Common line search utilites for computing the slope of a function. More...

#include <NOX_LineSearch_Utils_Slope.H>

Public Member Functions
	Slope ()
	Constructor (requires call to reset() to initialize object).

	Slope (const Teuchos::RCP< NOX::GlobalData > &gd)
	Constructor.

virtual	~Slope ()
	Destructor.

void	reset (const Teuchos::RCP< NOX::GlobalData > &gd)
	Reset method.

double	computeSlope (const NOX::Abstract::Vector &dir, const NOX::Abstract::Group &grp)
	Compute the inner product of the given direction and the gradient associated with the given group. More...

double	computeSlopeWithOutJac (const NOX::Abstract::Vector &dir, const NOX::Abstract::Group &grp)
	This is a variant of the computeSlope() method above optimized to work with out having to compute an explicit Jacobian. More...

Detailed Description

Common line search utilites for computing the slope of a function.

This class provides routines for computing the slope of a give function. There are two methods, one that uses a Jacobian and the other that estimates the action of the Jacobian by directional derivatives.

Member Function Documentation

double NOX::LineSearch::Utils::Slope::computeSlope	(	const NOX::Abstract::Vector &	dir,
		const NOX::Abstract::Group &	grp
	)

Compute the inner product of the given direction and the gradient associated with the given group.

Calculates and returns

$\zeta = d^T \nabla f(x).$

Here $d$ represents the input parameter dir and $\nabla f(x)$ is the gradient associated with the given group.

References NOX::Abstract::Group::applyJacobian(), NOX::Abstract::Vector::clone(), NOX::Abstract::Group::getF(), NOX::Abstract::Group::getGradient(), NOX::Abstract::Vector::innerProduct(), Teuchos::is_null(), NOX::Abstract::Group::isF(), NOX::Abstract::Group::isGradient(), NOX::Abstract::Group::Ok, and NOX::ShapeCopy.

double NOX::LineSearch::Utils::Slope::computeSlopeWithOutJac	(	const NOX::Abstract::Vector &	dir,
		const NOX::Abstract::Group &	grp
	)

This is a variant of the computeSlope() method above optimized to work with out having to compute an explicit Jacobian.

Calculates and returns

$\zeta = d^T \nabla f(x) = d^TJ^TF$

Here $d$ represents the input parameter dir $\nabla f(x)$ is the gradient associated with the given group (for nonlinear solves this equates to $ J^TF $ where $ J $ is the Jacobian and $ F $ is the original nonlinear function).