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);
}
Пример #2
0
NOX::Abstract::Group::ReturnType 
LOCA::DerivUtils::computeDwtJnDx(LOCA::MultiContinuation::AbstractGroup& grp,
				 const NOX::Abstract::MultiVector& w,
				 const NOX::Abstract::Vector& nullVector,
				 NOX::Abstract::MultiVector& result) const
{
  string callingFunction = 
    "LOCA::DerivUtils::computeDwtJnDx()";
  NOX::Abstract::Group::ReturnType status, finalStatus;

  // Vector to store w^T*J
  Teuchos::RCP<NOX::Abstract::MultiVector> wtJ = 
    w.clone(NOX::ShapeCopy);
  
  // Compute base w^T*J
  finalStatus = grp.computeJacobian();
  globalData->locaErrorCheck->checkReturnType(finalStatus, callingFunction);

  status = grp.applyJacobianTransposeMultiVector(w, *wtJ);
  finalStatus = 
    globalData->locaErrorCheck->combineAndCheckReturnTypes(status, finalStatus,
							   callingFunction);
  
  // Copy original solution vector
  Teuchos::RCP<NOX::Abstract::Vector> Xvec = 
    grp.getX().clone(NOX::DeepCopy);

  // Perturb solution vector in direction of nullVector, return perturbation
  double eps = perturbXVec(grp, *Xvec, nullVector);

  // Fill perturbed w^T*J vector
  finalStatus = grp.computeJacobian();
  globalData->locaErrorCheck->checkReturnType(finalStatus, callingFunction);
    
  status = grp.applyJacobianTransposeMultiVector(w, result);
  finalStatus = 
    globalData->locaErrorCheck->combineAndCheckReturnTypes(status, 
							   finalStatus,
							   callingFunction);

  // Difference perturbed and base vector 
  result.update(-1.0, *wtJ, 1.0);
  result.scale(1.0/eps);
  
  // Restore original solution vector
  grp.setX(*Xvec);

  return finalStatus;
}
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;
}
Пример #4
0
NOX::Abstract::Group::ReturnType
LOCA::Homotopy::Group::applyJacobianTransposeMultiVector(
			              const NOX::Abstract::MultiVector& input,
			              NOX::Abstract::MultiVector& result) const
{
  if (!isValidJacobian)
    return NOX::Abstract::Group::BadDependency;

  NOX::Abstract::Group::ReturnType status = 
    grpPtr->applyJacobianTransposeMultiVector(input, result);

  // If the Jacobian is not augmented for homotopy (i.e. using MFNK)
  // then lets augment it here.
  if (augmentJacForHomotopyNotImplemented)
    result.update(1.0-conParam, input, conParam);

  return status;
}
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);
}