double NOX::LineSearch::Utils::Slope::
computeSlope(const Abstract::Vector& dir, const Abstract::Group& grp) 
{
   if (grp.isGradient()) 
     return(dir.innerProduct(grp.getGradient()));

  // Allocate space for vecPtr if necessary
   if (Teuchos::is_null(vecPtr)) 
     vecPtr = dir.clone(ShapeCopy);

  // v = J * dir
  NOX::Abstract::Group::ReturnType status = grp.applyJacobian(dir,*vecPtr);
  
  if (status != NOX::Abstract::Group::Ok) 
  {
    utils.out() << "NOX::LineSearch::Utils::Slope::computeSlope -  Unable to apply Jacobian!" << std::endl;
    throw "NOX Error";
  }

  // Check that F exists
  if (!grp.isF()) 
  {
    utils.out() << "NOX::LineSearch::Utils::Slope::computeSlope - Invalid F" << std::endl;
    throw "NOX Error";
  }

  // Return <v, F> = F' * J * dir = <J'F, dir> = <g, dir>
  return(vecPtr->innerProduct(grp.getF()));
}
예제 #2
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void NOX::Direction::QuasiNewton::MemoryUnit::reset(const Abstract::Vector& newX, 
							 const Abstract::Vector& oldX, 
							 const Abstract::Vector& newG, 
							 const Abstract::Vector& oldG)
{
  if (Teuchos::is_null(sPtr))
  {
    sPtr = newX.clone(ShapeCopy);
    yPtr = newX.clone(ShapeCopy);
  }

  sPtr->update(1.0, newX, -1.0, oldX, 0.0);
  yPtr->update(1.0, newG, -1.0, oldG, 0.0);
  sdotyValue = sPtr->innerProduct(*yPtr);
  ydotyValue = yPtr->innerProduct(*yPtr);
  rhoValue = 1.0 / sdotyValue;
}
double NOX::LineSearch::Utils::Slope::
computeSlopeWithOutJac(const Abstract::Vector& dir, 
		       const Abstract::Group& grp) 
{
  // Allocate space for vecPtr and grpPtr if necessary
  if (Teuchos::is_null(vecPtr)) 
    vecPtr = dir.clone(ShapeCopy);
  if (Teuchos::is_null(grpPtr))
    grpPtr = grp.clone(ShapeCopy);

  // Check that F exists
  if (!grp.isF()) 
  {
    utils.out() << "NOX::LineSearch::Utils::Slope::computeSlope - Invalid F" << std::endl;
    throw "NOX Error";
  }

  // Compute the perturbation parameter
  double lambda = 1.0e-6;
  double denominator = dir.norm();

  // Don't divide by zero
  if (denominator == 0.0)
    denominator = 1.0;

  double eta = lambda * (lambda + grp.getX().norm() / denominator);

  // Don't divide by zero
  if (eta == 0.0)
    eta = 1.0e-6;

  // Perturb the solution vector
  vecPtr->update(eta, dir, 1.0, grp.getX(), 0.0);

  // Compute the new F --> F(x + eta * dir)
  grpPtr->setX(*vecPtr);  
  grpPtr->computeF();

  // Compute Js = (F(x + eta * dir) - F(x))/eta
  vecPtr->update(-1.0/eta, grp.getF(), 1.0/eta, grpPtr->getF(), 0.0);
  
  return(vecPtr->innerProduct(grp.getF()));
}