#include <GradientDescentSolver.hpp>

Inheritance diagram for dart::optimizer::GradientDescentSolver::Properties:

Public Member Functions
	Properties (const Solver::Properties &_solverProperties=Solver::Properties(), const UniqueProperties &_descentProperties=UniqueProperties())

Public Attributes
std::shared_ptr< Problem >	mProblem
	Nonlinear optimization Problem to be solved. More...

double	mTolerance
	The relative tolerance on the optimization parameters. More...

std::size_t	mNumMaxIterations
	The maximum number of iterations that the solver should use. More...

std::size_t	mIterationsPerPrint
	How many iterations between printing the Solver's progress to the terminal. More...

std::ostream *	mOutStream
	Stream for printing the Solver's progress. Default is std::cout. More...

bool	mPrintFinalResult
	Set to true if the final result should be printed to the terminal. More...

std::string	mResultFile
	Publish the results of the optimization to a file. More...

double	mStepSize
	Value of the fixed step size. More...

std::size_t	mMaxAttempts
	Number of attempts to make before quitting. More...

std::size_t	mPerturbationStep
	The number of steps between random perturbations being applied to the configuration. More...

double	mMaxPerturbationFactor
	The random perturbation works as follows: A random point in the domain of the Problem is selected, and then a random step size between 0 and mMaxPerturbationFactor is selected. More...

double	mMaxRandomizationStep
	The largest permittable change in value when randomizing a configuration. More...

double	mDefaultConstraintWeight
	This is the weight that will be applied to any constraints that do not have a corresponding weight specified by mEqConstraintWeights or by mIneqConstraintWeights. More...

Eigen::VectorXd	mEqConstraintWeights
	Vector of weights that should be applied to the equality constraints. More...

Eigen::VectorXd	mIneqConstraintWeights
	Vector of weights that should be applied to the inequality constraints. More...

Constructor & Destructor Documentation

◆ Properties()

dart::optimizer::GradientDescentSolver::Properties::Properties	(	const Solver::Properties &	_solverProperties = `Solver::Properties()`,
		const UniqueProperties &	_descentProperties = `UniqueProperties()`
	)

Member Data Documentation

◆ mDefaultConstraintWeight

double dart::optimizer::GradientDescentSolver::UniqueProperties::mDefaultConstraintWeight

inherited

This is the weight that will be applied to any constraints that do not have a corresponding weight specified by mEqConstraintWeights or by mIneqConstraintWeights.

◆ mEqConstraintWeights

Eigen::VectorXd dart::optimizer::GradientDescentSolver::UniqueProperties::mEqConstraintWeights

inherited

Vector of weights that should be applied to the equality constraints.

If there are fewer components in this vector than there are equality constraints in the Problem, then the remaining equality constraints will be assigned a weight of mDefaultConstraintWeight.

◆ mIneqConstraintWeights

Eigen::VectorXd dart::optimizer::GradientDescentSolver::UniqueProperties::mIneqConstraintWeights

inherited

Vector of weights that should be applied to the inequality constraints.

If there are fewer components in this vector than there are inequality constraints in the Problem, then the remaining inequality constraints will be assigned a weight of mDefaultConstraintWeight.

◆ mIterationsPerPrint

std::size_t dart::optimizer::Solver::Properties::mIterationsPerPrint

inherited

How many iterations between printing the Solver's progress to the terminal.

Use 0 for no printing.

◆ mMaxAttempts

std::size_t dart::optimizer::GradientDescentSolver::UniqueProperties::mMaxAttempts

inherited

Number of attempts to make before quitting.

Each attempt will start from the next seed provided by the problem. Once there are no more seeds, random starting configurations will be used.

Set this to 0 to keep trying until a solution is found (the program will need to be interrupted in order to stop if no solution is being found).

◆ mMaxPerturbationFactor

double dart::optimizer::GradientDescentSolver::UniqueProperties::mMaxPerturbationFactor

inherited

The random perturbation works as follows: A random point in the domain of the Problem is selected, and then a random step size between 0 and mMaxPerturbationFactor is selected.

The configuration will take a step of that random step size towards the random point.

A maximum value of 1.0 is recommended for mMaxPerturbationFactor. A smaller value will result in smaller randomized perturbations. A value significantly larger than 1.0 could bias the configuration towards the boundary of the Problem domain.

◆ mMaxRandomizationStep

double dart::optimizer::GradientDescentSolver::UniqueProperties::mMaxRandomizationStep

inherited

The largest permittable change in value when randomizing a configuration.

◆ mNumMaxIterations

std::size_t dart::optimizer::Solver::Properties::mNumMaxIterations

inherited

The maximum number of iterations that the solver should use.

Use 0 for infinite iterations.

◆ mOutStream

std::ostream* dart::optimizer::Solver::Properties::mOutStream

inherited

Stream for printing the Solver's progress. Default is std::cout.

◆ mPerturbationStep

std::size_t dart::optimizer::GradientDescentSolver::UniqueProperties::mPerturbationStep

inherited

The number of steps between random perturbations being applied to the configuration.

Set this to 0 to never apply randomized perturbations.

◆ mPrintFinalResult

bool dart::optimizer::Solver::Properties::mPrintFinalResult

inherited

Set to true if the final result should be printed to the terminal.

◆ mProblem

std::shared_ptr<Problem> dart::optimizer::Solver::Properties::mProblem

inherited

Nonlinear optimization Problem to be solved.

◆ mResultFile

std::string dart::optimizer::Solver::Properties::mResultFile

inherited

Publish the results of the optimization to a file.

Leave this string empty to avoid publishing anything.

◆ mStepSize

double dart::optimizer::GradientDescentSolver::UniqueProperties::mStepSize

inherited

Value of the fixed step size.

◆ mTolerance

double dart::optimizer::Solver::Properties::mTolerance

inherited

The relative tolerance on the optimization parameters.

For example, the distance between the last parameters and the current parameters to be considered converged.

Public Member Functions

Public Attributes

Constructor & Destructor Documentation

◆ Properties()

Member Data Documentation

◆ mDefaultConstraintWeight

◆ mEqConstraintWeights

◆ mIneqConstraintWeights

◆ mIterationsPerPrint

◆ mMaxAttempts

◆ mMaxPerturbationFactor

◆ mMaxRandomizationStep

◆ mNumMaxIterations

◆ mOutStream

◆ mPerturbationStep

◆ mPrintFinalResult

◆ mProblem

◆ mResultFile

◆ mStepSize

◆ mTolerance