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class GibbsSolver extends BaseUnweightedSampler with ProbabilisticGibbs with OneTime

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Inherited
  1. GibbsSolver
  2. OneTime
  3. ProbabilisticGibbs
  4. Gibbs
  5. FactoredAlgorithm
  6. BaseUnweightedSampler
  7. Sampler
  8. Algorithm
  9. AnyRef
  10. Any
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Instance Constructors

  1. new GibbsSolver(problem: Problem, toEliminate: Set[Variable[_]], toPreserve: Set[Variable[_]], _factors: List[Factor[Double]], _numSamples: Int, _burnIn: Int, _interval: Int, blockToSampler: BlockSamplerCreator)

Type Members

  1. class StarSampleException extends AlgorithmException
    Definition Classes
    ProbabilisticGibbs
  2. type LastUpdate[T] = (T, Int)
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  3. 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
  4. type TimesSeen[T] = Map[T, Int]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler

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
    Definition Classes
    ProbabilisticGibbs
  9. val blockToSampler: BlockSamplerCreator
  10. def burnIn(): Int

    Number of samples to throw away initially.

    Number of samples to throw away initially.

    Definition Classes
    GibbsSolverGibbs
  11. def chainMapper(chain: Chain[_, _]): Set[Variable[_]]
  12. 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
  13. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  14. 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
    GibbsSolverGibbs
  15. 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
  16. val dependentAlgorithm: Null
    Definition Classes
    GibbsSolverFactoredAlgorithm
  17. val dependentUniverses: Null
    Definition Classes
    GibbsSolverFactoredAlgorithm
  18. def doKill(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  19. def doResume(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  20. def doSample(): Unit
    Attributes
    protected
    Definition Classes
    ProbabilisticGibbsBaseUnweightedSamplerSampler
  21. def doStart(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  22. def doStop(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  23. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  24. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  25. val factors: List[Factor[Double]]

    List of all factors.

    List of all factors.

    Definition Classes
    Gibbs
  26. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  27. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  28. 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
  29. 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
  30. def getSampleCount: Int

    Number of samples taken

    Number of samples taken

    Definition Classes
    BaseUnweightedSampler
  31. def go(): List[Factor[Double]]
  32. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  33. def initUpdates(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  34. 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
    GibbsSolverAlgorithm
  35. def initializeBlocks(): Unit
  36. def interval(): Int

    Iterations thrown away between samples.

    Iterations thrown away between samples.

    Definition Classes
    GibbsSolverGibbs
  37. def isActive: Boolean
    Definition Classes
    Algorithm
  38. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  39. 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
  40. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  41. def newLastUpdate[T](target: Element[T]): LastUpdate[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  42. def newTimesSeen[T](target: Element[T]): TimesSeen[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  43. final def notify(): Unit
    Definition Classes
    AnyRef
  44. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  45. def numSamples(): Int
  46. lazy val queryTargets: List[Element[_]]
    Definition Classes
    BaseUnweightedSampler
  47. def resetCounts(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSamplerSampler
  48. 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
  49. def run(): Unit

    Run the algorithm, performing its computation to completion.

    Run the algorithm, performing its computation to completion.

    Definition Classes
    GibbsSolverOneTime
  50. def sample(): (Boolean, Sample)

    Produce a single sample.

    Produce a single sample.

    Definition Classes
    ProbabilisticGibbsBaseUnweightedSampler
  51. def sampleAllBlocks(): Unit
    Definition Classes
    ProbabilisticGibbs
  52. var sampleCount: Int
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  53. val semiring: LogSumProductSemiring

    Semiring for use in factors.

    Semiring for use in factors.

    Definition Classes
    ProbabilisticGibbsGibbsFactoredAlgorithm
  54. 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
  55. 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
  56. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  57. val targetElements: Null
    Definition Classes
    GibbsSolverGibbs
  58. def toString(): String
    Definition Classes
    AnyRef → Any
  59. val universe: Universe
    Definition Classes
    BaseUnweightedSampler
  60. def update(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSamplerSampler
  61. def updateTimesSeenForTarget[T](elem: Element[T], newValue: T): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  62. def updateTimesSeenWithValue[T](value: T, timesSeen: TimesSeen[T], seen: Int): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  63. val variables: Set[Variable[_]]

    Variables to sample at each time step.

    Variables to sample at each time step.

    Definition Classes
    Gibbs
  64. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  65. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  66. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from OneTime

Inherited from ProbabilisticGibbs

Inherited from Gibbs[Double]

Inherited from FactoredAlgorithm[Double]

Inherited from BaseUnweightedSampler

Inherited from Sampler

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

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