sg_const_vector_t> p_sg(num_p);
OutArgs::sg_vector_t f_sg;
OutArgs::sg_operator_t W_sg;
Teuchos::Array<SGDerivative> dfdp_sg(num_p);
Teuchos::Array<OutArgs::sg_vector_t> g_sg(num_g);
Teuchos::Array<SGDerivative> dgdx_sg(num_g);
Teuchos::Array<SGDerivative> dgdx_dot_sg(num_g);
Teuchos::Array< Teuchos::Array<SGDerivative> > dgdp_sg(num_g);
TEUCHOS_TEST_FOR_EXCEPTION(inArgs.get_sg_basis() == Teuchos::null,
std::logic_error,
"Error! Stokhos::SGQuadModelEvaluator::evalModel(): " <<
"SG basis inArg cannot be null!");
TEUCHOS_TEST_FOR_EXCEPTION(inArgs.get_sg_quadrature() == Teuchos::null,
std::logic_error,
"Error! Stokhos::SGQuadModelEvaluator::evalModel(): " <<
"SG quadrature inArg cannot be null!");
Teuchos::RCP<const Stokhos::OrthogPolyBasis<int,double> > basis =
inArgs.get_sg_basis();
Teuchos::RCP< const Stokhos::Quadrature<int,double> > quad =
inArgs.get_sg_quadrature();
if (inArgs.supports(IN_ARG_x_sg)) {
x_sg = inArgs.get_x_sg();
if (x_sg != Teuchos::null) {
do_quad = true;
}
}
if (inArgs.supports(IN_ARG_x_dot_sg)) {
x_dot_sg = inArgs.get_x_dot_sg();
if (x_dot_sg != Teuchos::null) {
do_quad = true;
}
}
for (int i=0; i<num_p; i++) {
p_sg[i] = inArgs.get_p_sg(i);
if (p_sg[i] != Teuchos::null) {
do_quad = true;
}
}
if (outArgs.supports(OUT_ARG_f_sg)) {
f_sg = outArgs.get_f_sg();
if (f_sg != Teuchos::null)
f_sg->init(0.0);
}
if (outArgs.supports(OUT_ARG_W_sg)) {
W_sg = outArgs.get_W_sg();
if (W_sg != Teuchos::null)
W_sg->init(0.0);
}
for (int i=0; i<num_p; i++) {
if (!outArgs.supports(OUT_ARG_DfDp_sg, i).none()) {
dfdp_sg[i] = outArgs.get_DfDp_sg(i);
if (dfdp_sg[i].getMultiVector() != Teuchos::null)
dfdp_sg[i].getMultiVector()->init(0.0);
else if (dfdp_sg[i].getLinearOp() != Teuchos::null)
dfdp_sg[i].getLinearOp()->init(0.0);
}
}
for (int i=0; i<num_g; i++) {
g_sg[i] = outArgs.get_g_sg(i);
if (g_sg[i] != Teuchos::null)
g_sg[i]->init(0.0);
if (!outArgs.supports(OUT_ARG_DgDx_sg, i).none()) {
dgdx_sg[i] = outArgs.get_DgDx_sg(i);
if (dgdx_sg[i].getMultiVector() != Teuchos::null)
dgdx_sg[i].getMultiVector()->init(0.0);
else if (dgdx_sg[i].getLinearOp() != Teuchos::null)
dgdx_sg[i].getLinearOp()->init(0.0);
}
if (!outArgs.supports(OUT_ARG_DgDx_dot_sg, i).none()) {
dgdx_dot_sg[i] = outArgs.get_DgDx_dot_sg(i);
if (dgdx_dot_sg[i].getMultiVector() != Teuchos::null)
dgdx_dot_sg[i].getMultiVector()->init(0.0);
else if (dgdx_dot_sg[i].getLinearOp() != Teuchos::null)
dgdx_dot_sg[i].getLinearOp()->init(0.0);
}
dgdp_sg[i].resize(num_p);
for (int j=0; j<num_p; j++) {
if (!outArgs.supports(OUT_ARG_DgDp_sg, i, j).none()) {
dgdp_sg[i][j] = outArgs.get_DgDp_sg(i,j);
if (dgdp_sg[i][j].getMultiVector() != Teuchos::null)
dgdp_sg[i][j].getMultiVector()->init(0.0);
else if (dgdp_sg[i][j].getLinearOp() != Teuchos::null)
dgdp_sg[i][j].getLinearOp()->init(0.0);
}
}
}
if (do_quad) {
// Get quadrature data
const Teuchos::Array< Teuchos::Array<double> >& quad_points =
quad->getQuadPoints();
const Teuchos::Array<double>& quad_weights =
quad->getQuadWeights();
const Teuchos::Array< Teuchos::Array<double> > & quad_values =
quad->getBasisAtQuadPoints();
const Teuchos::Array<double>& basis_norms = basis->norm_squared();
// Perform integrations
for (int qp=0; qp<quad_points.size(); qp++) {
// StieltjesPCEBasis can introduce quadrature points with zero weight
// Don't do those evaluations, since the model might not like the
// quadrature points (i.e., zero)
if (quad_weights[qp] == 0.0)
continue;
{
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR_DIFF("Stokhos: SGQuadModelEvaluator -- Polynomial Evaluation",
PolyEvaluation);
#endif
// Evaluate inputs at quadrature points
if (x_sg != Teuchos::null) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR("Stokhos: SGQuadModelEvaluator -- X Evaluation");
#endif
x_sg->evaluate(quad_values[qp], *x_qp);
me_inargs.set_x(x_qp);
}
if (x_dot_sg != Teuchos::null) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR("Stokhos: SGQuadModelEvaluator -- X_dot Evaluation");
#endif
x_dot_sg->evaluate(quad_values[qp], *x_dot_qp);
me_inargs.set_x_dot(x_qp);
}
for (int i=0; i<num_p; i++) {
if (p_sg[i] != Teuchos::null) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR("Stokhos: SGQuadModelEvaluator -- P Evaluation");
#endif
p_sg[i]->evaluate(quad_values[qp], *(p_qp[i]));
me_inargs.set_p(i, p_qp[i]);
}
}
if (f_sg != Teuchos::null)
me_outargs.set_f(f_qp);
if (W_sg != Teuchos::null)
me_outargs.set_W(W_qp);
for (int i=0; i<num_p; i++) {
if (!dfdp_sg[i].isEmpty())
me_outargs.set_DfDp(i, dfdp_qp[i]);
}
for (int i=0; i<num_g; i++) {
if (g_sg[i] != Teuchos::null)
me_outargs.set_g(i, g_qp[i]);
if (!dgdx_dot_sg[i].isEmpty())
me_outargs.set_DgDx_dot(i, dgdx_dot_qp[i]);
if (!dgdx_sg[i].isEmpty())
me_outargs.set_DgDx(i, dgdx_qp[i]);
for (int j=0; j<num_p; j++)
if (!dgdp_sg[i][j].isEmpty())
me_outargs.set_DgDp(i, j, dgdp_qp[i][j]);
}
}
{
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR("Stokhos: SGQuadModelEvaluator -- Model Evaluation");
#endif
// Evaluate model at quadrature points
me->evalModel(me_inargs, me_outargs);
}
{
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR_DIFF(
"Stokhos: SGQuadModelEvaluator -- Polynomial Integration", Integration);
#endif
// Sum in results
if (f_sg != Teuchos::null) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR("Stokhos: SGQuadModelEvaluator -- F Integration");
#endif
f_sg->sumIntoAllTerms(quad_weights[qp], quad_values[qp], basis_norms,
*f_qp);
}
if (W_sg != Teuchos::null) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR("Stokhos: SGQuadModelEvaluator -- W Integration");
#endif
W_sg->sumIntoAllTerms(quad_weights[qp], quad_values[qp], basis_norms,
*W_qp);
}
for (int j=0; j<num_p; j++) {
if (!dfdp_sg[j].isEmpty()) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR(
"Stokhos: SGQuadModelEvaluator -- df/dp Integration");
#endif
if (dfdp_sg[j].getMultiVector() != Teuchos::null) {
dfdp_sg[j].getMultiVector()->sumIntoAllTerms(
quad_weights[qp], quad_values[qp], basis_norms,
*(dfdp_qp[j].getMultiVector()));
}
else if (dfdp_sg[j].getLinearOp() != Teuchos::null) {
dfdp_sg[j].getLinearOp()->sumIntoAllTerms(
quad_weights[qp], quad_values[qp], basis_norms,
*(dfdp_qp[j].getLinearOp()));
}
}
}
for (int i=0; i<num_g; i++) {
if (g_sg[i] != Teuchos::null) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR("Stokhos: SGQuadModelEvaluator -- G Integration");
#endif
g_sg[i]->sumIntoAllTerms(quad_weights[qp], quad_values[qp],
basis_norms, *g_qp[i]);
}
if (!dgdx_dot_sg[i].isEmpty()) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR(
"Stokhos: SGQuadModelEvaluator -- dg/dx_dot Integration");
#endif
if (dgdx_dot_sg[i].getMultiVector() != Teuchos::null) {
dgdx_dot_sg[i].getMultiVector()->sumIntoAllTerms(
quad_weights[qp], quad_values[qp], basis_norms,
*(dgdx_dot_qp[i].getMultiVector()));
}
else if (dgdx_dot_sg[i].getLinearOp() != Teuchos::null) {
dgdx_dot_sg[i].getLinearOp()->sumIntoAllTerms(
quad_weights[qp], quad_values[qp], basis_norms,
*(dgdx_dot_qp[i].getLinearOp()));
}
}
if (!dgdx_sg[i].isEmpty()) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR(
"Stokhos: SGQuadModelEvaluator -- dg/dx Integration");
#endif
if (dgdx_sg[i].getMultiVector() != Teuchos::null) {
dgdx_sg[i].getMultiVector()->sumIntoAllTerms(
quad_weights[qp], quad_values[qp], basis_norms,
*(dgdx_qp[i].getMultiVector()));
}
else if (dgdx_sg[i].getLinearOp() != Teuchos::null) {
dgdx_sg[i].getLinearOp()->sumIntoAllTerms(
quad_weights[qp], quad_values[qp], basis_norms,
*(dgdx_qp[i].getLinearOp()));
}
}
for (int j=0; j<num_p; j++) {
if (!dgdp_sg[i][j].isEmpty()) {
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR(
"Stokhos: SGQuadModelEvaluator -- dg/dp Integration");
#endif
if (dgdp_sg[i][j].getMultiVector() != Teuchos::null) {
dgdp_sg[i][j].getMultiVector()->sumIntoAllTerms(
quad_weights[qp], quad_values[qp], basis_norms,
*(dgdp_qp[i][j].getMultiVector()));
}
else if (dgdp_sg[i][j].getLinearOp() != Teuchos::null) {
dgdp_sg[i][j].getLinearOp()->sumIntoAllTerms(
quad_weights[qp], quad_values[qp], basis_norms,
*(dgdp_qp[i][j].getLinearOp()));
}
}
}
}
}
}
}
else {
// Compute the non-SG functions
me->evalModel(me_inargs, me_outargs);
}
}
void Piro::Epetra::TrapezoidRuleSolver::evalModel( const InArgs& inArgs,
const OutArgs& outArgs ) const
{
using Teuchos::RCP;
using Teuchos::rcp;
EpetraExt::ModelEvaluator::InArgs nox_inargs = noxSolver->createInArgs();
EpetraExt::ModelEvaluator::OutArgs nox_outargs = noxSolver->createOutArgs();
// Parse InArgs
RCP<const Epetra_Vector> p_in;
if (num_p > 0) {
p_in = inArgs.get_p(0);
nox_inargs.set_p(0, p_in);
}
// Parse OutArgs: always 1 extra
RCP<Epetra_Vector> g_out;
if (num_g > 0) {
g_out = outArgs.get_g(0);
nox_outargs.set_g(0, g_out);
}
RCP<Epetra_Vector> gx_out = outArgs.get_g(num_g);
nox_outargs.set_g(num_g, gx_out);
RCP<Epetra_Vector> x = rcp(new Epetra_Vector(*model->get_x_init()));
RCP<Epetra_Vector> v = rcp(new Epetra_Vector(*model->get_x_dot_init()));
RCP<Epetra_Vector> a = rcp(new Epetra_Vector(*model->get_f_map()));
RCP<Epetra_Vector> x_pred = rcp(new Epetra_Vector(*model->get_f_map()));
RCP<Epetra_Vector> a_old = rcp(new Epetra_Vector(*model->get_f_map()));
TEUCHOS_TEST_FOR_EXCEPTION(v == Teuchos::null || x == Teuchos::null,
Teuchos::Exceptions::InvalidParameter,
std::endl << "Error in Piro::Epetra::TrapezoidRuleSolver " <<
"Requires initial x and x_dot: " << std::endl);
double nrm;
v->Norm2(&nrm); *out << "Initial Velocity = " << nrm << endl;
double t = t_init;
//calculate intial acceleration using small time step (1.0e-3*delta_t)
{
double pert= 1.0e6 * 4.0 / (delta_t * delta_t);
*x_pred = *x;
model->injectData(x_pred, x_pred, pert, t);
noxSolver->evalModel(nox_inargs, nox_outargs);
a->Update(pert, *gx_out, -pert, *x_pred,0.0);
a->Norm2(&nrm); *out << "Calculated a_init = " << nrm << endl;
}
// Start integration loop
double fdt2 = 4.0 / (delta_t * delta_t);
double dt2f = delta_t * delta_t / 4.0;
double hdt = delta_t/ 2.0;
for (int timeStep = 1; timeStep <= numTimeSteps; timeStep++) {
t += delta_t;
*a_old = *a;
*x_pred = *x;
x_pred->Update(delta_t, *v, dt2f, *a, 1.0);
model->injectData(x, x_pred, fdt2, t);
noxSolver->evalModel(nox_inargs, nox_outargs);
// Copy out final solution from nonlinear solver
*x = *gx_out;
// Compute a and v and new conditions
a->Update(fdt2, *x, -fdt2, *x_pred,0.0);
v->Update(hdt, *a, hdt, *a_old, 1.0);
if (observer != Teuchos::null) observer->observeSolution(*x,t);
if (g_out != Teuchos::null)
g_out->Print(*out << "Responses at time step(time) = " << timeStep << "("<<t<<")\n");
}
}
void
QCAD::GenEigensolver::evalModel(const InArgs& inArgs,
const OutArgs& outArgs ) const
{
// type definitions
typedef Epetra_MultiVector MV;
typedef Epetra_Operator OP;
typedef Anasazi::MultiVecTraits<double, Epetra_MultiVector> MVT;
// Get the stiffness and mass matrices
InArgs model_inArgs = model->createInArgs();
OutArgs model_outArgs = model->createOutArgs();
//input args
model_inArgs.set_t(0.0);
Teuchos::RCP<const Epetra_Vector> x = model->get_x_init();
Teuchos::RCP<const Epetra_Vector> x_dot = model->get_x_dot_init();
model_inArgs.set_x(x);
model_inArgs.set_x_dot(x_dot);
model_inArgs.set_alpha(0.0);
model_inArgs.set_beta(1.0);
for(int i=0; i<model_num_p; i++)
model_inArgs.set_p(i, inArgs.get_p(i));
//output args
Teuchos::RCP<Epetra_CrsMatrix> K =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(model->create_W(), true);
model_outArgs.set_W(K);
model->evalModel(model_inArgs, model_outArgs); //compute K matrix
// reset alpha and beta to compute the mass matrix
model_inArgs.set_alpha(1.0);
model_inArgs.set_beta(0.0);
Teuchos::RCP<Epetra_CrsMatrix> M =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(model->create_W(), true);
model_outArgs.set_W(M);
model->evalModel(model_inArgs, model_outArgs); //compute M matrix
Teuchos::RCP<Epetra_MultiVector> ivec = Teuchos::rcp( new Epetra_MultiVector(K->OperatorDomainMap(), blockSize) );
ivec->Random();
// Create the eigenproblem.
Teuchos::RCP<Anasazi::BasicEigenproblem<double, MV, OP> > eigenProblem =
Teuchos::rcp( new Anasazi::BasicEigenproblem<double, MV, OP>(K, M, ivec) );
// Inform the eigenproblem that the operator A is symmetric
eigenProblem->setHermitian(bHermitian);
// Set the number of eigenvalues requested
eigenProblem->setNEV( nev );
// Inform the eigenproblem that you are finishing passing it information
bool bSuccess = eigenProblem->setProblem();
TEUCHOS_TEST_FOR_EXCEPTION(!bSuccess, Teuchos::Exceptions::InvalidParameter,
"Anasazi::BasicEigenproblem::setProblem() returned an error.\n" << std::endl);
// Create parameter list to pass into the solver manager
//
Teuchos::ParameterList eigenPL;
eigenPL.set( "Which", which );
eigenPL.set( "Block Size", blockSize );
eigenPL.set( "Maximum Iterations", maxIters );
eigenPL.set( "Convergence Tolerance", conv_tol );
eigenPL.set( "Full Ortho", true );
eigenPL.set( "Use Locking", true );
eigenPL.set( "Verbosity", Anasazi::IterationDetails );
// Create the solver manager
Anasazi::LOBPCGSolMgr<double, MV, OP> eigenSolverMan(eigenProblem, eigenPL);
// Solve the problem
Anasazi::ReturnType returnCode = eigenSolverMan.solve();
// Get the eigenvalues and eigenvectors from the eigenproblem
Anasazi::Eigensolution<double,MV> sol = eigenProblem->getSolution();
std::vector<Anasazi::Value<double> > evals = sol.Evals;
Teuchos::RCP<MV> evecs = sol.Evecs;
std::vector<double> evals_real(sol.numVecs);
for(int i=0; i<sol.numVecs; i++) evals_real[i] = evals[i].realpart;
// Compute residuals.
std::vector<double> normR(sol.numVecs);
if (sol.numVecs > 0) {
Teuchos::SerialDenseMatrix<int,double> T(sol.numVecs, sol.numVecs);
Epetra_MultiVector Kvec( K->OperatorDomainMap(), evecs->NumVectors() );
Epetra_MultiVector Mvec( M->OperatorDomainMap(), evecs->NumVectors() );
T.putScalar(0.0);
for (int i=0; i<sol.numVecs; i++) {
T(i,i) = evals_real[i];
}
K->Apply( *evecs, Kvec );
M->Apply( *evecs, Mvec );
MVT::MvTimesMatAddMv( -1.0, Mvec, T, 1.0, Kvec );
MVT::MvNorm( Kvec, normR );
}
// Print the results
std::ostringstream os;
os.setf(std::ios_base::right, std::ios_base::adjustfield);
os<<"Solver manager returned " << (returnCode == Anasazi::Converged ? "converged." : "unconverged.") << std::endl;
os<<std::endl;
os<<"------------------------------------------------------"<<std::endl;
os<<std::setw(16)<<"Eigenvalue"
<<std::setw(18)<<"Direct Residual"
<<std::endl;
os<<"------------------------------------------------------"<<std::endl;
for (int i=0; i<sol.numVecs; i++) {
os<<std::setw(16)<<evals_real[i]
<<std::setw(18)<<normR[i]/evals_real[i]
<<std::endl;
}
os<<"------------------------------------------------------"<<std::endl;
std::cout << Anasazi::Anasazi_Version() << std::endl << std::endl;
std::cout << os.str();
// Package the results in an eigendata structure and "observe" them
// (put them into the user-supplied StateManager object) (see Albany_SaveEigenData.cpp)
Teuchos::RCP<Albany::EigendataStruct> eigenData = Teuchos::rcp( new Albany::EigendataStruct );
eigenData->eigenvalueIm = Teuchos::null; // eigenvalues are real
eigenData->eigenvectorIm = Teuchos::null; // eigenvectors are real
Teuchos::RCP<Albany::AbstractDiscretization> disc =
observer->getDiscretization();
eigenData->eigenvalueRe = Teuchos::rcp( new std::vector<double>(evals_real) );
for(int i=0; i<sol.numVecs; i++) (*(eigenData->eigenvalueRe))[i] *= -1;
//make eigenvals --> neg_eigenvals to mimic historic LOCA eigensolver (TODO: remove this and switch convention)
if (sol.numVecs > 0) {
// Store *overlapped* eigenvectors in EigendataStruct
eigenData->eigenvectorRe =
Teuchos::rcp(new Epetra_MultiVector(*(disc->getOverlapMap()), sol.numVecs));
// Importer for overlapped data
Teuchos::RCP<Epetra_Import> importer =
Teuchos::rcp(new Epetra_Import(*(disc->getOverlapMap()), *(disc->getMap())));
// Overlapped eigenstate vectors
for(int i=0; i<sol.numVecs; i++)
(*(eigenData->eigenvectorRe))(i)->Import( *((*evecs)(i)), *importer, Insert );
}
observer->setEigenData(eigenData);
}
void
MockModelEval_D::
evalModel(const InArgs& inArgs, const OutArgs& outArgs) const
{
int proc = comm->MyPID();
//
// Deterministic calculation
//
// Parse InArgs
RCP<const Epetra_Vector> p1_in = inArgs.get_p(0);
if (p1_in == Teuchos::null)
p1_in = p1_init;
RCP<const Epetra_Vector> p2_in = inArgs.get_p(1);
if (p2_in == Teuchos::null)
p2_in = p2_init;
RCP<const Epetra_Vector> x_in = inArgs.get_x();
// Parse OutArgs
RCP<Epetra_Vector> f_out = outArgs.get_f();
if (f_out != Teuchos::null) {
double p = (*p1_in)[0];
double xi = (*p2_in)[0];
if (proc == 0) {
double x = (*x_in)[0];
(*f_out)[0] = x - p + xi;
}
}
RCP<Epetra_CrsMatrix> W_out =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(outArgs.get_W());
if (W_out != Teuchos::null) {
if (proc == 0) {
double val = 1.0;
int i = 0;
W_out->ReplaceMyValues(i, 1, &val, &i);
}
}
RCP<Epetra_MultiVector> dfdp1 = outArgs.get_DfDp(0).getMultiVector();
if (dfdp1 != Teuchos::null) {
if (proc == 0)
(*dfdp1)[0][0] = -1.0;
}
RCP<Epetra_MultiVector> dfdp2 = outArgs.get_DfDp(1).getMultiVector();
if (dfdp2 != Teuchos::null) {
if (proc == 0)
(*dfdp2)[0][0] = 1.0;
}
RCP<Epetra_Vector> g_out = outArgs.get_g(0);
if (g_out != Teuchos::null) {
if (proc == 0) {
double x = (*x_in)[0];
(*g_out)[0] = 1.0 / x;
}
}
RCP<Epetra_MultiVector> dgdx = outArgs.get_DgDx(0).getMultiVector();
if (dgdx != Teuchos::null) {
if (proc == 0) {
double x = (*x_in)[0];
(*dgdx)[0][0] = -1.0 / (x*x);
}
}
RCP<Epetra_MultiVector> dgdp1 = outArgs.get_DgDp(0,0).getMultiVector();
if (dgdp1 != Teuchos::null) {
if (proc == 0) {
(*dgdp1)[0][0] = 0.0;
}
}
RCP<Epetra_MultiVector> dgdp2 = outArgs.get_DgDp(0,1).getMultiVector();
if (dgdp2 != Teuchos::null) {
if (proc == 0) {
(*dgdp2)[0][0] = 0.0;
}
}
//
// Stochastic calculation
//
#ifdef Piro_ENABLE_Stokhos
// Parse InArgs
RCP<const Stokhos::OrthogPolyBasis<int,double> > basis =
inArgs.get_sg_basis();
RCP<Stokhos::OrthogPolyExpansion<int,double> > expn =
inArgs.get_sg_expansion();
InArgs::sg_const_vector_t x_sg = inArgs.get_x_sg();
InArgs::sg_const_vector_t p1_sg = inArgs.get_p_sg(0);
InArgs::sg_const_vector_t p2_sg = inArgs.get_p_sg(1);
// Parse OutArgs
OutArgs::sg_vector_t f_sg = outArgs.get_f_sg();
if (f_sg != Teuchos::null && proc == 0) {
for (int block=0; block<f_sg->size(); block++) {
(*f_sg)[block][0] =
(*x_sg)[block][0] - (*p1_sg)[block][0] + (*p2_sg)[block][0];
}
}
OutArgs::sg_operator_t W_sg = outArgs.get_W_sg();
if (W_sg != Teuchos::null) {
W_sg->init(0.0);
Teuchos::RCP<Epetra_CrsMatrix> W =
Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(W_sg->getCoeffPtr(0),
true);
if (proc == 0) {
int i = 0;
double val = 1.0;
W->ReplaceMyValues(i, 1, &val, &i);
}
}
RCP<Stokhos::EpetraMultiVectorOrthogPoly> dfdp1_sg =
outArgs.get_DfDp_sg(0).getMultiVector();
if (dfdp1_sg != Teuchos::null) {
dfdp1_sg->init(0.0);
if (proc == 0) {
(*dfdp1_sg)[0][0][0] = -1.0;
}
}
RCP<Stokhos::EpetraMultiVectorOrthogPoly> dfdp2_sg =
outArgs.get_DfDp_sg(1).getMultiVector();
if (dfdp2_sg != Teuchos::null) {
dfdp2_sg->init(0.0);
if (proc == 0) {
(*dfdp2_sg)[0][0][0] = 1.0;
}
}
Stokhos::OrthogPolyApprox<int,double> x(basis);
if (x_sg != Teuchos::null && proc == 0) {
for (int i=0; i<basis->size(); i++) {
x[i] = (*x_sg)[i][0];
}
}
OutArgs::sg_vector_t g_sg = outArgs.get_g_sg(0);
if (g_sg != Teuchos::null && proc == 0) {
Stokhos::OrthogPolyApprox<int,double> xinv(basis);
expn->divide(xinv, 1.0, x);
for (int block=0; block<g_sg->size(); block++) {
(*g_sg)[block][0] = xinv[block];
}
}
RCP<Stokhos::EpetraMultiVectorOrthogPoly> dgdx_sg =
outArgs.get_DgDx_sg(0).getMultiVector();
if (dgdx_sg != Teuchos::null && proc == 0) {
Stokhos::OrthogPolyApprox<int,double> x2(basis), x2inv(basis);
expn->times(x2, x, x);
expn->divide(x2inv, -1.0, x2);
for (int block=0; block<dgdx_sg->size(); block++) {
(*dgdx_sg)[block][0][0] = x2inv[block];
}
}
RCP<Stokhos::EpetraMultiVectorOrthogPoly> dgdp1_sg =
outArgs.get_DgDp_sg(0,0).getMultiVector();
if (dgdp1_sg != Teuchos::null) {
dgdp1_sg->init(0.0);
}
RCP<Stokhos::EpetraMultiVectorOrthogPoly> dgdp2_sg =
outArgs.get_DgDp_sg(0,1).getMultiVector();
if (dgdp2_sg != Teuchos::null) {
dgdp2_sg->init(0.0);
}
#endif
}
void EpetraExt::MultiPointModelEvaluator::evalModel( const InArgs& inArgs,
const OutArgs& outArgs ) const
{
EpetraExt::ModelEvaluator::InArgs underlyingInArgs = underlyingME->createInArgs();
EpetraExt::ModelEvaluator::OutArgs underlyingOutArgs = underlyingME->createOutArgs();
//temp code for multipoint param q vec
/*
Teuchos::RefCountPtr<Epetra_Vector> q =
Teuchos::rcp(new Epetra_Vector(*(underlyingME->get_p_map(1))));
*/
// Parse InArgs
Teuchos::RefCountPtr<const Epetra_Vector> p_in = inArgs.get_p(0);
if (p_in.get()) underlyingInArgs.set_p(0, p_in);
Teuchos::RefCountPtr<const Epetra_Vector> x_in = inArgs.get_x();
block_x->Epetra_Vector::operator=(*x_in); //copy into block vector
// Parse OutArgs
Teuchos::RefCountPtr<Epetra_Vector> f_out = outArgs.get_f();
Teuchos::RefCountPtr<Epetra_Operator> W_out = outArgs.get_W();
Teuchos::RefCountPtr<EpetraExt::BlockCrsMatrix> W_block =
Teuchos::rcp_dynamic_cast<EpetraExt::BlockCrsMatrix>(W_out);
Teuchos::RefCountPtr<Epetra_Vector> g_out;
if (underlyingNg) g_out = outArgs.get_g(0);
if (g_out.get()) g_out->PutScalar(0.0);
EpetraExt::ModelEvaluator::Derivative DfDp_out = outArgs.get_DfDp(0);
EpetraExt::ModelEvaluator::Derivative DgDx_out;
EpetraExt::ModelEvaluator::Derivative DgDp_out;
if (underlyingNg) {
DgDx_out = outArgs.get_DgDx(0);
DgDp_out = outArgs.get_DgDp(0,0);
if (!DgDx_out.isEmpty()) DgDx_out.getMultiVector()->PutScalar(0.0);
if (!DgDp_out.isEmpty()) DgDp_out.getMultiVector()->PutScalar(0.0);
}
// For mathcingProblems, g is needed to calc DgDx DgDp, so ask for
// g even if it isn't requested.
bool need_g = g_out.get();
if (matchingProblem)
if ( !DgDx_out.isEmpty() || !DgDp_out.isEmpty() ) need_g = true;
// Begin loop over Points (steps) owned on this proc
for (int i=0; i < timeStepsOnTimeDomain; i++) {
// Set MultiPoint parameter vector
underlyingInArgs.set_p(1, (*q_vec)[i]);
// Set InArgs
if(longlong) {
#ifndef EPETRA_NO_64BIT_GLOBAL_INDICES
block_x->ExtractBlockValues(*split_x, (*rowIndex_LL)[i]);
#endif
}
else {
#ifndef EPETRA_NO_32BIT_GLOBAL_INDICES
block_x->ExtractBlockValues(*split_x, (*rowIndex_int)[i]);
#endif
}
underlyingInArgs.set_x(split_x);
// Set OutArgs
if (f_out.get()) underlyingOutArgs.set_f(split_f);
if (need_g) underlyingOutArgs.set_g(0, split_g);
if (W_out.get()) underlyingOutArgs.set_W(split_W);
if (!DfDp_out.isEmpty()) underlyingOutArgs.set_DfDp(0, *deriv_DfDp);
if (!DgDx_out.isEmpty()) underlyingOutArgs.set_DgDx(0, *deriv_DgDx);
if (!DgDp_out.isEmpty()) underlyingOutArgs.set_DgDp(0, 0, *deriv_DgDp);
//********Eval Model ********/
underlyingME->evalModel(underlyingInArgs, underlyingOutArgs);
//********Eval Model ********/
// If matchingProblem, modify all g-related quantitites G = 0.5*(g-g*)^2 / g*^2
if (matchingProblem) {
if (need_g) {
double diff = (*split_g)[0] - (*(*matching_vec)[i])[0];
double nrmlz = fabs((*(*matching_vec)[i])[0]) + 1.0e-6;
(*split_g)[0] = 0.5 * diff * diff/(nrmlz*nrmlz);
if (!DgDx_out.isEmpty()) split_DgDx->Scale(diff/(nrmlz*nrmlz));
if (!DgDp_out.isEmpty()) split_DgDp->Scale(diff/(nrmlz*nrmlz));
}
}
// Repackage block components into global block matrx/vector/multivector
if(longlong) {
#ifndef EPETRA_NO_64BIT_GLOBAL_INDICES
if (f_out.get()) block_f->LoadBlockValues(*split_f, (*rowIndex_LL)[i]);
if (W_out.get()) W_block->LoadBlock(*split_W, i, 0);
// note: split_DfDp points inside deriv_DfDp
if (!DfDp_out.isEmpty()) block_DfDp->LoadBlockValues(*split_DfDp, (*rowIndex_LL)[i]);
if (!DgDx_out.isEmpty()) block_DgDx->LoadBlockValues(*split_DgDx, (*rowIndex_LL)[i]);
#endif
}
else {
#ifndef EPETRA_NO_32BIT_GLOBAL_INDICES
if (f_out.get()) block_f->LoadBlockValues(*split_f, (*rowIndex_int)[i]);
if (W_out.get()) W_block->LoadBlock(*split_W, i, 0);
// note: split_DfDp points inside deriv_DfDp
if (!DfDp_out.isEmpty()) block_DfDp->LoadBlockValues(*split_DfDp, (*rowIndex_int)[i]);
if (!DgDx_out.isEmpty()) block_DgDx->LoadBlockValues(*split_DgDx, (*rowIndex_int)[i]);
#endif
}
// Assemble multiple steps on this domain into g and dgdp(0) vectors
if (g_out.get()) g_out->Update(1.0, *split_g, 1.0);
if (!DgDp_out.isEmpty())
DgDp_out.getMultiVector()->Update(1.0, *split_DgDp, 1.0);
} // End loop over multiPoint steps on this domain/cluster
//Copy block vectors into *_out vectors of same size
if (f_out.get()) f_out->operator=(*block_f);
if (!DfDp_out.isEmpty())
DfDp_out.getMultiVector()->operator=(*block_DfDp);
if (!DgDx_out.isEmpty())
DgDx_out.getMultiVector()->operator=(*block_DgDx);
//Sum together obj fn contributions from differnt Domains (clusters).
if (numTimeDomains > 1) {
double factorToZeroOutCopies = 0.0;
if (globalComm->SubDomainComm().MyPID()==0) factorToZeroOutCopies = 1.0;
if (g_out.get()) {
(*g_out).Scale(factorToZeroOutCopies);
double* vPtr = &((*g_out)[0]);
Epetra_Vector tmp = *(g_out.get());
globalComm->SumAll( &(tmp[0]), vPtr, num_g0);
}
if (!DgDp_out.isEmpty()) {
DgDp_out.getMultiVector()->Scale(factorToZeroOutCopies);
double* mvPtr = (*DgDp_out.getMultiVector())[0];
Epetra_MultiVector tmp = *(DgDp_out.getMultiVector());
globalComm->SumAll(tmp[0], mvPtr, num_dg0dp0);
}
}
}
void Piro::Epetra::NOXSolver::evalModel(const InArgs& inArgs,
const OutArgs& outArgs ) const
{
// Parse input parameters
for (int i=0; i<num_p; i++) {
Teuchos::RCP<const Epetra_Vector> p_in = inArgs.get_p(i);
if (p_in != Teuchos::null)
interface->inargs_set_p(p_in, i); // Pass "p_in" through to inargs
}
// Reset initial guess, if the user requests
if(piroParams->sublist("NOX").get("Reset Initial Guess",false)==true)
*currentSolution=*model->get_x_init();
// Solve
solver->reset(*currentSolution);
NOX::StatusTest::StatusType status = solver->solve();
// Print status
if (status == NOX::StatusTest::Converged)
//utils.out() << "Step Converged" << std::endl;
;
else {
utils.out() << "Nonlinear solver failed to converge!" << std::endl;
outArgs.setFailed();
}
// Get the NOX and Epetra_Vector with the final solution from the solver
(*currentSolution)=grp->getX();
Teuchos::RCP<const Epetra_Vector> finalSolution =
Teuchos::rcp(&(currentSolution->getEpetraVector()), false);
// Print solution
if (utils.isPrintType(NOX::Utils::Details)) {
utils.out() << std::endl << "Final Solution" << std::endl
<< "****************" << std::endl;
finalSolution->Print(utils.pout());
}
// Output the parameter list
if (utils.isPrintType(NOX::Utils::Parameters)) {
utils.out() << std::endl << "Final Parameters" << std::endl
<< "****************" << std::endl;
piroParams->print(utils.out());
utils.out() << std::endl;
}
// Print stats
bool print_stats = piroParams->get("Print Convergence Stats", true);
if (print_stats) {
static int totalNewtonIters=0;
static int totalKrylovIters=0;
static int stepNum=0;
int NewtonIters = piroParams->sublist("NOX").
sublist("Output").get("Nonlinear Iterations", -1000);
int KrylovIters = linsys->getLinearItersTotal() - totalKrylovIters;
int lastSolveKrylovIters = linsys->getLinearItersLastSolve();
totalNewtonIters += NewtonIters;
totalKrylovIters += KrylovIters;
stepNum++;
utils.out() << "Convergence Stats: for step #" << stepNum << " : Newton, Krylov, Kr/Ne; LastKrylov, LastTol: "
<< NewtonIters << " " << KrylovIters << " "
<< (double) KrylovIters / (double) NewtonIters << " "
<< lastSolveKrylovIters << " " << linsys->getAchievedTol() << std::endl;
if (stepNum > 1)
utils.out() << "Convergence Stats: running total: Newton, Krylov, Kr/Ne, Kr/Step: "
<< totalNewtonIters << " " << totalKrylovIters << " "
<< (double) totalKrylovIters / (double) totalNewtonIters
<< " " << (double) totalKrylovIters / (double) stepNum << std::endl;
}
//
// Do Sensitivity Calc, if requested. See 3 main steps
//
// Set inargs and outargs
EpetraExt::ModelEvaluator::InArgs model_inargs = model->createInArgs();
EpetraExt::ModelEvaluator::OutArgs model_outargs = model->createOutArgs();
model_inargs.set_x(finalSolution);
// We make different choices for layouts of df/dp, dg/dx depending on
// whether we are doing forward or adjoint sensitivities
std::string sensitivity_method = piroParams->get("Sensitivity Method",
"Forward");
bool do_sens = false;
for (int i=0; i<num_p; i++) {
// p
model_inargs.set_p(i, inArgs.get_p(i));
// df/dp
do_sens = false;
for (int j=0; j<num_g; j++) {
if (!outArgs.supports(OUT_ARG_DgDp, j, i).none() &&
!outArgs.get_DgDp(j,i).isEmpty()) {
do_sens = true;
// This code does not work with non-empty p_indexes. The reason is
// each p_indexes could theoretically be different for each g.
// We would then need to make one df/dp for all the chosen p's
// and then index into them properly below. Note that the number of
// columns in df/dp should be the number of chosen p's, not the total
// number of p's.
if (outArgs.get_DgDp(j,i).getMultiVector() != Teuchos::null) {
Teuchos::Array<int> p_indexes =
outArgs.get_DgDp(j,i).getDerivativeMultiVector().getParamIndexes();
TEUCHOS_TEST_FOR_EXCEPTION(p_indexes.size() > 0,
Teuchos::Exceptions::InvalidParameter,
std::endl <<
"Piro::Epetra::NOXSolver::evalModel(): " <<
"Non-empty paramIndexes for dg/dp(" << i << "," <<
j << ") is not currently supported." << std::endl);
}
}
}
if (do_sens) {
Teuchos::RCP<const Epetra_Map> p_map = model->get_p_map(i);
Teuchos::RCP<const Epetra_Map> f_map = model->get_f_map();
int num_params = p_map->NumGlobalElements();
int num_resids = f_map->NumGlobalElements();
bool p_dist = p_map->DistributedGlobal();
bool f_dist = f_map->DistributedGlobal();
DerivativeSupport ds = model_outargs.supports(OUT_ARG_DfDp,i);
// Determine which layout to use for df/dp. Ideally one would look
// at num_params, num_resids, what is supported by the underlying
// model evaluator, and the sensitivity method, and make the best
// choice to minimze the number of solves. However this choice depends
// also on what layout of dg/dx is supported (e.g., if only the operator
// form is supported for forward sensitivities, then df/dp must be
// DERIV_MV_BY_COL). For simplicity, we order the conditional tests
// to get the right layout in most situations.
DerivativeLayout dfdp_layout;
if (sensitivity_method == "Forward") {
if (ds.supports(DERIV_MV_BY_COL) && !p_dist)
dfdp_layout = COL;
else if (ds.supports(DERIV_TRANS_MV_BY_ROW) && !f_dist)
dfdp_layout = ROW;
else if (ds.supports(DERIV_LINEAR_OP))
dfdp_layout = OP;
else
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"For df/dp(" << i <<") with forward sensitivities, " <<
"underlying ModelEvaluator must support DERIV_LINEAR_OP, " <<
"DERIV_MV_BY_COL with p not distributed, or "
"DERIV_TRANS_MV_BY_ROW with f not distributed." <<
std::endl);
}
else if (sensitivity_method == "Adjoint") {
if (ds.supports(DERIV_LINEAR_OP))
dfdp_layout = OP;
else if (ds.supports(DERIV_TRANS_MV_BY_ROW) && !f_dist)
dfdp_layout = ROW;
else if (ds.supports(DERIV_MV_BY_COL) && !p_dist)
dfdp_layout = COL;
else
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"For df/dp(" << i <<") with adjoint sensitivities, " <<
"underlying ModelEvaluator must support DERIV_LINEAR_OP, " <<
"DERIV_MV_BY_COL with p not distributed, or "
"DERIV_TRANS_MV_BY_ROW with f not distributed." <<
std::endl);
}
else
TEUCHOS_TEST_FOR_EXCEPTION(true,
Teuchos::Exceptions::InvalidParameter,
std::endl <<
"Piro::Epetra::NOXSolver::evalModel(): " <<
"Unknown sensitivity method" << sensitivity_method <<
". Valid choices are \"Forward\" and \"Adjoint\"."
<< std::endl);
if (dfdp_layout == COL) {
Teuchos::RCP<Epetra_MultiVector> dfdp =
Teuchos::rcp(new Epetra_MultiVector(*f_map, num_params));
// Teuchos::Array<int> p_indexes =
// outArgs.get_DgDp(i,0).getDerivativeMultiVector().getParamIndexes();
// EpetraExt::ModelEvaluator::DerivativeMultiVector
// dmv_dfdp(dfdp, DERIV_MV_BY_COL, p_indexes);
EpetraExt::ModelEvaluator::DerivativeMultiVector
dmv_dfdp(dfdp, DERIV_MV_BY_COL);
model_outargs.set_DfDp(i,dmv_dfdp);
}
else if (dfdp_layout == ROW) {
Teuchos::RCP<Epetra_MultiVector> dfdp =
Teuchos::rcp(new Epetra_MultiVector(*p_map, num_resids));
// Teuchos::Array<int> p_indexes =
// outArgs.get_DgDp(i,0).getDerivativeMultiVector().getParamIndexes();
// EpetraExt::ModelEvaluator::DerivativeMultiVector
// dmv_dfdp(dfdp, DERIV_TRANS_MV_BY_ROW, p_indexes);
EpetraExt::ModelEvaluator::DerivativeMultiVector
dmv_dfdp(dfdp, DERIV_TRANS_MV_BY_ROW);
model_outargs.set_DfDp(i,dmv_dfdp);
}
else if (dfdp_layout == OP) {
Teuchos::RCP<Epetra_Operator> dfdp_op = model->create_DfDp_op(i);
TEUCHOS_TEST_FOR_EXCEPTION(
dfdp_op == Teuchos::null, std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"Needed df/dp operator (" << i << ") is null!" << std::endl);
model_outargs.set_DfDp(i,dfdp_op);
}
}
}
for (int j=0; j<num_g; j++) {
// g
Teuchos::RCP<Epetra_Vector> g_out = outArgs.get_g(j);
if (g_out != Teuchos::null) {
g_out->PutScalar(0.0);
model_outargs.set_g(j, g_out);
}
// dg/dx
do_sens = false;
for (int i=0; i<num_p; i++) {
Teuchos::RCP<Epetra_MultiVector> dgdp_out;
if (!outArgs.supports(OUT_ARG_DgDp, j, i).none() &&
!outArgs.get_DgDp(j,i).isEmpty()) {
do_sens = true;
}
}
if (do_sens) {
Teuchos::RCP<const Epetra_Map> g_map = model->get_g_map(j);
Teuchos::RCP<const Epetra_Map> x_map = model->get_x_map();
int num_responses = g_map->NumGlobalElements();
int num_solution = x_map->NumGlobalElements();
bool g_dist = g_map->DistributedGlobal();
bool x_dist = x_map->DistributedGlobal();
DerivativeSupport ds = model_outargs.supports(OUT_ARG_DgDx,j);
DerivativeLayout dgdx_layout;
if (sensitivity_method == "Forward") {
if (ds.supports(DERIV_LINEAR_OP))
dgdx_layout = OP;
else if (ds.supports(DERIV_MV_BY_COL) && !x_dist)
dgdx_layout = COL;
else if (ds.supports(DERIV_TRANS_MV_BY_ROW) && !g_dist)
dgdx_layout = ROW;
else
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"For dg/dx(" << j <<") with forward sensitivities, " <<
"underlying ModelEvaluator must support DERIV_LINEAR_OP, " <<
"DERIV_MV_BY_COL with x not distributed, or "
"DERIV_TRANS_MV_BY_ROW with g not distributed." <<
std::endl);
}
else if (sensitivity_method == "Adjoint") {
if (ds.supports(DERIV_TRANS_MV_BY_ROW) && !g_dist)
dgdx_layout = ROW;
else if (ds.supports(DERIV_MV_BY_COL) && !x_dist)
dgdx_layout = COL;
else if (ds.supports(DERIV_LINEAR_OP))
dgdx_layout = OP;
else
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"For dg/dx(" << j <<") with adjoint sensitivities, " <<
"underlying ModelEvaluator must support DERIV_LINEAR_OP, " <<
"DERIV_MV_BY_COL with x not distributed, or "
"DERIV_TRANS_MV_BY_ROW with g not distributed." <<
std::endl);
}
else
TEUCHOS_TEST_FOR_EXCEPTION(true,
Teuchos::Exceptions::InvalidParameter,
std::endl <<
"Piro::Epetra::NOXSolver::evalModel(): " <<
"Unknown sensitivity method" << sensitivity_method <<
". Valid choices are \"Forward\" and \"Adjoint\"."
<< std::endl);
if (dgdx_layout == OP) {
Teuchos::RCP<Epetra_Operator> dgdx_op = model->create_DgDx_op(j);
TEUCHOS_TEST_FOR_EXCEPTION(
dgdx_op == Teuchos::null, std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"Needed dg/dx operator (" << j << ") is null!" << std::endl);
model_outargs.set_DgDx(j,dgdx_op);
}
else if (dgdx_layout == ROW) {
Teuchos::RCP<Epetra_MultiVector> dgdx =
Teuchos::rcp(new Epetra_MultiVector(*x_map, num_responses));
EpetraExt::ModelEvaluator::DerivativeMultiVector
dmv_dgdx(dgdx, DERIV_TRANS_MV_BY_ROW);
model_outargs.set_DgDx(j,dmv_dgdx);
}
else if (dgdx_layout == COL) {
Teuchos::RCP<Epetra_MultiVector> dgdx =
Teuchos::rcp(new Epetra_MultiVector(*g_map, num_solution));
EpetraExt::ModelEvaluator::DerivativeMultiVector
dmv_dgdx(dgdx, DERIV_MV_BY_COL);
model_outargs.set_DgDx(j,dmv_dgdx);
}
// dg/dp
for (int i=0; i<num_p; i++) {
if (!outArgs.supports(OUT_ARG_DgDp,j,i).none()) {
Derivative dgdp = outArgs.get_DgDp(j,i);
if (dgdp.getLinearOp() != Teuchos::null) {
Teuchos::RCP<const Epetra_Map> g_map = model->get_g_map(j);
Teuchos::RCP<const Epetra_Map> p_map = model->get_p_map(i);
int num_responses = g_map->NumGlobalElements();
int num_params = p_map->NumGlobalElements();
bool g_dist = g_map->DistributedGlobal();
bool p_dist = p_map->DistributedGlobal();
DerivativeSupport ds = model_outargs.supports(OUT_ARG_DgDp,j,i);
if (ds.supports(DERIV_LINEAR_OP)) {
Teuchos::RCP<Epetra_Operator> dgdp_op =
model->create_DgDp_op(j,i);
TEUCHOS_TEST_FOR_EXCEPTION(
dgdp_op == Teuchos::null, std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"Needed dg/dp operator (" << j << "," << i << ") is null!" <<
std::endl);
model_outargs.set_DgDp(j,i,dgdp_op);
}
else if (ds.supports(DERIV_MV_BY_COL) && !p_dist) {
Teuchos::RCP<Epetra_MultiVector> dgdp =
Teuchos::rcp(new Epetra_MultiVector(*g_map, num_params));
EpetraExt::ModelEvaluator::DerivativeMultiVector
dmv_dgdp(dgdp, DERIV_MV_BY_COL);
model_outargs.set_DgDp(j,i,dmv_dgdp);
}
else if (ds.supports(DERIV_TRANS_MV_BY_ROW) && !g_dist) {
Teuchos::RCP<Epetra_MultiVector> dgdp =
Teuchos::rcp(new Epetra_MultiVector(*p_map, num_responses));
EpetraExt::ModelEvaluator::DerivativeMultiVector
dmv_dgdp(dgdp, DERIV_TRANS_MV_BY_ROW);
model_outargs.set_DgDp(j,i,dmv_dgdp);
}
else
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"For dg/dp(" << j << "," << i <<
") with operator sensitivities, "<<
"underlying ModelEvaluator must support DERIV_LINEAR_OP, " <<
"DERIV_MV_BY_COL with p not distributed, or "
"DERIV_TRANS_MV_BY_ROW with g not distributed." <<
std::endl);
}
else
model_outargs.set_DgDp(j,i,outArgs.get_DgDp(j,i));
}
}
}
}
// (1) Calculate g, df/dp, dg/dp, dg/dx
model->evalModel(model_inargs, model_outargs);
// Ensure Jacobian is up-to-date
if (do_sens)
grp->computeJacobian();
// Handle operator dg/dp
for (int i=0; i<num_p; i++) {
for (int j=0; j<num_g; j++) {
if (!outArgs.supports(OUT_ARG_DgDp, j, i).none()) {
if (outArgs.get_DgDp(j,i).getLinearOp() != Teuchos::null) {
Teuchos::RCP<Epetra_Operator> op =
outArgs.get_DgDp(j,i).getLinearOp();
Teuchos::RCP<SensitivityOperator> sens_op =
Teuchos::rcp_dynamic_cast<SensitivityOperator>(op);
sens_op->setup(model_outargs.get_DfDp(i),
model_outargs.get_DgDx(j),
model_outargs.get_DgDp(j,i),
piroParams, grp, tls_strategy);
}
}
}
}
if (sensitivity_method == "Forward") {
for (int i=0; i<num_p; i++) {
// See if there are any forward sensitivities we need to do
// that aren't handled by the operator
do_sens = false;
for (int j=0; j<num_g; j++) {
if (!outArgs.supports(OUT_ARG_DgDp, j, i).none()) {
if (outArgs.get_DgDp(j,i).getMultiVector() != Teuchos::null)
do_sens = true;
}
}
if (!do_sens)
continue;
if (!model_outargs.supports(OUT_ARG_DfDp, i).none()) {
TEUCHOS_TEST_FOR_EXCEPTION(
model_outargs.get_DfDp(i).getLinearOp()!=Teuchos::null,
std::logic_error,
std::endl <<"Piro::Epetra::NOXSolver::evalModel(): " <<
"Can\'t use df/dp operator " << i << " with non-operator " <<
"forward sensitivities." << std::endl);
Teuchos::RCP<Epetra_MultiVector> dfdp =
model_outargs.get_DfDp(i).getMultiVector();
if (dfdp != Teuchos::null) {
int num_cols = dfdp->NumVectors();
// (2) Calculate dx/dp multivector from -(J^{-1}*df/dp)
Teuchos::RCP<Epetra_MultiVector> dxdp =
Teuchos::rcp(new Epetra_MultiVector(dfdp->Map(), num_cols));
NOX::Epetra::MultiVector dfdp_nox(
dfdp, NOX::DeepCopy,
NOX::Epetra::MultiVector::CreateView);
NOX::Epetra::MultiVector dxdp_nox(
dxdp, NOX::DeepCopy,
NOX::Epetra::MultiVector::CreateView);
grp->applyJacobianInverseMultiVector(*piroParams, dfdp_nox, dxdp_nox);
dxdp_nox.scale(-1.0);
// (3) Calculate dg/dp = dg/dx*dx/dp + dg/dp
for (int j=0; j<num_g; j++) {
if (!outArgs.supports(OUT_ARG_DgDp, j, i).none()) {
Teuchos::RCP<Epetra_MultiVector> dgdp_out =
outArgs.get_DgDp(j,i).getMultiVector();
if (dgdp_out != Teuchos::null) {
Derivative dgdx_dv = model_outargs.get_DgDx(j);
Teuchos::RCP<Epetra_Operator> dgdx_op = dgdx_dv.getLinearOp();
Teuchos::RCP<Epetra_MultiVector> dgdx =
dgdx_dv.getMultiVector();
Derivative dfdp_dv = model_outargs.get_DfDp(i);
EDerivativeMultiVectorOrientation dgdp_orient =
outArgs.get_DgDp(j,i).getMultiVectorOrientation();
if (dgdx_op != Teuchos::null) {
bool transpose = false;
if (dgdp_orient == DERIV_TRANS_MV_BY_ROW)
transpose = true;
Epetra_MultiVector tmp(dgdx_op->OperatorRangeMap(),
dxdp->NumVectors());
dgdx_op->Apply(*dxdp, tmp);
if (transpose) {
TEUCHOS_TEST_FOR_EXCEPTION(
dgdp_out->Map().DistributedGlobal(),
std::logic_error,
std::endl <<
"Piro::Epetra::NOXSolver::evalModel(): " <<
"Can\'t handle special case: " <<
" dg/dx operator, " <<
" transposed, distributed dg/dp. " << std::endl);
for (int j=0; j<dgdp_out->NumVectors(); j++)
for (int i=0; i<dgdp_out->MyLength(); i++)
(*dgdp_out)[j][i] += tmp[i][j];
}
else
dgdp_out->Update(1.0, tmp, 1.0);
}
else {
Teuchos::RCP<Epetra_MultiVector> arg1, arg2;
EDerivativeMultiVectorOrientation dfdp_orient =
model_outargs.get_DfDp(i).getMultiVectorOrientation();
EDerivativeMultiVectorOrientation dgdx_orient =
model_outargs.get_DgDx(j).getMultiVectorOrientation();
char flag1, flag2;
if (dgdp_orient == DERIV_MV_BY_COL) {
arg1 = dgdx;
arg2 = dxdp;
if (dgdx_orient == DERIV_MV_BY_COL)
flag1 = 'N';
else
flag1 = 'T';
if (dfdp_orient == DERIV_MV_BY_COL)
flag2 = 'N';
else
flag2 = 'T';
}
else {
arg1 = dxdp;
arg2 = dgdx;
if (dfdp_orient == DERIV_MV_BY_COL)
flag1 = 'T';
else
flag1 = 'N';
if (dgdx_orient == DERIV_MV_BY_COL)
flag2 = 'T';
else
flag2 = 'N';
}
dgdp_out->Multiply(flag1, flag2, 1.0, *arg1, *arg2, 1.0);
}
}
}
}
}
}
}
}
else if (sensitivity_method == "Adjoint") {
// Hold on to original Jacobian operator
Teuchos::RCP<NOX::Epetra::LinearSystem> linSys = grp->getLinearSystem();
Teuchos::RCP<Epetra_Operator> jac = linSys->getJacobianOperator();
tls_strategy->createJacobianTranspose();
const NOX::Epetra::Vector& x_nox =
dynamic_cast<const NOX::Epetra::Vector&>(grp->getX());
tls_strategy->createTransposePreconditioner(x_nox, *piroParams);
for (int j=0; j<num_g; j++) {
// See if there are any forward sensitivities we need to do
// that aren't handled by the operator
do_sens = false;
for (int i=0; i<num_p; i++) {
if (!outArgs.supports(OUT_ARG_DgDp, j, i).none()) {
if (outArgs.get_DgDp(j,i).getMultiVector() != Teuchos::null)
do_sens = true;
}
}
if (!do_sens)
continue;
if (!model_outargs.supports(OUT_ARG_DgDx, j).none()) {
TEUCHOS_TEST_FOR_EXCEPTION(
model_outargs.get_DgDx(j).getLinearOp()!=Teuchos::null,
std::logic_error,
std::endl << "Piro::Epetra::NOXSolver::evalModel(): " <<
"Can\'t use dg/dx operator " << j << " with non-operator " <<
"adjoint sensitivities." << std::endl);
Teuchos::RCP<Epetra_MultiVector> dgdx =
model_outargs.get_DgDx(j).getMultiVector();
if (dgdx != Teuchos::null) {
int num_cols = dgdx->NumVectors();
// (2) Calculate xbar multivector from -(J^{-T}*dg/dx)
Teuchos::RCP<Epetra_MultiVector> xbar =
Teuchos::rcp(new Epetra_MultiVector(dgdx->Map(), num_cols));
for (int col=0; col<num_cols; col++) {
Teuchos::RCP<Epetra_Vector> gx =
Teuchos::rcp((*dgdx)(col),false);
Teuchos::RCP<Epetra_Vector> xb =
Teuchos::rcp((*xbar)(col),false);
NOX::Epetra::Vector dgdx_nox(
gx, NOX::Epetra::Vector::CreateView, NOX::DeepCopy);
NOX::Epetra::Vector xbar_nox(
xb, NOX::Epetra::Vector::CreateView, NOX::DeepCopy);
// Solve
tls_strategy->applyJacobianTransposeInverse(
*piroParams, dgdx_nox, xbar_nox);
}
xbar->Scale(-1.0);
// (3) Calculate dg/dp^T = df/dp^T*xbar + dg/dp^T
for (int i=0; i<num_p; i++) {
if (!outArgs.supports(OUT_ARG_DgDp, j, i).none()) {
Teuchos::RCP<Epetra_MultiVector> dgdp_out =
outArgs.get_DgDp(j,i).getMultiVector();
if (dgdp_out != Teuchos::null) {
Derivative dfdp_dv = model_outargs.get_DfDp(i);
Teuchos::RCP<Epetra_Operator> dfdp_op = dfdp_dv.getLinearOp();
Teuchos::RCP<Epetra_MultiVector> dfdp =
dfdp_dv.getMultiVector();
Derivative dgdx_dv = model_outargs.get_DgDx(j);
EDerivativeMultiVectorOrientation dgdp_orient =
outArgs.get_DgDp(j,i).getMultiVectorOrientation();
if (dfdp_op != Teuchos::null) {
bool transpose = false;
if (dgdp_orient == DERIV_MV_BY_COL)
transpose = true;
Epetra_MultiVector tmp(dfdp_op->OperatorDomainMap(),
xbar->NumVectors());
dfdp_op->SetUseTranspose(true);
dfdp_op->Apply(*xbar, tmp);
dfdp_op->SetUseTranspose(false);
if (transpose) {
TEUCHOS_TEST_FOR_EXCEPTION(
dgdp_out->Map().DistributedGlobal(),
std::logic_error,
std::endl <<
"Piro::Epetra::NOXSolver::evalModel(): " <<
"Can\'t handle special case: " <<
" df/dp operator, " <<
" transposed, distributed dg/dp. " << std::endl);
for (int j=0; j<dgdp_out->NumVectors(); j++)
for (int i=0; i<dgdp_out->MyLength(); i++)
(*dgdp_out)[j][i] += tmp[i][j];
}
else
dgdp_out->Update(1.0, tmp, 1.0);
}
else {
Teuchos::RCP<Epetra_MultiVector> arg1, arg2;
EDerivativeMultiVectorOrientation dgdp_orient =
model_outargs.get_DgDp(j,i).getMultiVectorOrientation();
EDerivativeMultiVectorOrientation dfdp_orient =
model_outargs.get_DfDp(i).getMultiVectorOrientation();
EDerivativeMultiVectorOrientation dgdx_orient =
model_outargs.get_DgDx(j).getMultiVectorOrientation();
char flag1, flag2;
if (dgdp_orient == DERIV_TRANS_MV_BY_ROW) {
arg1 = dfdp;
arg2 = xbar;
if (dfdp_orient == DERIV_TRANS_MV_BY_ROW)
flag1 = 'N';
else
flag1 = 'T';
if (dgdx_orient == DERIV_TRANS_MV_BY_ROW)
flag2 = 'N';
else
flag2 = 'T';
}
else {
arg1 = xbar;
arg2 = dfdp;
if (dgdx_orient == DERIV_TRANS_MV_BY_ROW)
flag1 = 'T';
else
flag1 = 'N';
if (dfdp_orient == DERIV_TRANS_MV_BY_ROW)
flag2 = 'T';
else
flag2 = 'N';
}
dgdp_out->Multiply(flag1, flag2, 1.0, *arg1, *arg2, 1.0);
}
}
}
}
}
}
}
// Set original operators in linear system
jac->SetUseTranspose(false);
linSys->setJacobianOperatorForSolve(jac);
linSys->destroyPreconditioner();
}
if (status == NOX::StatusTest::Converged)
if (observer != Teuchos::null)
observer->observeSolution(*finalSolution);
// return the final solution as an additional g-vector, if requested
Teuchos::RCP<Epetra_Vector> gx_out = outArgs.get_g(num_g);
if (gx_out != Teuchos::null) *gx_out = *finalSolution;
// Clear RCPs to parameter vectors
for (int i=0; i<num_p; i++)
interface->inargs_set_p(Teuchos::null, i);
}