Packages

class BPSolver extends OneTimeProbabilisticBeliefPropagation

Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. BPSolver
  2. OneTimeProbabilisticBeliefPropagation
  3. OneTime
  4. ProbabilisticBeliefPropagation
  5. BeliefPropagation
  6. FactoredAlgorithm
  7. Algorithm
  8. AnyRef
  9. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new BPSolver(problem: Problem, toEliminate: Set[Variable[_]], toPreserve: Set[Variable[_]], factors: List[Factor[Double]], iters: Int, semiring: LogConvertibleSemiRing[Double])

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 cleanUp(): Unit

    Called when the algorithm is killed.

    Called when the algorithm is killed. By default, does nothing. Can be overridden.

    Definition Classes
    Algorithm
  8. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. def convertFactors(factors: List[Factor[Double]]): List[Factor[Double]]
    Attributes
    protected
    Definition Classes
    ProbabilisticBeliefPropagation
  10. 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
  11. val dependentAlgorithm: Null
    Definition Classes
    BPSolverFactoredAlgorithm
  12. val dependentUniverses: Null
    Definition Classes
    BPSolverFactoredAlgorithm
  13. def doKill(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  14. def doResume(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  15. def doStart(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  16. def doStop(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  17. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  19. val factorGraph: FactorGraph[Double]
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    BeliefPropagation
  20. def factorToBeliefs[T](factor: Factor[Double]): List[Tuple2[Double, _]]
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    ProbabilisticBeliefPropagation
  21. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  22. def findNodeForElement[T](target: Element[T]): Node
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    ProbabilisticBeliefPropagation
  23. def generateGraph(): Unit
  24. 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
  25. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  26. 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
  27. 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
  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 getNewMessageFactorToVar(fn: FactorNode, vn: VariableNode): Factor[Double]
    Attributes
    protected
    Definition Classes
    BeliefPropagation
  30. def getNewMessageVarToFactor(vn: VariableNode, fn: FactorNode): Factor[Double]
    Attributes
    protected
    Definition Classes
    BeliefPropagation
  31. def go(): (List[Factor[Double]], Map[Variable[_], Factor[_]])
  32. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  33. 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
    BPSolverBeliefPropagationAlgorithm
  34. def isActive: Boolean
    Definition Classes
    Algorithm
  35. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  36. def iterations: Int
  37. val iters: Int
  38. 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
  39. 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
  40. def makeRecordingFactor[U](v: Variable[U]): Factor[U]
  41. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  42. def newMessage(source: Node, target: Node): Factor[Double]
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    ProbabilisticBeliefPropagationBeliefPropagation
  43. def normalize(factor: Factor[Double]): Factor[Double]

    Normalize a factor.

    Normalize a factor.

    Definition Classes
    ProbabilisticBeliefPropagation
  44. final def notify(): Unit
    Definition Classes
    AnyRef
  45. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  46. 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
  47. def run(): Unit

    Run the algorithm, performing its computation to completion.

    Run the algorithm, performing its computation to completion.

    Definition Classes
    OneTimeProbabilisticBeliefPropagationOneTime
  48. 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
  49. val semiring: LogConvertibleSemiRing[Double]
    Definition Classes
    BPSolverBeliefPropagationFactoredAlgorithm
  50. 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
  51. 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
  52. 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
  53. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  54. val targetElements: Null
    Definition Classes
    BPSolverBeliefPropagation
  55. def toString(): String
    Definition Classes
    AnyRef → Any
  56. val tupleFactor: Factor[Double]
  57. val tupleVar: Variable[_]
  58. val universe: Null
    Definition Classes
    BPSolverBeliefPropagationFactoredAlgorithm
  59. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  60. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  61. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from OneTime

Inherited from BeliefPropagation[Double]

Inherited from FactoredAlgorithm[Double]

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped