c

com.cra.figaro.experimental.particlebp

ProbQueryParticleBeliefPropagation

abstract class ProbQueryParticleBeliefPropagation extends ProbQueryAlgorithm with ParticleBeliefPropagation

Class to implement a probability query BP algorithm

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Inherited
  1. ProbQueryParticleBeliefPropagation
  2. ParticleBeliefPropagation
  3. InnerBPHandler
  4. FactoredAlgorithm
  5. ProbQueryAlgorithm
  6. BaseProbQueryAlgorithm
  7. Algorithm
  8. AnyRef
  9. Any
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Visibility
  1. Public
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Instance Constructors

  1. new ProbQueryParticleBeliefPropagation(numArgSamples: Int, numTotalSamples: Int, universe: Universe, targets: Element[_]*)(dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, depth: Int = Int.MaxValue, upperBounds: Boolean = false)

Type Members

  1. class NotATargetException [T] extends AlgorithmException
    Definition Classes
    BaseProbQueryAlgorithm

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 def doDistribution[T](target: Element[T]): Stream[(Double, T)]
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  3. abstract def doExpectation[T](target: Element[T], function: (T) ⇒ Double): Double
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  4. abstract def doKill(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  5. abstract def doProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  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 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

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: ProbQueryBeliefPropagation

    BP algorithm associated with this time step.

    BP algorithm associated with this time step.

    Attributes
    protected[com.cra.figaro]
    Definition Classes
    InnerBPHandler
  7. def check[T](target: Element[T]): Unit
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  8. 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
  9. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. def computeDistribution[T](target: Element[T]): Stream[(Double, T)]

    Return an estimate of the marginal probability distribution over the target that lists each element with its probability.

    Return an estimate of the marginal probability distribution over the target that lists each element with its probability. The result is a lazy stream. It is up to the algorithm how the stream is ordered.

    Definition Classes
    ProbQueryParticleBeliefPropagationBaseProbQueryAlgorithm
  11. def computeExpectation[T](target: Element[T], function: (T) ⇒ Double): Double

    Return an estimate of the expectation of the function under the marginal probability distribution of the target.

    Return an estimate of the expectation of the function under the marginal probability distribution of the target.

    Definition Classes
    ProbQueryParticleBeliefPropagationBaseProbQueryAlgorithm
  12. def computeProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

    Definition Classes
    BaseProbQueryAlgorithm
  13. def computeProjection[T](target: Element[T]): List[(T, Double)]
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    BaseProbQueryAlgorithm
  14. val currentUniverse: Universe

    Universe associated with this algorithm.

    Universe associated with this algorithm.

    Attributes
    protected
    Definition Classes
    InnerBPHandler
  15. 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.

    Definition Classes
    ParticleBeliefPropagation
  16. val densityEstimator: AutomaticDensityEstimator
  17. val dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double
  18. val dependentUniverses: List[(Universe, List[NamedEvidence[_]])]
  19. def distribution[T](target: Element[T]): Stream[(Double, T)]

    Return an estimate of the marginal probability distribution over the target that lists each element with its probability.

    Return an estimate of the marginal probability distribution over the target that lists each element with its probability. The result is a lazy stream. It is up to the algorithm how the stream is ordered. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  20. def doProjection[T](target: Element[T]): List[(T, Double)]
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  21. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  22. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  23. def expectation[T](target: Element[T])(function: (T) ⇒ Double, c: Any = DummyImplicit): Double

    Return an estimate of the expectation of the function under the marginal probability distribution of the target.

    Return an estimate of the expectation of the function under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  24. def expectation[T](target: Element[T], function: (T) ⇒ Double): Double

    Return an estimate of the expectation of the function under the marginal probability distribution of the target.

    Return an estimate of the expectation of the function under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  25. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  26. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  27. def getFactors(neededElements: List[Element[_]], targetElements: List[Element[_]], upperBounds: Boolean = false): List[Factor[Double]]

    Getting factors for PBP returns an empty list, since all of the factor creation is handled inside of the BP instances

    Getting factors for PBP returns an empty list, since all of the factor creation is handled inside of the BP instances

    Definition Classes
    ProbQueryParticleBeliefPropagationFactoredAlgorithm
  28. 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
  29. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  30. 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
  31. def isActive: Boolean
    Definition Classes
    Algorithm
  32. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  33. 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
  34. def mean(target: Element[Double]): Double

    Return the mean of the probability density function for the given continuous element.

    Return the mean of the probability density function for the given continuous element.

    Definition Classes
    BaseProbQueryAlgorithm
  35. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  36. final def notify(): Unit
    Definition Classes
    AnyRef
  37. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  38. val pbpSampler: ParticleGenerator
  39. def posteriorElement[T](target: Element[T], universe: Universe = Universe.universe): Element[T]

    Return an element representing the posterior probability distribution of the given element.

    Return an element representing the posterior probability distribution of the given element.

    Definition Classes
    ProbQueryAlgorithm
  40. def probability[T](target: Element[T], value: T): Double

    Return an estimate of the probability that the target produces the value.

    Return an estimate of the probability that the target produces the value. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  41. def probability[T](target: Element[T])(predicate: (T) ⇒ Boolean, c: Any = DummyImplicit): Double

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  42. def probability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  43. val queryTargets: List[Element[_]]
  44. 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
  45. 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.

    Definition Classes
    ParticleBeliefPropagation
  46. val semiring: LogSumProductSemiring
  47. 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
  48. def starterElements: List[Element[_]]

    Elements towards which queries are directed.

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

    Definition Classes
    ParticleBeliefPropagation
  49. 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
  50. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  51. val targetElements: List[Element[_]]
  52. def toString(): String
    Definition Classes
    AnyRef → Any
  53. val universe: Universe
  54. def variance(target: Element[Double]): Double

    Return the variance of the probability density function for the given continuous element.

    Return the variance of the probability density function for the given continuous element.

    Definition Classes
    BaseProbQueryAlgorithm
  55. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  56. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  57. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from ParticleBeliefPropagation

Inherited from InnerBPHandler

Inherited from FactoredAlgorithm[Double]

Inherited from ProbQueryAlgorithm

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped