void
LOCA::Extended::MultiVector::multiply(
double alpha,
const LOCA::Extended::MultiVector& y,
NOX::Abstract::MultiVector::DenseMatrix& b) const
{
// Verify dimensions are consistent
if (y.numMultiVecRows != numMultiVecRows || y.numColumns != b.numRows() ||
y.numScalarRows != numScalarRows || numColumns != b.numCols())
globalData->locaErrorCheck->throwError(
"LOCA::Extended::MultiVector::multiply()",
"Size of supplied multivector/matrix is incompatible with this multivector");
// Zero out b
b.putScalar(0.0);
// Create temporary matrix to hold product for each multivec
NOX::Abstract::MultiVector::DenseMatrix tmp(b);
// Compute and sum products for each multivec
for (int i=0; i<numMultiVecRows; i++) {
multiVectorPtrs[i]->multiply(alpha, *(y.multiVectorPtrs[i]), tmp);
b += tmp;
}
// Compute and add in product for scalars
if (numScalarRows > 0)
b.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, alpha, *y.scalarsPtr,
*scalarsPtr, 1.0);
}
void
LOCA::BorderedSolver::HouseholderQR::applyCompactWY(
const NOX::Abstract::MultiVector::DenseMatrix& Y1,
const NOX::Abstract::MultiVector& Y2,
const NOX::Abstract::MultiVector::DenseMatrix& T,
NOX::Abstract::MultiVector::DenseMatrix& X1,
NOX::Abstract::MultiVector& X2,
bool isZeroX1, bool isZeroX2,
bool useTranspose) const
{
if (isZeroX1 && isZeroX2) {
X1.putScalar(0.0);
X2.init(0.0);
return;
}
int m = Y2.numVectors();
Teuchos::ETransp T_flag;
if (useTranspose)
T_flag = Teuchos::TRANS;
else
T_flag = Teuchos::NO_TRANS;
NOX::Abstract::MultiVector::DenseMatrix tmp(m, X2.numVectors());
// Compute Y1^T*X1 + Y2^T*X2
if (!isZeroX2)
X2.multiply(1.0, Y2, tmp);
// Opportunity for optimization here since Y1 is a lower-triangular
// matrix with unit diagonal
if (!isZeroX2 && !isZeroX1)
tmp.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, 1.0, Y1, X1, 1.0);
else if (!isZeroX1)
tmp.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, 1.0, Y1, X1, 0.0);
// Compute op(T)*(Y1^T*X1 + Y2^T*X2)
dblas.TRMM(Teuchos::LEFT_SIDE, Teuchos::UPPER_TRI, T_flag,
Teuchos::NON_UNIT_DIAG, tmp.numRows(), tmp.numCols(), 1.0,
T.values(), T.numRows(), tmp.values(), tmp.numRows());
// Compute X1 = X1 + Y1*op(T)*(Y1^T*X1 + Y2^T*X2)
// Opportunity for optimization here since Y1 is a lower-triangular
// matrix with unit diagonal
if (isZeroX1)
X1.multiply(Teuchos::NO_TRANS, Teuchos::NO_TRANS, 1.0, Y1, tmp, 0.0);
else
X1.multiply(Teuchos::NO_TRANS, Teuchos::NO_TRANS, 1.0, Y1, tmp, 1.0);
// Compute X2 = X2 + Y1*op(T)*(Y1^T*X1 + Y2^T*X2)
if (isZeroX2)
X2.update(Teuchos::NO_TRANS, 1.0, Y2, tmp, 0.0);
else
X2.update(Teuchos::NO_TRANS, 1.0, Y2, tmp, 1.0);
}
NOX::Abstract::Group::ReturnType
LOCA::MultiContinuation::CompositeConstraint::multiplyDX(
double alpha,
const NOX::Abstract::MultiVector& input_x,
NOX::Abstract::MultiVector::DenseMatrix& result_p) const
{
std::string callingFunction =
"LOCA::MultiContinuation::CompositeConstraint::multiplyDX()";
NOX::Abstract::Group::ReturnType status;
NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;
// If dg/dx is zero for every constraint, result_p is zero
if (isDXZero()) {
result_p.putScalar(0.0);
return finalStatus;
}
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> result_p_sub;
int num_rows;
int num_cols = result_p.numCols();
for (int i=0; i<numConstraintObjects; i++) {
num_rows = constraintPtrs[i]->numConstraints();
// if dg/dx is zero for this constraint, set corresponding entries of
// result_p to zero
if (constraintPtrs[i]->isDXZero()) {
for (int j=0; j<num_rows; j++)
for (int k=0; k<num_cols; k++)
result_p(indices[i][j],k) = 0.0;
}
else {
// Create a sub view of rows indices[i][0] -- indices[i][end]
// of result_p
result_p_sub =
Teuchos::rcp(new NOX::Abstract::MultiVector::DenseMatrix(Teuchos::View,
result_p,
num_rows,
num_cols,
indices[i][0],
0));
status = constraintPtrs[i]->multiplyDX(alpha, input_x,
*result_p_sub);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(
status,
finalStatus,
callingFunction);
}
}
return finalStatus;
}
NOX::Abstract::Group::ReturnType
LOCA::BorderedSolver::Nested::applyInverseTranspose(
Teuchos::ParameterList& params,
const NOX::Abstract::MultiVector* F,
const NOX::Abstract::MultiVector::DenseMatrix* G,
NOX::Abstract::MultiVector& X,
NOX::Abstract::MultiVector::DenseMatrix& Y) const
{
bool isZeroF = (F == NULL);
bool isZeroG = (G == NULL);
if (isZeroF && isZeroG) {
X.init(0.0);
Y.putScalar(0.0);
}
int num_cols = X.numVectors();
Teuchos::RCP<NOX::Abstract::MultiVector> FF;
if (!isZeroF)
FF = unbordered_grp->getX().createMultiVector(num_cols);
NOX::Abstract::MultiVector::DenseMatrix GG(myWidth, num_cols);
GG.putScalar(0.0);
if (!isZeroF) {
NOX::Abstract::MultiVector::DenseMatrix GG1(Teuchos::View, GG,
underlyingWidth, num_cols,
0, 0);
grp->extractSolutionComponent(*F, *FF);
grp->extractParameterComponent(false, *F, GG1);
}
if (!isZeroG) {
NOX::Abstract::MultiVector::DenseMatrix GG2(Teuchos::View, GG,
numConstraints, num_cols,
underlyingWidth, 0);
GG2.assign(*G);
}
Teuchos::RCP<NOX::Abstract::MultiVector> XX =
unbordered_grp->getX().createMultiVector(num_cols);
NOX::Abstract::MultiVector::DenseMatrix YY(myWidth, num_cols);
NOX::Abstract::MultiVector::DenseMatrix YY1(Teuchos::View, YY,
underlyingWidth, num_cols,
0, 0);
NOX::Abstract::MultiVector::DenseMatrix YY2(Teuchos::View, YY,
numConstraints, num_cols,
underlyingWidth, 0);
NOX::Abstract::Group::ReturnType status =
solver->applyInverseTranspose(params, FF.get(), &GG, *XX, YY);
Y.assign(YY2);
grp->loadNestedComponents(*XX, YY1, X);
return status;
}
NOX::Abstract::Group::ReturnType
LOCA::MultiContinuation::ConstraintInterfaceMVDX::multiplyDX(
double alpha,
const NOX::Abstract::MultiVector& input_x,
NOX::Abstract::MultiVector::DenseMatrix& result_p) const
{
if (!isDXZero()) {
const NOX::Abstract::MultiVector* dgdx = getDX();
input_x.multiply(alpha, *dgdx, result_p);
}
else
result_p.putScalar(0.0);
return NOX::Abstract::Group::Ok;
}
NOX::Abstract::Group::ReturnType
LOCA::BorderedSolver::LowerTriangularBlockElimination::
solve(Teuchos::ParameterList& params,
const LOCA::BorderedSolver::AbstractOperator& op,
const LOCA::MultiContinuation::ConstraintInterface& B,
const NOX::Abstract::MultiVector::DenseMatrix& C,
const NOX::Abstract::MultiVector* F,
const NOX::Abstract::MultiVector::DenseMatrix* G,
NOX::Abstract::MultiVector& X,
NOX::Abstract::MultiVector::DenseMatrix& Y) const
{
string callingFunction =
"LOCA::BorderedSolver::LowerTriangularBlockElimination::solve()";
NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;
NOX::Abstract::Group::ReturnType status;
// Determine if X or Y is zero
bool isZeroF = (F == NULL);
bool isZeroG = (G == NULL);
bool isZeroB = B.isDXZero();
bool isZeroX = isZeroF;
bool isZeroY = isZeroG && (isZeroB || isZeroX);
// First compute X
if (isZeroX)
X.init(0.0);
else {
// Solve X = J^-1 F, note F must be nonzero
status = op.applyInverse(params, *F, X);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// Now compute Y
if (isZeroY)
Y.putScalar(0.0);
else {
// Compute G - B^T*X and store in Y
if (isZeroG)
B.multiplyDX(-1.0, X, Y);
else {
Y.assign(*G);
if (!isZeroB && !isZeroX) {
NOX::Abstract::MultiVector::DenseMatrix T(Y.numRows(),Y.numCols());
B.multiplyDX(1.0, X, T);
Y -= T;
}
}
// Overwrite Y with Y = C^-1 * (G - B^T*X)
NOX::Abstract::MultiVector::DenseMatrix M(C);
int *ipiv = new int[M.numRows()];
Teuchos::LAPACK<int,double> L;
int info;
L.GETRF(M.numRows(), M.numCols(), M.values(), M.stride(), ipiv, &info);
if (info != 0) {
status = NOX::Abstract::Group::Failed;
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(
status,
finalStatus,
callingFunction);
}
L.GETRS('N', M.numRows(), Y.numCols(), M.values(), M.stride(), ipiv,
Y.values(), Y.stride(), &info);
delete [] ipiv;
if (info != 0) {
status = NOX::Abstract::Group::Failed;
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(
status,
finalStatus,
callingFunction);
}
}
return finalStatus;
}
void
LOCA::BorderedSolver::HouseholderQR::computeQR(
const NOX::Abstract::MultiVector::DenseMatrix& C,
const NOX::Abstract::MultiVector& B,
bool use_c_transpose,
NOX::Abstract::MultiVector::DenseMatrix& Y1,
NOX::Abstract::MultiVector& Y2,
NOX::Abstract::MultiVector::DenseMatrix& T,
NOX::Abstract::MultiVector::DenseMatrix& R)
{
double beta;
int m = B.numVectors();
// Initialize
Y1.putScalar(0.0);
T.putScalar(0.0);
Y2 = B;
if (use_c_transpose) {
for (int i=0; i<m; i++)
for (int j=0; j<m; j++)
R(i,j) = C(j,i); // Copy transpose of C into R
}
else
R.assign(C);
// A temporary vector
Teuchos::RCP<NOX::Abstract::MultiVector> v2 = Y2.clone(1);
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> v1;
Teuchos::RCP<NOX::Abstract::MultiVector> h2;
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> h1;
Teuchos::RCP<NOX::Abstract::MultiVector> y2;
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> y1;
Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> z;
std::vector<int> h_idx;
std::vector<int> y_idx;
y_idx.reserve(m);
for (int i=0; i<m; i++) {
// Create view of column i of Y1 starting at row i
v1 =
Teuchos::rcp(new NOX::Abstract::MultiVector::DenseMatrix(Teuchos::View,
Y1,
m-i,
1, i, i));
// Create view of columns i through m-1 of Y2
h_idx.resize(m-i);
for (unsigned int j=0; j<h_idx.size(); j++)
h_idx[j] = i+j;
h2 = Y2.subView(h_idx);
// Create view of columns i thru m-1 of R, starting at row i
h1 =
Teuchos::rcp(new NOX::Abstract::MultiVector::DenseMatrix(Teuchos::View,
R,
m-i,
m-i,
i, i));
if (i > 0) {
// Create view of columns 0 through i-1 of Y2
y_idx.push_back(i-1);
y2 = Y2.subView(y_idx);
// Create view of columns 0 through i-1 of Y1, starting at row i
y1 =
Teuchos::rcp(new NOX::Abstract::MultiVector::DenseMatrix(Teuchos::View,
Y1,
m-i,
i, i, 0));
// Create view of column i, row 0 through i-1 of T
z =
Teuchos::rcp(new NOX::Abstract::MultiVector::DenseMatrix(Teuchos::View,
T,
i,
1,
0, i));
}
// Compute Householder Vector
computeHouseholderVector(i, R, Y2, *v1, *v2, beta);
// Apply Householder reflection
applyHouseholderVector(*v1, *v2, beta, *h1, *h2);
// Copy v2 into Y2
Y2[i] = (*v2)[0];
T(i,i) = -beta;
if (i > 0) {
// Compute z = y2^T * v2
v2->multiply(1.0, *y2, *z);
// Compute z = -beta * (z + y1^T * v1)
z->multiply(Teuchos::TRANS, Teuchos::NO_TRANS, -beta, *y1, *v1, -beta);
// Compute z = T * z
dblas.TRMV(Teuchos::UPPER_TRI, Teuchos::NO_TRANS, Teuchos::NON_UNIT_DIAG,
i, T.values(), m, z->values(), 1);
}
}
}
