t

# ParticleBeliefPropagation 

### Companion object ParticleBeliefPropagation

#### trait ParticleBeliefPropagation extends FactoredAlgorithm[Double] with InnerBPHandler

Trait for performing particle belief propagation.

Only supports Double factors at the moment (i.e., no support for utilities or sufficient statistics)

Linear Supertypes
Ordering
1. Alphabetic
2. By Inheritance
Inherited
1. ParticleBeliefPropagation
2. InnerBPHandler
3. FactoredAlgorithm
4. Algorithm
5. AnyRef
6. Any
1. Hide All
2. Show All
Visibility
1. Public
2. All

### Abstract Value Members

1. abstract def createBP(targets: List[Element[_]], dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, depth: Int = Int.MaxValue, upperBounds: Boolean = false): Unit

Instantiates the appropriate BP algorithm for the current time step.

Instantiates the appropriate BP algorithm for the current time step.

Attributes
protected
Definition Classes
InnerBPHandler
2. abstract val densityEstimator

The density estimator that will estimate the density of a particle.

The density estimator that will estimate the density of a particle. used for resampling.

3. abstract val dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double

The algorithm to compute probability of specified evidence in a dependent universe.

The algorithm to compute probability of specified evidence in a dependent universe. We use () => Double to represent this algorithm instead of an instance of ProbEvidenceAlgorithm. Typical usage is to return the result of ProbEvidenceAlgorithm.computeProbEvidence when invoked.

Definition Classes
ParticleBeliefPropagationFactoredAlgorithm
4. abstract val dependentUniverses: List[(Universe, List[NamedEvidence[_]])]

A list of universes that depend on this universe such that evidence on those universes should be taken into account in this universe.

A list of universes that depend on this universe such that evidence on those universes should be taken into account in this universe.

Definition Classes
ParticleBeliefPropagationFactoredAlgorithm
5. abstract def doKill(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
Algorithm
6. abstract def doResume(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
Algorithm
7. abstract def doStart(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
Algorithm
8. abstract def doStop(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
Algorithm
9. abstract def getFactors(neededElements: List[Element[_]], targetElements: List[Element[_]], upperBounds: Boolean = false): List[Factor[Double]]

All implementations of factored algorithms must specify a way to get the factors from the given universe and dependent universes.

All implementations of factored algorithms must specify a way to get the factors from the given universe and dependent universes.

Definition Classes
FactoredAlgorithm
10. abstract val pbpSampler

A particle generator to generate particles and do resampling.

11. abstract def runBP(): Unit

Runs the BP algorithm at the current time step.

Runs the BP algorithm at the current time step.

Attributes
protected
Definition Classes
InnerBPHandler
12. abstract val semiring: DivideableSemiRing[Double]

Since BP uses division to compute messages, the semiring has to have a division function defined

Since BP uses division to compute messages, the semiring has to have a division function defined

Definition Classes
ParticleBeliefPropagationFactoredAlgorithm
13. abstract val targetElements: List[Element[_]]

Target elements that should not be eliminated but should be available for querying.

14. abstract val universe

The universe on which this belief propagation algorithm should be applied.

The universe on which this belief propagation algorithm should be applied.

Definition Classes
ParticleBeliefPropagationFactoredAlgorithm

### Concrete Value Members

1. final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
2. final def ##(): Int
Definition Classes
AnyRef → Any
3. final def ==(arg0: Any): Boolean
Definition Classes
AnyRef → Any
4. val active: Boolean
Attributes
protected
Definition Classes
Algorithm
5. final def asInstanceOf[T0]: T0
Definition Classes
Any
6. val

BP algorithm associated with this time step.

BP algorithm associated with this time step.

Attributes
protected[com.cra.figaro]
Definition Classes
InnerBPHandler
7. def cleanUp(): Unit

Called when the algorithm is killed.

Called when the algorithm is killed. By default, does nothing. Can be overridden.

Definition Classes
Algorithm
8. def clone(): AnyRef
Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
9. val currentUniverse

Universe associated with this algorithm.

Universe associated with this algorithm.

Attributes
protected
Definition Classes
InnerBPHandler
10. val debug: Boolean

By default, implementations that inherit this trait have no debug information.

By default, implementations that inherit this trait have no debug information. Override this if you want a debugging option.

11. final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
12. def equals(arg0: Any): Boolean
Definition Classes
AnyRef → Any
13. def finalize(): Unit
Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
14. final def getClass(): Class[_]
Definition Classes
AnyRef → Any
15. def getNeededElements(starterElements: List[Element[_]], depth: Int, parameterized: Boolean = false): (List[Element[_]], Boolean)

Get the elements that are needed by the query target variables and the evidence variables.

Get the elements that are needed by the query target variables and the evidence variables. Also compute the values of those variables to the given depth. Only get factors for elements that are actually used by the target variables. This is more efficient. Also, it avoids problems when values of unused elements have not been computed.

In addition to getting all the needed elements, it determines if any of the conditioned, constrained, or dependent universe parent elements has * in its range. If any of these elements has * in its range, the lower and upper bounds of factors will be different, so we need to compute both. If they don't, we don't need to compute bounds.

Definition Classes
FactoredAlgorithm
16. def hashCode(): Int
Definition Classes
AnyRef → Any
17. def initialize(): Unit

Called when the algorithm is started before running any steps.

Called when the algorithm is started before running any steps. By default, does nothing. Can be overridden.

Definition Classes
Algorithm
18. def isActive: Boolean
Definition Classes
Algorithm
19. final def isInstanceOf[T0]: Boolean
Definition Classes
Any
20. def kill(): Unit

Kill the algorithm so that it is inactive.

Kill the algorithm so that it is inactive. It will no longer be able to provide answers.Throws AlgorithmInactiveException if the algorithm is not active.

Definition Classes
Algorithm
21. final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
22. final def notify(): Unit
Definition Classes
AnyRef
23. final def notifyAll(): Unit
Definition Classes
AnyRef
24. def resume(): Unit

Resume the computation of the algorithm, if it has been stopped.

Resume the computation of the algorithm, if it has been stopped. Throws AlgorithmInactiveException if the algorithm is not active.

Definition Classes
Algorithm
25. def runStep(): Unit

Runs this particle belief propagation algorithm for one iteration.

Runs this particle belief propagation algorithm for one iteration. An iteration here is one iteration of the outer loop. This means that the inner BP loop may run several iterations.

26. def start(): Unit

Start the algorithm and make it active.

Start the algorithm and make it active. After it returns, the algorithm must be ready to provide answers. Throws AlgorithmActiveException if the algorithm is already active.

Definition Classes
Algorithm
27. def starterElements: List[Element[_]]

Elements towards which queries are directed.

Elements towards which queries are directed. By default, these are the target elements.

28. def stop(): Unit

Stop the algorithm from computing.

Stop the algorithm from computing. The algorithm is still ready to provide answers after it returns. Throws AlgorithmInactiveException if the algorithm is not active.

Definition Classes
Algorithm
29. final def synchronized[T0](arg0: ⇒ T0): T0
Definition Classes
AnyRef
30. def toString(): String
Definition Classes
AnyRef → Any
31. final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
32. final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
33. final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )