Trait

com.cra.figaro.algorithm

BaseProbQueryAlgorithm

Related Doc: package algorithm

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trait BaseProbQueryAlgorithm[U[_]] extends Algorithm

Algorithms that compute conditional probabilities of queries. This is a base trait, to provide support for both elements in a single universe, or references across multiple universes. Generic type U is either an Element or a Reference. T is the type of the element or reference.

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Algorithm, AnyRef, Any
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Type Members

  1. class NotATargetException[T] extends AlgorithmException

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Abstract Value Members

  1. abstract def computeDistribution[T](target: U[T]): Stream[(Double, T)]

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    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.

  2. abstract def computeExpectation[T](target: U[T], function: (T) ⇒ Double): Double

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

  3. abstract def doDistribution[T](target: U[T]): Stream[(Double, T)]

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    Attributes
    protected
  4. abstract def doExpectation[T](target: U[T], function: (T) ⇒ Double): Double

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    Attributes
    protected
  5. abstract def doKill(): Unit

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    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  6. abstract def doProbability[T](target: U[T], predicate: (T) ⇒ Boolean): Double

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    Attributes
    protected
  7. abstract def doResume(): Unit

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    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  8. abstract def doStart(): Unit

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    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  9. abstract def doStop(): Unit

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    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  10. abstract val queryTargets: Seq[U[_]]

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Concrete Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. var active: Boolean

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    Attributes
    protected
    Definition Classes
    Algorithm
  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. def cleanUp(): Unit

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    Called when the algorithm is killed.

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

    Definition Classes
    Algorithm
  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. def computeProbability[T](target: U[T], predicate: (T) ⇒ Boolean): Double

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

  9. def computeProjection[T](target: U[T]): List[(T, Double)]

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    Attributes
    protected[com.cra.figaro.algorithm]
  10. def distribution[T](target: U[T]): Stream[(Double, T)]

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    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.

  11. def doProjection[T](target: U[T]): List[(T, Double)]

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    Attributes
    protected
  12. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  13. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  14. def expectation[T](target: U[T], function: (T) ⇒ Double): Double

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    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.

  15. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  16. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  17. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  18. def initialize(): Unit

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    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
  19. def isActive: Boolean

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    Definition Classes
    Algorithm
  20. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  21. def kill(): Unit

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    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
  22. def mean(target: U[Double]): Double

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

  23. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  24. final def notify(): Unit

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    Definition Classes
    AnyRef
  25. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  26. def probability[T](target: U[T], value: T): Double

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    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.

  27. def probability[T](target: U[T], predicate: (T) ⇒ Boolean): Double

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    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.

  28. def resume(): Unit

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    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
  29. def start(): Unit

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    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
  30. def stop(): Unit

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    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
  31. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  32. def toString(): String

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    Definition Classes
    AnyRef → Any
  33. def variance(target: U[Double]): Double

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

  34. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  35. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  36. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

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