本文整理汇总了C++中nox::abstract::MultiVector::update方法的典型用法代码示例。如果您正苦于以下问题：C++ MultiVector::update方法的具体用法？C++ MultiVector::update怎么用？C++ MultiVector::update使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类nox::abstract::MultiVector的用法示例。
在下文中一共展示了MultiVector::update方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: if
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);
}示例2: getDX
NOX::Abstract::Group::ReturnType
LOCA::MultiContinuation::ConstraintInterfaceMVDX::addDX(
Teuchos::ETransp transb,
double alpha,
const NOX::Abstract::MultiVector::DenseMatrix& b,
double beta,
NOX::Abstract::MultiVector& result_x) const
{
if (!isDXZero()) {
const NOX::Abstract::MultiVector* dgdx = getDX();
result_x.update(transb, alpha, *dgdx, b, beta);
}
else
result_x.scale(beta);
return NOX::Abstract::Group::Ok;
}示例3: u
void
LOCA::BorderedSolver::HouseholderQR::applyHouseholderVector(
const NOX::Abstract::MultiVector::DenseMatrix& V1,
const NOX::Abstract::MultiVector& V2,
double beta,
NOX::Abstract::MultiVector::DenseMatrix& A1,
NOX::Abstract::MultiVector& A2)
{
int nColsA = A2.numVectors();
// Compute u = V2^T * A2
NOX::Abstract::MultiVector::DenseMatrix u(1, nColsA);
A2.multiply(1.0, V2, u);
// Compute u = u + V1^T * A_P
u.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, 1.0, V1, A1, 1.0);
// Compute A1 = A1 - b*V1*u
A1.multiply(Teuchos::NO_TRANS, Teuchos::NO_TRANS, -beta, V1, u, 1.0);
// Compute A2 = A2 - b*V2*u
A2.update(Teuchos::NO_TRANS, -beta, V2, u, 1.0);
}