gov.sandia.cognition.statistics.bayesian

Class AbstractParticleFilter<ObservationType,ParameterType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner<ObservationType,DataDistribution<ParameterType>>

gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter<ObservationType,ParameterType>

Type Parameters:

ObservationType - Type of observations handled by the algorithm.

ParameterType - Type of parameters to infer.

All Implemented Interfaces:

BatchAndIncrementalLearner<ObservationType,DataDistribution<ParameterType>>, BatchLearner<java.util.Collection<? extends ObservationType>,DataDistribution<ParameterType>>, IncrementalLearner<ObservationType,DataDistribution<ParameterType>>, BayesianEstimator<ObservationType,ParameterType,DataDistribution<ParameterType>>, ParticleFilter<ObservationType,ParameterType>, RecursiveBayesianEstimator<ObservationType,ParameterType,DataDistribution<ParameterType>>, CloneableSerializable, Randomized, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

SamplingImportanceResamplingParticleFilter

public abstract class AbstractParticleFilter<ObservationType,ParameterType>
extends AbstractBatchAndIncrementalLearner<ObservationType,DataDistribution<ParameterType>>
implements ParticleFilter<ObservationType,ParameterType>

Partial abstract implementation of ParticleFilter.

Since:

3.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface gov.sandia.cognition.statistics.bayesian.ParticleFilter

ParticleFilter.Updater<ObservationType,ParameterType>

Field Summary

Fields

Modifier and Type	Field and Description
protected int	numParticles Number of particles in the filter.
protected java.util.Random	random Random number generator.
protected ParticleFilter.Updater<ObservationType,ParameterType>	updater Updates the particle given an existing particle.

Constructor Summary

Constructors

Constructor and Description
AbstractParticleFilter() Default constructor.

Method Summary

Modifier and Type	Method and Description
AbstractParticleFilter<ObservationType,ParameterType>	clone() This makes public the clone method on the Object class and removes the exception that it throws.
double	computeEffectiveParticles(DataDistribution<ParameterType> particles) Computes the effective number of particles.
DataDistribution<ParameterType>	createInitialLearnedObject() Creates a new initial learned object, before any data is given.
int	getNumParticles() Gets the number of particles
java.util.Random	getRandom() Gets the random number generator used by this object.
ParticleFilter.Updater<ObservationType,ParameterType>	getUpdater() Gets the updater
void	setNumParticles(int numParticles) Sets the number of particles
void	setRandom(java.util.Random random) Sets the random number generator used by this object.
void	setUpdater(ParticleFilter.Updater<ObservationType,ParameterType> updater) Setter for updater

Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner

learn, learn, update

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner

learn

Methods inherited from interface gov.sandia.cognition.learning.algorithm.IncrementalLearner

update, update

Field Detail

updater

protected ParticleFilter.Updater<ObservationType,ParameterType> updater

Updates the particle given an existing particle.

random

protected transient java.util.Random random

Random number generator.

numParticles

protected int numParticles

Number of particles in the filter.

Constructor Detail

AbstractParticleFilter

public AbstractParticleFilter()

Default constructor.

Method Detail

clone

public AbstractParticleFilter<ObservationType,ParameterType> clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class AbstractBatchAndIncrementalLearner<ObservationType,DataDistribution<ParameterType>>

Returns:

A clone of this object.

getUpdater

public ParticleFilter.Updater<ObservationType,ParameterType> getUpdater()

Description copied from interface: ParticleFilter

Gets the updater

Specified by:

getUpdater in interface ParticleFilter<ObservationType,ParameterType>

Returns:

Updater algorithm that updates the particles.

setUpdater

public void setUpdater(ParticleFilter.Updater<ObservationType,ParameterType> updater)

Setter for updater

Parameters:

updater - Updater algorithm that updates the particles.

getRandom

public java.util.Random getRandom()

Description copied from interface: Randomized

Gets the random number generator used by this object.

Specified by:

getRandom in interface Randomized

Returns:

The random number generator used by this object.

setRandom

public void setRandom(java.util.Random random)

Description copied from interface: Randomized

Sets the random number generator used by this object.

Specified by:

setRandom in interface Randomized

Parameters:

random - The random number generator for this object to use.

createInitialLearnedObject

public DataDistribution<ParameterType> createInitialLearnedObject()

Description copied from interface: IncrementalLearner

Creates a new initial learned object, before any data is given.

Specified by:

createInitialLearnedObject in interface IncrementalLearner<ObservationType,DataDistribution<ParameterType>>

Returns:

The initial learned object.

computeEffectiveParticles

public double computeEffectiveParticles(DataDistribution<ParameterType> particles)

Description copied from interface: ParticleFilter

Computes the effective number of particles.

Specified by:

computeEffectiveParticles in interface ParticleFilter<ObservationType,ParameterType>

Parameters:

particles - Current state of the Particle filter.

Returns:

Effective number of particles.

getNumParticles

public int getNumParticles()

Description copied from interface: ParticleFilter

Gets the number of particles

Specified by:

getNumParticles in interface ParticleFilter<ObservationType,ParameterType>

Returns:

Number of particles.

setNumParticles

public void setNumParticles(int numParticles)

Description copied from interface: ParticleFilter

Sets the number of particles

Specified by:

setNumParticles in interface ParticleFilter<ObservationType,ParameterType>

Parameters:

numParticles - Number of particles.