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com.cra.figaro.algorithm.factored.gibbs

ProbabilisticGibbs

trait ProbabilisticGibbs extends BaseUnweightedSampler with Gibbs[Double]

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Inherited
  1. ProbabilisticGibbs
  2. Gibbs
  3. FactoredAlgorithm
  4. BaseUnweightedSampler
  5. Sampler
  6. Algorithm
  7. AnyRef
  8. Any
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Type Members

  1. type LastUpdate[T] = (T, Int)
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  2. type Sample = Map[Element[_], Any]

    A sample is a map from elements to their values.

    A sample is a map from elements to their values.

    Definition Classes
    BaseUnweightedSampler
  3. class StarSampleException extends AlgorithmException
  4. type TimesSeen[T] = Map[T, Int]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler

Abstract Value Members

  1. abstract def burnIn(): Int

    Number of samples to throw away initially.

    Number of samples to throw away initially.

    Definition Classes
    Gibbs
  2. abstract def createBlocks(): List[Block]

    Method to create a blocking scheme given information about the model and factors.

    Method to create a blocking scheme given information about the model and factors.

    Definition Classes
    Gibbs
  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
    FactoredAlgorithm
  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
    FactoredAlgorithm
  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 interval(): Int

    Iterations thrown away between samples.

    Iterations thrown away between samples.

    Definition Classes
    Gibbs
  10. abstract val targetElements: List[Element[_]]

    Elements whose samples will be recorded at each iteration.

    Elements whose samples will be recorded at each iteration.

    Definition Classes
    Gibbs

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. var allLastUpdates: Map[Element[_], LastUpdate[_]]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  6. var allTimesSeen: Map[Element[_], TimesSeen[_]]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  7. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  8. val blockSamplers: List[BlockSampler]
    Attributes
    protected
  9. 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
  10. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  11. val currentSamples: Map[Variable[_], Int]

    The most recent set of samples, used for sampling variables conditioned on the values of other variables.

    The most recent set of samples, used for sampling variables conditioned on the values of other variables.

    Definition Classes
    Gibbs
  12. def doSample(): Unit
    Attributes
    protected
    Definition Classes
    ProbabilisticGibbsBaseUnweightedSamplerSampler
  13. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  14. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  15. val factors: List[Factor[Double]]

    List of all factors.

    List of all factors.

    Definition Classes
    Gibbs
  16. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  17. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  18. 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
    ProbabilisticGibbsFactoredAlgorithm
  19. 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
  20. def getSampleCount: Int

    Number of samples taken

    Number of samples taken

    Definition Classes
    BaseUnweightedSampler
  21. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  22. def initUpdates(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  23. 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
  24. def isActive: Boolean
    Definition Classes
    Algorithm
  25. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  26. 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
  27. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  28. def newLastUpdate[T](target: Element[T]): LastUpdate[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  29. def newTimesSeen[T](target: Element[T]): TimesSeen[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  30. final def notify(): Unit
    Definition Classes
    AnyRef
  31. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  32. lazy val queryTargets: List[Element[_]]
    Definition Classes
    BaseUnweightedSampler
  33. def resetCounts(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSamplerSampler
  34. 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
  35. def sample(): (Boolean, Sample)

    Produce a single sample.

    Produce a single sample.

    Definition Classes
    ProbabilisticGibbsBaseUnweightedSampler
  36. def sampleAllBlocks(): Unit
  37. var sampleCount: Int
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  38. val semiring: LogSumProductSemiring

    Semiring for use in factors.

    Semiring for use in factors.

    Definition Classes
    ProbabilisticGibbsGibbsFactoredAlgorithm
  39. 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
  40. 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
  41. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  42. def toString(): String
    Definition Classes
    AnyRef → Any
  43. val universe: Universe
    Definition Classes
    BaseUnweightedSampler
  44. def update(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSamplerSampler
  45. def updateTimesSeenForTarget[T](elem: Element[T], newValue: T): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  46. def updateTimesSeenWithValue[T](value: T, timesSeen: TimesSeen[T], seen: Int): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  47. val variables: Set[Variable[_]]

    Variables to sample at each time step.

    Variables to sample at each time step.

    Definition Classes
    Gibbs
  48. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  49. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  50. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Gibbs[Double]

Inherited from FactoredAlgorithm[Double]

Inherited from BaseUnweightedSampler

Inherited from Sampler

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped