#include <Optimiser.h>

Inheritance diagram for Optimiser:

Public Types
typedef float	PrecisionType

Public Member Functions
	Optimiser ()

virtual	~Optimiser ()

void	SetObjectiveFunction (std::shared_ptr< ObjectiveFunction > &objectiveFunctionIn)

virtual void	Optimise (PrecisionType *startingPoint)=0

virtual void	Initialise ()=0

PrecisionType	GetBestObjectiveFunctionValue ()

PrecisionType	GetInitialObjectiveFunctionValue ()

PrecisionType *	GetBestPoint ()

void	ResetCurrentIterationNumber ()

void	SetMaxIterations (unsigned int maxIterations)

void	SetPreviouslyEvaluatedObjectiveFunctionValue (PrecisionType objectiveFunctionValue)

void	SetOutputIntermediateGradientFolder (const std::string &outputFolderIn, const std::string &outPrefix)

Protected Member Functions
void	MoveCurrentPointAlongGradient (PrecisionType stepSize)

void	PerformLineSearch (PrecisionType maxLength, PrecisionType smallLength, PrecisionType &startLength)

Protected Attributes
PrecisionType	currentObjectiveFunctionValue
	The current objective function value corresponding to the current iteration. More...

PrecisionType	bestObjectiveFunctionValue
	The best objective function value achieved. More...

PrecisionType	initialObjectiveFunctionValue
	The objective function value at the starting point of the optimisation. More...

unsigned int	currentIterationNumber
	Tracker of the current iteration number. More...

unsigned int	maxNumberOfIterations
	The maximum number of allowed iterations. More...

const unsigned int	maxNumberOfLineIterations
	The maximum number of iterations used for the line-serach along the gradient. More...

PrecisionType	maxLineSearchStepSize
	The maximum step size used for the line-search. Has to be initialised in derived class. More...

PrecisionType	minLineSearchStepSize
	The minimum step size used for the line-search. Has to be initialised in derived class. More...

unsigned int	numberOfIterationsPerformed
	The total number of iterations performed. More...

unsigned int	numberOfDOFs
	The number of degrees of freedom. More...

std::shared_ptr< ObjectiveFunction >	objectiveFunction
	Shared pointer to the objective function. More...

PrecisionType *	gradient
	The array xi in numerical recipes. More...

PrecisionType *	currentPoint
	The current point, p in numerical recipes. More...

PrecisionType *	bestPoint
	The best point achieved, p in numerical recipes. More...

PrecisionType	preEvaluatedObjectiveFunctionValue
	A pre-calculated objective function value that will be used during the optimisation if usePreEvaluatedEvaluatedObjectiveFunctionValue is set to true. More...

bool	usePreEvaluatedEvaluatedObjectiveFunctionValue
	Indicator if the first objective function value calculation can be skipped. More...

std::string	outputIntermediateGradientFolder
	Folder to which the intermediated objective function gradients will be saved. More...

std::string	outputIntermediateGradientPrefix
	String holding additional information to differentiate the output from different levels. More...

Detailed Description

Base class that defines the basic optimiser functionality. Has to be derived and implemented into a working optimiser class.

Member Typedef Documentation

◆ PrecisionType

typedef float Optimiser::PrecisionType

Constructor & Destructor Documentation

◆ Optimiser()

Optimiser::Optimiser ( )

Constructor

◆ ~Optimiser()

Optimiser::~Optimiser ( )

virtual

Destructor

Member Function Documentation

◆ GetBestObjectiveFunctionValue()

Optimiser::PrecisionType Optimiser::GetBestObjectiveFunctionValue ( )

Return the best objecitve function value

◆ GetBestPoint()

Optimiser::PrecisionType * Optimiser::GetBestPoint ( )

Return the pointer to the point which resulted in the best functcion value.

◆ GetInitialObjectiveFunctionValue()

Optimiser::PrecisionType Optimiser::GetInitialObjectiveFunctionValue ( )

Return the initial objecitve function value

◆ Initialise()

virtual void Optimiser::Initialise ( )

pure virtual

Initialise the optimiser. Needs to be implemented by inheriting class.

Implemented in ConjugateGradientOptimiser.

◆ MoveCurrentPointAlongGradient()

void Optimiser::MoveCurrentPointAlongGradient ( PrecisionType stepSize )

inlineprotected

Move the current point so that it moves by step size from the best point into the direction of the gradient.

\[ \mathbf{p}_\mathrm{cur} = \mathbf{p}_\mathrm{best} + s \cdot \nabla\mathbf{f} \]

Todo:: Make parallel

◆ Optimise()

virtual void Optimiser::Optimise ( PrecisionType * startingPoint )

pure virtual

Initiate the optimisation

Parameters

startingPoint Point where to start the optimisation from. Can be null-pointer to start form zero.

Implemented in ConjugateGradientOptimiser.

◆ PerformLineSearch()

void Optimiser::PerformLineSearch	(	PrecisionType	maxLength,
		PrecisionType	smallLength,
		PrecisionType &	startLength
	)

protected

Perform a line search. Walk along the gradient direction with increasing step sizes. If no more improvements are found, continue with halved step sizes until the minimum size was reached, or maximum number of maxNumberOfLineIterations was exceeded.

Parameters

maxLength	The maximum size to which the line-search steps are limited.
smallLength	The length below which no more line-search steps are performed.
startLength	The initial step-size. Will be updated with the total stpe size which can be utilised for consecutive line-searches (i.e. with updated gradients).

◆ ResetCurrentIterationNumber()

void Optimiser::ResetCurrentIterationNumber ( )

Set the current iteration number to zero.

◆ SetMaxIterations()

void Optimiser::SetMaxIterations ( unsigned int maxIterations )

inline

Set the number of iterations

Parameters

maxIterations The maximum number of iterations performed.

◆ SetObjectiveFunction()

void Optimiser::SetObjectiveFunction ( std::shared_ptr< ObjectiveFunction > & objectiveFunctionIn )

Set the objective function which is to be optimised

Parameters

objectiveFunctionIn Shared pointer to the objective function

◆ SetOutputIntermediateGradientFolder()

void Optimiser::SetOutputIntermediateGradientFolder	(	const std::string &	outputFolderIn,
		const std::string &	outPrefix
	)

inline

◆ SetPreviouslyEvaluatedObjectiveFunctionValue()

void Optimiser::SetPreviouslyEvaluatedObjectiveFunctionValue ( PrecisionType objectiveFunctionValue )

Set a previously evaluated objective function value such that the first value calculation can be skipped during the optimisation. Note this value has to be the same as for the starting point of the optimisation. No additional checks are being performed internally.

Member Data Documentation

◆ bestObjectiveFunctionValue

PrecisionType Optimiser::bestObjectiveFunctionValue

protected

The best objective function value achieved.

◆ bestPoint

PrecisionType* Optimiser::bestPoint

protected

The best point achieved, p in numerical recipes.

◆ currentIterationNumber

unsigned int Optimiser::currentIterationNumber

protected

Tracker of the current iteration number.

◆ currentObjectiveFunctionValue

PrecisionType Optimiser::currentObjectiveFunctionValue

protected

The current objective function value corresponding to the current iteration.

◆ currentPoint

PrecisionType* Optimiser::currentPoint

protected

The current point, p in numerical recipes.

◆ gradient

PrecisionType* Optimiser::gradient

protected

The array xi in numerical recipes.

◆ initialObjectiveFunctionValue

PrecisionType Optimiser::initialObjectiveFunctionValue

protected

The objective function value at the starting point of the optimisation.

◆ maxLineSearchStepSize

PrecisionType Optimiser::maxLineSearchStepSize

protected

The maximum step size used for the line-search. Has to be initialised in derived class.

◆ maxNumberOfIterations

unsigned int Optimiser::maxNumberOfIterations

protected

The maximum number of allowed iterations.

◆ maxNumberOfLineIterations

const unsigned int Optimiser::maxNumberOfLineIterations

protected

The maximum number of iterations used for the line-serach along the gradient.

◆ minLineSearchStepSize

PrecisionType Optimiser::minLineSearchStepSize

protected

The minimum step size used for the line-search. Has to be initialised in derived class.

◆ numberOfDOFs

unsigned int Optimiser::numberOfDOFs

protected

The number of degrees of freedom.

◆ numberOfIterationsPerformed

unsigned int Optimiser::numberOfIterationsPerformed

protected

The total number of iterations performed.

◆ objectiveFunction

std::shared_ptr<ObjectiveFunction> Optimiser::objectiveFunction

protected

Shared pointer to the objective function.

◆ outputIntermediateGradientFolder

std::string Optimiser::outputIntermediateGradientFolder

protected

Folder to which the intermediated objective function gradients will be saved.

◆ outputIntermediateGradientPrefix

std::string Optimiser::outputIntermediateGradientPrefix

protected

String holding additional information to differentiate the output from different levels.

◆ preEvaluatedObjectiveFunctionValue

PrecisionType Optimiser::preEvaluatedObjectiveFunctionValue

protected

A pre-calculated objective function value that will be used during the optimisation if usePreEvaluatedEvaluatedObjectiveFunctionValue is set to true.

◆ usePreEvaluatedEvaluatedObjectiveFunctionValue

bool Optimiser::usePreEvaluatedEvaluatedObjectiveFunctionValue

protected

Indicator if the first objective function value calculation can be skipped.

The documentation for this class was generated from the following files:

motion-lib/Optimiser.h
motion-lib/Optimiser.cpp

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ PrecisionType

Constructor & Destructor Documentation

◆ Optimiser()

◆ ~Optimiser()

Member Function Documentation

◆ GetBestObjectiveFunctionValue()

◆ GetBestPoint()

◆ GetInitialObjectiveFunctionValue()

◆ Initialise()

◆ MoveCurrentPointAlongGradient()

◆ Optimise()

◆ PerformLineSearch()

◆ ResetCurrentIterationNumber()

◆ SetMaxIterations()

◆ SetObjectiveFunction()

◆ SetOutputIntermediateGradientFolder()

◆ SetPreviouslyEvaluatedObjectiveFunctionValue()

Member Data Documentation

◆ bestObjectiveFunctionValue

◆ bestPoint

◆ currentIterationNumber

◆ currentObjectiveFunctionValue

◆ currentPoint

◆ gradient

◆ initialObjectiveFunctionValue

◆ maxLineSearchStepSize

◆ maxNumberOfIterations

◆ maxNumberOfLineIterations

◆ minLineSearchStepSize

◆ numberOfDOFs

◆ numberOfIterationsPerformed

◆ objectiveFunction

◆ outputIntermediateGradientFolder

◆ outputIntermediateGradientPrefix

◆ preEvaluatedObjectiveFunctionValue

◆ usePreEvaluatedEvaluatedObjectiveFunctionValue