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# OneTimeProbQueryDecision 

#### trait OneTimeProbQueryDecision[T, U] extends OneTimeProbQuery with DecisionAlgorithm[T, U]

Trait for one time Decision Algorithms.

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Inherited
1. OneTimeProbQueryDecision
2. DecisionAlgorithm
3. OneTimeProbQuery
4. OneTime
5. ProbQueryAlgorithm
6. BaseProbQueryAlgorithm
7. Algorithm
8. AnyRef
9. Any
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### Type Members

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

### Abstract Value Members

1. abstract 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
BaseProbQueryAlgorithm
2. abstract 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
BaseProbQueryAlgorithm
3. abstract def computeUtility(): Map[(T, U), DecisionSample]

Compute the utility of each parent/decision tuple and return a DecisionSample.

Compute the utility of each parent/decision tuple and return a DecisionSample. Each decision algorithm must define how this is done since it is used to set the policy for a decision. For sampling algorithms, this will me a map of parent/decision tuples to a utility and a weight for that combination. For factored algorithms, the DecisionSample will contain the exact expected utility with a weight of 1.0.

Definition Classes
DecisionAlgorithm
4. abstract val queryTargets: Seq[Element[_]]
Definition Classes
BaseProbQueryAlgorithm
5. abstract def run(): Unit

Run the algorithm, performing its computation to completion.

Run the algorithm, performing its computation to completion.

Definition Classes
OneTime
6. abstract val universe
Definition Classes
ProbQueryAlgorithm

### 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 check[T](target: Element[T]): Unit
Attributes
protected
Definition Classes
BaseProbQueryAlgorithm
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 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
10. def computeProjection[T](target: Element[T]): List[(T, Double)]
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
BaseProbQueryAlgorithm
11. 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
12. def doDistribution[T](target: Element[T]): Stream[(Double, T)]
Attributes
protected
Definition Classes
OneTimeProbQueryBaseProbQueryAlgorithm
13. def doExpectation[T](target: Element[T], function: (T) ⇒ Double): Double
Attributes
protected
Definition Classes
OneTimeProbQueryBaseProbQueryAlgorithm
14. def doKill(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
OneTimeAlgorithm
15. def doProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double
Attributes
protected
Definition Classes
OneTimeProbQueryBaseProbQueryAlgorithm
16. def doProjection[T](target: Element[T]): List[(T, Double)]
Attributes
protected
Definition Classes
OneTimeProbQueryBaseProbQueryAlgorithm
17. def doResume(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
OneTimeAlgorithm
18. def doStart(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
OneTimeAlgorithm
19. def doStop(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
OneTimeAlgorithm
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. def finalize(): Unit
Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
25. final def getClass(): Class[_]
Definition Classes
AnyRef → Any
26. def getUtility(p: T, d: U)

Get the total utility and weight for a specific value of a parent and decision.

Get the total utility and weight for a specific value of a parent and decision.

Definition Classes
DecisionAlgorithm
27. def getUtility(): Map[(T, U), DecisionSample]

Get the total utility and weight for all sampled values of the parent and decision.

Get the total utility and weight for all sampled values of the parent and decision.

Definition Classes
DecisionAlgorithm
28. def hashCode(): Int
Definition Classes
AnyRef → Any
29. 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
30. def isActive: Boolean
Definition Classes
Algorithm
31. final def isInstanceOf[T0]: Boolean
Definition Classes
Any
32. 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
33. 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
34. final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
35. final def notify(): Unit
Definition Classes
AnyRef
36. final def notifyAll(): Unit
Definition Classes
AnyRef
37. 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
38. 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
39. 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
40. 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
41. 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
42. def setPolicy(e: Decision[T, U]): Unit

Sets the policy for the given decision.

Sets the policy for the given decision. This will get the computed utility of the algorithm and call setPolicy on the decision. Note there is no error checking here, so the decision in the argument must match the target decision in the algorithm.

Definition Classes
DecisionAlgorithm
43. 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
44. 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
45. final def synchronized[T0](arg0: ⇒ T0): T0
Definition Classes
AnyRef
46. def toString(): String
Definition Classes
AnyRef → Any
47. 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
48. final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
49. final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
50. final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )