本文整理汇总了C++中nox::abstract::Group::computeJacobian方法的典型用法代码示例。如果您正苦于以下问题:C++ Group::computeJacobian方法的具体用法?C++ Group::computeJacobian怎么用?C++ Group::computeJacobian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::Group
的用法示例。
在下文中一共展示了Group::computeJacobian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: throwError
bool NOX::Direction::QuasiNewton::compute(NOX::Abstract::Vector& dir,
NOX::Abstract::Group& soln,
const Solver::Generic& solver)
{
NOX::Abstract::Group::ReturnType status;
// Compute F at current solution
status = soln.computeF();
if (status != NOX::Abstract::Group::Ok)
throwError("compute", "Unable to compute F");
// Compute Jacobian at current solution.
status = soln.computeJacobian();
if (status != NOX::Abstract::Group::Ok)
throwError("compute", "Unable to compute Jacobian");
// Compute the gradient at the current solution
status = soln.computeGradient();
if (status != NOX::Abstract::Group::Ok)
throwError("compute", "Unable to compute gradient");
// Push the old information onto the memory, but only after at least one previous iteration
if (solver.getNumIterations() > 0)
{
const NOX::Abstract::Group& oldSoln = solver.getPreviousSolutionGroup();
if (oldSoln.isGradient())
memory.add(soln.getX(), oldSoln.getX(), soln.getGradient(), oldSoln.getGradient());
}
// *** Calculate the QN direction ***
// d = -g
dir = soln.getGradient();
dir.scale(-1.0);
if (!memory.empty())
{
int m = memory.size();
vector<double> alpha(m);
double beta;
for (int i = m-1; i >= 0; i --)
{
alpha[i] = memory[i].rho() * dir.innerProduct( memory[i].s() );
dir.update(-1.0 * alpha[i], memory[i].y(), 1.0);
}
dir.scale( memory[m-1].sdoty() / memory[m-1].ydoty() );
for (int i = 0; i < m; i ++)
{
beta = memory[i].rho() * dir.innerProduct( memory[i].y() );
dir.update(alpha[i] - beta, memory[i].s(), 1.0);
}
}
return true;
}
示例2: if
bool NOX::Direction::Newton::compute(NOX::Abstract::Vector& dir,
NOX::Abstract::Group& soln,
const NOX::Solver::Generic& solver)
{
NOX::Abstract::Group::ReturnType status;
// Compute F at current solution.
status = soln.computeF();
if (status != NOX::Abstract::Group::Ok)
NOX::Direction::Newton::throwError("compute", "Unable to compute F");
// Reset the linear solver tolerance.
if (useAdjustableForcingTerm) {
resetForcingTerm(soln, solver.getPreviousSolutionGroup(),
solver.getNumIterations(), solver);
}
else {
if (utils->isPrintType(Utils::Details)) {
utils->out() << " CALCULATING FORCING TERM" << endl;
utils->out() << " Method: Constant" << endl;
utils->out() << " Forcing Term: " << eta_k << endl;
}
}
// Compute Jacobian at current solution.
status = soln.computeJacobian();
if (status != NOX::Abstract::Group::Ok)
NOX::Direction::Newton::throwError("compute", "Unable to compute Jacobian");
// Compute the Newton direction
status = soln.computeNewton(paramsPtr->sublist("Newton").sublist("Linear Solver"));
// It didn't converge, but maybe we can recover.
if ((status != NOX::Abstract::Group::Ok) &&
(doRescue == false)) {
NOX::Direction::Newton::throwError("compute",
"Unable to solve Newton system");
}
else if ((status != NOX::Abstract::Group::Ok) &&
(doRescue == true)) {
if (utils->isPrintType(NOX::Utils::Warning))
utils->out() << "WARNING: NOX::Direction::Newton::compute() - Linear solve "
<< "failed to achieve convergence - using the step anyway "
<< "since \"Rescue Bad Newton Solve\" is true " << endl;
}
// Set search direction.
dir = soln.getNewton();
return true;
}
示例3: if
bool
NOX::Solver::TensorBased::computeTensorDirection(NOX::Abstract::Group& soln,
const NOX::Solver::Generic& solver)
{
NOX::Abstract::Group::ReturnType dir_status;
Teuchos::ParameterList& linearParams = paramsPtr->sublist("Direction").
sublist(paramsPtr->sublist("Direction").
get("Method","Tensor")).
sublist("Linear Solver");
// Compute F at current solution.
dir_status = soln.computeF();
if (dir_status != NOX::Abstract::Group::Ok)
throwError("computeTensorDirection", "Unable to compute F");
// Compute Jacobian at current solution.
dir_status = soln.computeJacobian();
if (dir_status != NOX::Abstract::Group::Ok)
throwError("computeTensorDirection", "Unable to compute Jacobian");
// Begin processing for the tensor step, if necessary.
double sDotS = 0.0;
int tempVal1 = 0;
if ((nIter > 0) && (requestedBaseStep == TensorStep))
{
// Compute the tensor term s = x_{k-1} - x_k
*sVecPtr = soln.getX();
sVecPtr->update(1.0, solver.getPreviousSolutionGroup().getX(), -1.0);
double normS = sVecPtr->norm();
sDotS = normS * normS;
// Form the tensor term a = (F_{k-1} - F_k - J*s) / (s^T s)^2
soln.applyJacobian(*sVecPtr, *aVecPtr);
numJvMults++;
aVecPtr->update(1.0, solver.getPreviousSolutionGroup().getF(), -1.0);
aVecPtr->update(-1.0, soln.getF(), 1.0);
if (sDotS != 0)
aVecPtr->scale(1.0 / (sDotS * sDotS));
// Save old Newton step as initial guess to second system
*tmpVecPtr = *newtonVecPtr;
tmpVecPtr->scale(-1.0); // Rewrite to avoid this?
// Compute residual of linear system using initial guess...
soln.applyJacobian(*tmpVecPtr, *residualVecPtr);
numJvMults++;
residualVecPtr->update(1.0, solver.getPreviousSolutionGroup().getF(),-1.0);
double residualNorm = residualVecPtr->norm();
#if DEBUG_LEVEL > 0
double tmpVecNorm = tmpVecPtr->norm();
double residualNormRel = residualNorm /
solver.getPreviousSolutionGroup().getNormF();
if (utilsPtr->isPrintType(NOX::Utils::Details))
{
utilsPtr->out() << " Norm of initial guess: " << utilsPtr->sciformat(tmpVecNorm, 6)
<< std::endl;
utilsPtr->out() << " initg norm of model residual = "
<< utilsPtr->sciformat(residualNorm, 6) << " (abs) "
<< utilsPtr->sciformat(residualNormRel, 6) << " (rel)" << std::endl;
}
#endif
// Save some parameters and use them later...
double tol = linearParams.get("Tolerance", 1e-4);
double relativeResidual = residualNorm /
solver.getPreviousSolutionGroup().getNormF();
// Decide whether to use initial guess...
bool isInitialGuessGood = false;
#ifdef USE_INITIAL_GUESS_LOGIC
if (relativeResidual < 1.0)
{
if (utilsPtr->isPrintType(NOX::Utils::Details))
utilsPtr->out() << " Initial guess is good..." << std::endl;
isInitialGuessGood = true;
// RPP - Brett please make sure the line below is correct.
*tensorVecPtr = *tmpVecPtr;
double newTol = tol / relativeResidual;
if (newTol > 0.99)
newTol = 0.99; // force at least one iteration
linearParams.set("Tolerance", newTol);
if (utilsPtr->isPrintType(NOX::Utils::Details))
utilsPtr->out() << " Setting tolerance to " << utilsPtr->sciformat(newTol,6) << std::endl;
}
else
#endif // USE_INITIAL_GUESS_LOGIC
{
//utilsPtr->out() << " Initial guess is BAD... do not use!\n";
isInitialGuessGood = false;
*residualVecPtr = solver.getPreviousSolutionGroup().getF();
}
// Compute the term inv(J)*Fp....
tmpVecPtr->init(0.0);
dir_status = soln.applyJacobianInverse(linearParams, *residualVecPtr,
*tmpVecPtr);
// If it didn't converge, maybe we can recover.
//.........这里部分代码省略.........