本文整理汇总了C++中nox::abstract::multivector::DenseMatrix::scale方法的典型用法代码示例。如果您正苦于以下问题：C++ DenseMatrix::scale方法的具体用法？C++ DenseMatrix::scale怎么用？C++ DenseMatrix::scale使用的例子？那么, 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::DenseMatrix的用法示例。
在下文中一共展示了DenseMatrix::scale方法的2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: computeConstraints
NOX::Abstract::Group::ReturnType
LOCA::TurningPoint::MinimallyAugmented::Constraint::
computeDP(const std::vector<int>& paramIDs,
NOX::Abstract::MultiVector::DenseMatrix& dgdp,
bool isValidG)
{
std::string callingFunction =
"LOCA::TurningPoint::MinimallyAugmented::Constraint::computeDP()";
NOX::Abstract::Group::ReturnType status;
NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;
// Compute sigma, w and v if necessary
if (!isValidConstraints) {
status = computeConstraints();
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// Compute -(w^T*J*v)_p
status = grpPtr->computeDwtJnDp(paramIDs, (*w_vector)[0], (*v_vector)[0],
dgdp, false);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
dgdp.scale(-1.0/sigma_scale);
// Set the first column of dgdp
dgdp(0,0) = constraints(0,0);
return finalStatus;
}示例2: ltC
//.........这里部分代码省略.........
Teuchos::RCP<NOX::Abstract::MultiVector> b =
result_x.subView(index_dp);
// verify underlying complex matrix is valid
if (!group->isComplex()) {
status = group->computeComplex(w);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// compute (J+iwB)(y+iz)_x [A b]
Teuchos::RCP<NOX::Abstract::MultiVector> tmp_real =
result_y.clone(NOX::ShapeCopy);
Teuchos::RCP<NOX::Abstract::MultiVector> tmp_real_sub =
tmp_real->subView(index_ip);
Teuchos::RCP<NOX::Abstract::MultiVector> tmp_imag =
result_y.clone(NOX::ShapeCopy);
Teuchos::RCP<NOX::Abstract::MultiVector> tmp_imag_sub =
tmp_imag->subView(index_ip);
tmp_real->init(0.0);
tmp_imag->init(0.0);
status = group->computeDCeDxa(*yVector, *zVector, w, result_x,
*CeRealVector, *CeImagVector, *tmp_real_sub,
*tmp_imag_sub);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
// compute [G+iH d(J+iwB)(y+iz)/dp iB(y+iz)] - [(J+iwB)_x[A b] 0+i0]
tmp_real->update(1.0, input_y, -1.0);
tmp_imag->update(1.0, input_z, -1.0);
// verify underlying complex matrix is valid
if (!group->isComplex()) {
status = group->computeComplex(w);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status,
finalStatus,
callingFunction);
}
// compute [C+iD e+if g+ih] = (J+iwB)^-1 (tmp_real + i tmp_imag)
status = group->applyComplexInverseMultiVector(params, *tmp_real, *tmp_imag,
result_y, result_z);
finalStatus =
globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
callingFunction);
Teuchos::RCP<NOX::Abstract::MultiVector> C =
result_y.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> D =
result_z.subView(index_input);
Teuchos::RCP<NOX::Abstract::MultiVector> e =
result_y.subView(index_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> f =
result_z.subView(index_dp);
Teuchos::RCP<NOX::Abstract::MultiVector> g =
result_y.subView(index_B);
Teuchos::RCP<NOX::Abstract::MultiVector> h =
result_z.subView(index_B);
// compute lambda = ((phi^T h)(phi^T C-u) - (phi^T g)(phi^T D-v)) /
// ((phi^T h)(phi^T e)-(phi^T g)(phi^T f))
NOX::Abstract::MultiVector::DenseMatrix ltC(1,m);
NOX::Abstract::MultiVector::DenseMatrix ltD(1,m);
double lte = hopfGroup->lTransNorm((*e)[0]);
double ltf = hopfGroup->lTransNorm((*f)[0]);
double ltg = hopfGroup->lTransNorm((*g)[0]);
double lth = hopfGroup->lTransNorm((*h)[0]);
double denom = lth*lte - ltg*ltf;
hopfGroup->lTransNorm(*C, ltC);
ltC -= input_w;
ltC.scale(lth);
hopfGroup->lTransNorm(*D, ltD);
ltD -= input_p;
result_p.assign(ltD);
result_p.scale(-ltg);
result_p += ltC;
result_p.scale(1.0/denom);
// compute omega = (phi^T D-v - (phi^T f)lambda)/(phi^T h)
result_w.assign(result_p);
result_w.scale(-ltf);
result_w += ltD;
result_w.scale(1.0/lth);
// compute A = A - b*lambda (remember A is a sub-view of result_x)
A->update(Teuchos::NO_TRANS, -1.0, *b, result_p, 1.0);
// compute C = C - e*lambda - g*omega (remember C is a sub-view of result_y)
C->update(Teuchos::NO_TRANS, -1.0, *e, result_p, 1.0);
C->update(Teuchos::NO_TRANS, -1.0, *g, result_w, 1.0);
// compute D = D - f*lambda - h*omega (remember D is a sub-view of result_z)
D->update(Teuchos::NO_TRANS, -1.0, *f, result_p, 1.0);
D->update(Teuchos::NO_TRANS, -1.0, *h, result_w, 1.0);
return finalStatus;
}