C++ Group::getNormF方法代码示例

bool
NOX::Solver::TensorBased::implementGlobalStrategy(NOX::Abstract::Group& newGrp,
                      double& in_stepSize,
                      const NOX::Solver::Generic& s)
{
  bool ok;
  counter.incrementNumLineSearches();
  isNewtonDirection = false;
  NOX::Abstract::Vector& searchDirection = *tensorVecPtr;

  if ((counter.getNumLineSearches() == 1)  ||  (lsType == Newton))
  {
    isNewtonDirection = true;
    searchDirection = *newtonVecPtr;
  }

  // Do line search and compute new soln.
  if ((lsType != Dual) || (isNewtonDirection))
    ok = performLinesearch(newGrp, in_stepSize, searchDirection, s);
  else if (lsType == Dual)
  {
    double fTensor = 0.0;
    double fNew = 0.0;
    double tensorStep = 1.0;
    bool isTensorDescent = false;

    const Abstract::Group& oldGrp = s.getPreviousSolutionGroup();
    double fprime = slopeObj.computeSlope(searchDirection, oldGrp);

    // Backtrack along tensor direction if it is descent direction.
    if (fprime < 0)
    {
      ok = performLinesearch(newGrp, in_stepSize, searchDirection, s);
      assert(ok);
      fTensor = 0.5 * newGrp.getNormF() * newGrp.getNormF();
      tensorStep = in_stepSize;
      isTensorDescent = true;
    }

    // Backtrack along the Newton direction.
    ok = performLinesearch(newGrp, in_stepSize, *newtonVecPtr, s);
    fNew = 0.5 * newGrp.getNormF() * newGrp.getNormF();

    // If backtracking on the tensor step produced a better step, then use it.
    if (isTensorDescent  &&  (fTensor <= fNew))
    {
      newGrp.computeX(oldGrp, *tensorVecPtr, tensorStep);
      newGrp.computeF();
    }
  }

  return ok;
}

double NOX::MeritFunction::SumOfSquares::
computef(const NOX::Abstract::Group& grp) const
{
  if ( !(grp.isF()) ) {
    utils->err()
      << "ERROR: NOX::MeritFunction::SumOfSquares::computef() - "
      << "F has not been computed yet!.  Please call "
      << "computeF() on the group passed into this function."
      << std::endl;
    throw "NOX Error";
  }

  return (0.5 * grp.getNormF() * grp.getNormF());
}

double NOX::StatusTest::NormF::computeNorm(const NOX::Abstract::Group& grp)
{
  if (!grp.isF())
    return -1.0;

  double norm;
  int n = grp.getX().length();

  switch (normType) 
  {
    
  case NOX::Abstract::Vector::TwoNorm:
    norm = grp.getNormF();
    if (scaleType == Scaled)
      norm /= sqrt(1.0 * n);
    break;

  default:
    norm = grp.getF().norm(normType);
    if (scaleType == Scaled)
      norm /= n;
    break;

  }

  return norm;
}

bool  NOX::Direction::ModifiedNewton::rescueBadNewtonSolve(const NOX::Abstract::Group& grp) const
{
  //! Check if the "rescue" option has been selected
  if (!doRescue)
    return false;

  //! See if the group has compute the accuracy
  double accuracy;
  NOX::Abstract::Group::ReturnType status = oldJacobianGrpPtr->getNormLastLinearSolveResidual(accuracy);
    
  // If this functionality is not supported in the group, return false
  /* NOTE FROM TAMMY: We could later modify this to acutally caluclate
     the error itself if it's just a matter of the status being
     NotDefined. */
  if (status != NOX::Abstract::Group::Ok) 
    return false;

  // Check if there is any improvement in the relative residual
  double normF = grp.getNormF();

  // If we can't reduce the relative norm at all, we're not happy
  if (accuracy >= normF) 
    return false;

  // Otherwise, we just print a warning and keep going
  if (utils->isPrintType(NOX::Utils::Warning))
    utils->out() << "WARNING: NOX::Direction::ModifiedNewton::compute - Unable to achieve desired linear solve accuracy." << std::endl;
  return true;

}

void
NOX::Solver::TensorBased::printDirectionInfo(std::string dirName,
                    const NOX::Abstract::Vector& dir,
                    const NOX::Abstract::Group& soln,
                    bool isTensorModel) const
{
  double dirNorm = dir.norm();

  double residual = getNormModelResidual(dir, soln, isTensorModel);
  double residualRel = residual / soln.getNormF();

  double fprime = getDirectionalDerivative(dir, soln);
  double fprimeRel = fprime / dirNorm;

  if (utilsPtr->isPrintType(NOX::Utils::Details))
  {
    utilsPtr->out() << " " << dirName << " norm of model residual =   "
     << utilsPtr->sciformat(residual, 6) << " (abs)     "
     << utilsPtr->sciformat(residualRel, 6) << " (rel)" << std::endl;
    utilsPtr->out() << " " << dirName << " directional derivative =  "
     << utilsPtr->sciformat(fprime, 6) << " (abs)    "
     << utilsPtr->sciformat(fprimeRel, 6) << " (rel)" << std::endl;
    utilsPtr->out() << " " << dirName << " norm = "
       << utilsPtr->sciformat(dirNorm, 6) << std::endl;
  }
}

double NOX::LineSearch::Polynomial::
computeValue(const NOX::Abstract::Group& grp, double phi)
{
  double value = phi;

  if (suffDecrCond == AredPred)
  {
    value = grp.getNormF();
  }

  return value;
}

bool NOX::Direction::Broyden::doRestart(NOX::Abstract::Group& soln, 
					const NOX::Solver::LineSearchBased& solver)
{
  // Test 1 - First iteration!
  if (solver.getNumIterations() == 0)
    return true;

  // Test 2 - Frequency
  if (cnt >= cntMax)
    return true;

  // Test 3 - Last step was zero!
  if (solver.getStepSize() == 0.0)
    return true;

  // Test 4 - Check for convergence rate
  convRate = soln.getNormF() / solver.getPreviousSolutionGroup().getNormF();
  if (convRate > maxConvRate)
    return true;

  return false;
}

// **************************************************************************
// *** computeForcingTerm
// **************************************************************************
double NOX::Direction::Utils::InexactNewton::
computeForcingTerm(const NOX::Abstract::Group& soln,
		   const NOX::Abstract::Group& oldsoln, 
		   int niter,
		   const NOX::Solver::Generic& solver,
		   double eta_last)
{
  const std::string indent = "       ";

  if (forcingTermMethod == Constant) {
    if (printing->isPrintType(NOX::Utils::Details)) {
      printing->out() << indent << "CALCULATING FORCING TERM" << std::endl;
      printing->out() << indent << "Method: Constant" << std::endl;
      printing->out() << indent << "Forcing Term: " << eta_k << std::endl;
    }
    if (setTolerance)
      paramsPtr->sublist(directionMethod).sublist("Linear Solver").
	set("Tolerance", eta_k);

    return eta_k;
  }

  // Get linear solver current tolerance. 
  // NOTE: These values are changing at each nonlinear iteration and 
  // must either be updated from the parameter list each time a compute 
  // is called or supplied during the function call!
  double eta_km1 = 0.0;
  if (eta_last < 0.0)
    eta_km1 = paramsPtr->sublist(directionMethod).
      sublist("Linear Solver").get("Tolerance", 0.0);
  else
    eta_km1 = eta_last;

  // Tolerance may have been adjusted in a line search algorithm so we 
  // have to account for this.
  const NOX::Solver::LineSearchBased* solverPtr = 0;
  solverPtr = dynamic_cast<const NOX::Solver::LineSearchBased*>(&solver);
  if (solverPtr != 0) {
    eta_km1 = 1.0 - solverPtr->getStepSize() * (1.0 - eta_km1);
  }

  if (printing->isPrintType(NOX::Utils::Details)) {
    printing->out() << indent << "CALCULATING FORCING TERM" << std::endl;
    printing->out() << indent << "Method: " << method << std::endl;
  }


  if (forcingTermMethod == Type1) {
    
    if (niter == 0) {
      
      eta_k = eta_initial;

    }
    else {

      // Return norm of predicted F

      // do NOT use the following lines!! This does NOT account for 
      // line search step length taken.
      // const double normpredf = 0.0;
      // oldsoln.getNormLastLinearSolveResidual(normpredf);
      
      // Create a new vector to be the predicted RHS
      if (Teuchos::is_null(predRhs)) {
	predRhs = oldsoln.getF().clone(ShapeCopy);
      }
      if (Teuchos::is_null(stepDir)) {
	stepDir = oldsoln.getF().clone(ShapeCopy);
      }
      
      // stepDir = X - oldX (i.e., the step times the direction)
      stepDir->update(1.0, soln.getX(), -1.0, oldsoln.getX(), 0);
      
      // Compute predRhs = Jacobian * step * dir
      if (!(oldsoln.isJacobian())) {
	if (printing->isPrintType(NOX::Utils::Details)) {
	  printing->out() << "WARNING: NOX::InexactNewtonUtils::resetForcingTerm() - "
	       << "Jacobian is out of date! Recomputing Jacobian." << std::endl;
	}
	const_cast<NOX::Abstract::Group&>(oldsoln).computeJacobian();
      }
      oldsoln.applyJacobian(*stepDir, *predRhs);

      // Compute predRhs = RHSVector + predRhs (this is the predicted RHS)
      predRhs->update(1.0, oldsoln.getF(), 1.0);
      
      // Compute the norms
      double normpredf = predRhs->norm();
      double normf = soln.getNormF();
      double normoldf = oldsoln.getNormF();

      if (printing->isPrintType(NOX::Utils::Details)) {
	printing->out() << indent << "Forcing Term Norm: Using L-2 Norm."
			<< std::endl;
      }

//.........这里部分代码省略.........