c

com.cra.figaro.algorithm.factored.beliefpropagation

ProbQueryBeliefPropagation

abstract class ProbQueryBeliefPropagation extends ProbQueryAlgorithm with ProbabilisticBeliefPropagation

Class to implement a probability query BP algorithm.

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Inherited
  1. ProbQueryBeliefPropagation
  2. ProbabilisticBeliefPropagation
  3. BeliefPropagation
  4. FactoredAlgorithm
  5. ProbQueryAlgorithm
  6. BaseProbQueryAlgorithm
  7. Algorithm
  8. AnyRef
  9. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ProbQueryBeliefPropagation(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 doDistribution[T](target: Element[T]): Stream[(Double, T)]
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  2. abstract def doExpectation[T](target: Element[T], function: (T) ⇒ Double): Double
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  3. abstract def doKill(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  4. abstract def doProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  5. abstract def doResume(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  6. abstract def doStart(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  7. 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 belief(source: Node): Factor[Double]

    Returns the product of all messages from a source node's neighbors to itself.

    Returns the product of all messages from a source node's neighbors to itself.

    Definition Classes
    BeliefPropagation
  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
    ProbQueryBeliefPropagationBaseProbQueryAlgorithm
  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
    ProbQueryBeliefPropagationBaseProbQueryAlgorithm
  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. def convertFactors(factors: List[Factor[Double]]): List[Factor[Double]]
    Attributes
    protected
    Definition Classes
    ProbabilisticBeliefPropagation
  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
    BeliefPropagation
  16. val dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double
  17. val dependentUniverses: List[(Universe, List[NamedEvidence[_]])]
  18. 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
  19. def doProjection[T](target: Element[T]): List[(T, Double)]
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  20. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  21. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  22. 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
  23. 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
  24. val factorGraph: FactorGraph[Double]
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    BeliefPropagation
  25. def factorToBeliefs[T](factor: Factor[Double]): List[Tuple2[Double, _]]
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    ProbabilisticBeliefPropagation
  26. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  27. def findNodeForElement[T](target: Element[T]): Node
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    ProbabilisticBeliefPropagation
  28. def generateGraph(): Unit
  29. def getBeliefsForElement[T](target: Element[T]): List[(Double, T)]

    Get the belief for an element.

    Get the belief for an element.

    Attributes
    protected[com.cra.figaro]
    Definition Classes
    ProbabilisticBeliefPropagation
  30. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  31. def getFactors(neededElements: List[Element[_]], targetElements: List[Element[_]], upperBounds: Boolean = false): List[Factor[Double]]

    Returns the factors needed for BP.

    Returns the factors needed for BP. Since BP operates on a complete factor graph, factors are created for all elements in the universe.

    Definition Classes
    ProbabilisticBeliefPropagationFactoredAlgorithm
  32. def getFinalFactorForElement[T](target: Element[T]): Factor[Double]

    Get the final factor for an element.

    Get the final factor for an element.

    Definition Classes
    ProbabilisticBeliefPropagation
  33. 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
  34. def getNewMessageFactorToVar(fn: FactorNode, vn: VariableNode): Factor[Double]
    Attributes
    protected
    Definition Classes
    BeliefPropagation
  35. def getNewMessageVarToFactor(vn: VariableNode, fn: FactorNode): Factor[Double]
    Attributes
    protected
    Definition Classes
    BeliefPropagation
  36. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  37. 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
    ProbQueryBeliefPropagationBeliefPropagationAlgorithm
  38. def isActive: Boolean
    Definition Classes
    Algorithm
  39. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  40. 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
  41. def logSpaceSemiring(): LogConvertibleSemiRing[Double]

    Returns the log space version of the semiring (or the semiring if already in log space)

    Returns the log space version of the semiring (or the semiring if already in log space)

    Attributes
    protected
    Definition Classes
    BeliefPropagation
  42. 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
  43. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  44. var neededElements: List[Element[_]]
  45. var needsBounds: Boolean
  46. def newMessage(source: Node, target: Node): Factor[Double]
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    ProbabilisticBeliefPropagationBeliefPropagation
  47. def normalize(factor: Factor[Double]): Factor[Double]

    Normalize a factor.

    Normalize a factor.

    Definition Classes
    ProbabilisticBeliefPropagation
  48. final def notify(): Unit
    Definition Classes
    AnyRef
  49. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  50. 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
  51. 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
  52. 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
  53. 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
  54. val queryTargets: List[Element[_]]
  55. 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
  56. def runStep(): Unit

    Runs this belief propagation algorithm for one iteration.

    Runs this belief propagation algorithm for one iteration. An iteration consists of each node of the factor graph sending a message to each of its neighbors.

    Definition Classes
    BeliefPropagation
  57. val semiring: SumProductSemiring
  58. 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
  59. def starterElements: List[Element[_]]

    Elements towards which queries are directed.

    Elements towards which queries are directed. By default, these are the target elements. This is overridden by DecisionVariableElimination, where it also includes utility variables.

    Definition Classes
    BeliefPropagation
  60. 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
  61. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  62. val targetElements: List[Element[_]]
  63. def toString(): String
    Definition Classes
    AnyRef → Any
  64. val universe: Universe
  65. 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
  66. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  67. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  68. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from BeliefPropagation[Double]

Inherited from FactoredAlgorithm[Double]

Inherited from ProbQueryAlgorithm

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped