Package pulse.search.direction

Class CompositePathOptimiser

java.lang.Object

pulse.util.UpwardsNavigable

pulse.util.Group

pulse.util.Accessible

pulse.util.PropertyHolder

pulse.search.direction.PathOptimiser

pulse.search.direction.GradientBasedOptimiser

pulse.search.direction.CompositePathOptimiser

All Implemented Interfaces:

Serializable, Descriptive, Reflexive

Direct Known Subclasses:

BFGSOptimiser, SR1Optimiser, SteepestDescentOptimiser

public abstract class CompositePathOptimiser
extends GradientBasedOptimiser

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
static double	EPS	For numerical comparison.
static int	MAX_FAILED_ATTEMPTS	Maximum number of consequent failed iterations that can be rejected.

Constructor Summary

Constructors

Constructor	Description
CompositePathOptimiser()

Method Summary

Modifier and Type	Method	Description
InstanceDescriptor<? extends LinearOptimiser>	getLinearOptimiserDescriptor()
LinearOptimiser	getLinearSolver()
GradientGuidedPath	initState(GeneralTask t)	Creates a new Path instance for storing the gradient, direction, and minimum point for this PathSolver.
boolean	iteration(GeneralTask task)	This method sets out the basic algorithm for estimating the minimum of the target function, which is defined as the sum of squared residuals (SSR), or the deviations of the model solution (a DifferenceScheme used to solve the Problem for this task) from the empirical values (the ExperimentalData).
List<Property>	listedTypes()	By default, collects a list of default properties corresponding to types defined by listedKeywords().
void	setLinearSolver(LinearOptimiser linearSearch)	Assigns a LinearSolver to this PathSolver and sets this object as its parent.

Methods inherited from class pulse.search.direction.GradientBasedOptimiser

dx, getGradientResolution, getGradientStep, gradient, listedKeywords, reset, set, setGradientResolution

Methods inherited from class pulse.search.direction.PathOptimiser

compatibleWith, genericProperties, getErrorTolerance, getInstance, getMaxIterations, getSolver, ignoreSiblings, prepare, setErrorTolerance, setInstance, setMaxIterations, setSolver, toString, update

Methods inherited from class pulse.util.PropertyHolder

addListener, areDetailsHidden, data, describe, firePropertyChanged, getDescriptor, getListeners, getPrefix, initListeners, isListedNumericType, isListedParameter, numericData, parameterListChanged, removeListeners, setPrefix, updateProperties, updateProperty

Methods inherited from class pulse.util.Accessible

accessibleChildren, genericProperty, numericProperties, numericProperty, property, update

Methods inherited from class pulse.util.Group

access, children, contents, getSimpleName, subgroups

Methods inherited from class pulse.util.UpwardsNavigable

addHierarchyListener, getHierarchyListeners, getParent, identify, removeHierarchyListener, removeHierarchyListeners, setParent, specificAncestor, tellParent

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

MAX_FAILED_ATTEMPTS

public static final int MAX_FAILED_ATTEMPTS

Maximum number of consequent failed iterations that can be rejected. Up to 2 failed attempts are allowed.

See Also:

Constant Field Values

EPS

public static final double EPS

For numerical comparison.

See Also:

Constant Field Values

Constructor Detail

CompositePathOptimiser

public CompositePathOptimiser()

Method Detail

iteration

public boolean iteration(GeneralTask task)
                  throws SolverException

Description copied from class: PathOptimiser

This method sets out the basic algorithm for estimating the minimum of the target function, which is defined as the sum of squared residuals (SSR), or the deviations of the model solution (a DifferenceScheme used to solve the Problem for this task) from the empirical values (the ExperimentalData). The algorithm will go through the following steps: (1) find the direction, which points to the minimum, using the concrete direction method; (2) estimate the magnitude of the step to reach the minimum using the LinearSolver; (3) assign a new set of parameters to the SearchTask; (4) calculate the new SSR value.

Specified by:

iteration in class PathOptimiser

Parameters:

task - a SearchTask that needs to be driven to a minimum of SSR.

Returns:

the SSR value with the newly found parameters.

Throws:

SolverException

See Also:

direction(Path), LinearOptimiser

getLinearSolver

public LinearOptimiser getLinearSolver()

setLinearSolver

public void setLinearSolver(LinearOptimiser linearSearch)

Assigns a LinearSolver to this PathSolver and sets this object as its parent.

Parameters:

linearSearch - a LinearSolver

getLinearOptimiserDescriptor

public InstanceDescriptor<? extends LinearOptimiser> getLinearOptimiserDescriptor()

listedTypes

public List<Property> listedTypes()

Description copied from class: PropertyHolder

By default, collects a list of default properties corresponding to types defined by listedKeywords(). However, this method is overridable to include non-numeric properties.

Overrides:

listedTypes in class PropertyHolder

Returns:

a list of Property instances, which have been explicitly marked as a listed parameter for this PropertyHolder.

initState

public GradientGuidedPath initState(GeneralTask t)

Creates a new Path instance for storing the gradient, direction, and minimum point for this PathSolver.

Specified by:

initState in class PathOptimiser

Parameters:

t - the search task

Returns:

a Path instance