abstract class ProbEvidenceSampler extends ProbEvidenceAlgorithm with Sampler

Algorithm that computes probability of evidence using forward sampling. The evidence is specified as NamedEvidence. Only the probability of this evidence is computed. Conditions and constraints that are already on elements are considered part of the definition of the model.

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  1. ProbEvidenceSampler
  2. Sampler
  3. ProbEvidenceAlgorithm
  4. Algorithm
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Instance Constructors

  1. new ProbEvidenceSampler(universe: Universe, evidence: List[NamedEvidence[_]] = List[NamedEvidence[_]](), partition: Double = 1.0)

Abstract Value Members

  1. abstract def additionalEvidenceAlgorithm(evidence: List[NamedEvidence[_]]): ProbEvidenceAlgorithm

    The algorithm used to compute the probability of additional evidence, as created by probAdditionalEvidence.

    The algorithm used to compute the probability of additional evidence, as created by probAdditionalEvidence. This algorithm can be different to the one defined in this class. (For example, a one-time algorithm can use an anytime algorithm for additional evidence.)

    Definition Classes
    ProbEvidenceAlgorithm
  2. abstract def doKill(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  3. abstract def doResume(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  4. abstract def doStart(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  5. abstract def doStop(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm

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. def cleanUp(): Unit

    Removes the evidence provided in the constructor from the universe.

    Removes the evidence provided in the constructor from the universe.

    Definition Classes
    ProbEvidenceSamplerProbEvidenceAlgorithmAlgorithm
  7. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. def computedResult: Double
    Attributes
    protected
    Definition Classes
    ProbEvidenceSamplerProbEvidenceAlgorithm
  9. val denominator: Double
    Definition Classes
    ProbEvidenceAlgorithm
  10. def doSample(): Unit
    Attributes
    protected
    Definition Classes
    ProbEvidenceSamplerSampler
  11. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  13. val evidence: List[NamedEvidence[_]]
  14. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  15. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  16. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  17. def initialize(): Unit

    Since probability of evidence algorithms introduce additional evidence (namely, their evidence argument), into an existing universe, a mechanism must be provided for introducing the evidence when the algorithm begins and cleaning it up at the end.

    Since probability of evidence algorithms introduce additional evidence (namely, their evidence argument), into an existing universe, a mechanism must be provided for introducing the evidence when the algorithm begins and cleaning it up at the end. This is achieved with the initialize method, called when the algorithm starts, and the cleanUp method, called when the algorithm is killed.

    Definition Classes
    ProbEvidenceAlgorithmAlgorithm
  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. def logComputedResult: Double
    Attributes
    protected
  22. def logProbEvidence: Double

    The computed log probability of evidence.

    The computed log probability of evidence.

    Definition Classes
    ProbEvidenceSamplerProbEvidenceAlgorithm
  23. val lw: LikelihoodWeighter
  24. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  25. final def notify(): Unit
    Definition Classes
    AnyRef
  26. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  27. def probAdditionalEvidence(evidence: List[NamedEvidence[_]]): ProbEvidenceAlgorithm

    Returns an algorithm to compute the probability of the additional evidence provided.

    Returns an algorithm to compute the probability of the additional evidence provided.

    Definition Classes
    ProbEvidenceAlgorithm
  28. def probEvidence: Double

    The computed probability of evidence.

    The computed probability of evidence.

    Definition Classes
    ProbEvidenceAlgorithm
  29. def resetCounts(): Unit
    Attributes
    protected
    Definition Classes
    ProbEvidenceSamplerSampler
  30. 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
  31. 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
  32. 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
  33. var successWeight: Double
    Attributes
    protected
  34. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  35. def toString(): String
    Definition Classes
    AnyRef → Any
  36. var totalWeight: Double
    Attributes
    protected
  37. val universe: Universe
  38. def update(): Unit
    Attributes
    protected
    Definition Classes
    ProbEvidenceSamplerSampler
  39. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  40. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  41. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Sampler

Inherited from ProbEvidenceAlgorithm

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

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