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# ProbabilisticVariableElimination 

#### trait ProbabilisticVariableElimination extends VariableElimination[Double]

Variable elimination over probabilistic factors.

Linear Supertypes
VariableElimination[Double], OneTime, FactoredAlgorithm[Double], Algorithm, AnyRef, Any
Known Subclasses
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Inherited
1. ProbabilisticVariableElimination
2. VariableElimination
3. OneTime
4. FactoredAlgorithm
5. Algorithm
6. AnyRef
7. Any
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Visibility
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### Abstract Value Members

1. abstract val dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double

The algorithm to compute probability of specified evidence in a dependent universe.

The algorithm to compute probability of specified evidence in a dependent universe. We use () => Double to represent this algorithm instead of an instance of ProbEvidenceAlgorithm. Typical usage is to return the result of ProbEvidenceAlgorithm.computeProbEvidence when invoked.

Definition Classes
FactoredAlgorithm
2. abstract val dependentUniverses: List[(Universe, List[NamedEvidence[_]])]

A list of universes that depend on this universe such that evidence on those universes should be taken into account in this universe.

A list of universes that depend on this universe such that evidence on those universes should be taken into account in this universe.

Definition Classes
FactoredAlgorithm
3. abstract def finish(factorsAfterElimination: MultiSet[Factor[Double]], eliminationOrder: List[Variable[_]]): Unit

All implementation of variable elimination must specify what to do after variables have been eliminated.

All implementation of variable elimination must specify what to do after variables have been eliminated.

Definition Classes
VariableElimination
4. abstract val semiring: Semiring[Double]

The sum, product operations on the factor types and appropriate values for zero and one must be defined.

The sum, product operations on the factor types and appropriate values for zero and one must be defined.

Definition Classes
FactoredAlgorithm
5. abstract val showTiming: Boolean

Flag indicating whether the run time of each step should be displayed.

Flag indicating whether the run time of each step should be displayed.

Definition Classes
VariableElimination
6. abstract val targetElements: List[Element[_]]

Target elements that should not be eliminated but should be available for querying.

Target elements that should not be eliminated but should be available for querying.

Definition Classes
VariableElimination
7. abstract val universe

The universe on which this variable elimination algorithm should be applied.

The universe on which this variable elimination algorithm should be applied.

Definition Classes
VariableEliminationFactoredAlgorithm

### 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 cleanUp(): Unit

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
Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
8. val comparator: Option[(Double, Double) ⇒ Boolean]

Some variable elimination algorithms, such as computing the most probable explanation, record values of variables as they are eliminated.

Some variable elimination algorithms, such as computing the most probable explanation, record values of variables as they are eliminated. Such values are stored in a factor that maps values of the other variables to a value of the eliminated variable. This factor is produced by finding the value of the variable that "maximizes" the entry associated with the value in the product factor resulting from eliminating this variable, for some maximization function. The recordingFunction determines which of two entries is greater according to the maximization function. It returns true iff the second entry is greater. The recording function is an option so that variable elimination algorithms that do not use it can ignore it.

Definition Classes
VariableElimination
9. 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
VariableElimination
10. def doElimination(allFactors: List[Factor[Double]], targetVariables: Seq[Variable[_]]): Unit
Attributes
protected
Definition Classes
VariableElimination
11. def doKill(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
OneTimeAlgorithm
12. def doResume(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
OneTimeAlgorithm
13. def doStart(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
OneTimeAlgorithm
14. def doStop(): Unit
Attributes
protected[com.cra.figaro.algorithm]
Definition Classes
OneTimeAlgorithm
15. def eliminateInOrder(order: List[Variable[_]], factors: MultiSet[Factor[Double]], map: FactorMap[Double]): MultiSet[Factor[Double]]
Attributes
protected
Definition Classes
VariableElimination
16. final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
17. def equals(arg0: Any): Boolean
Definition Classes
AnyRef → Any
18. def finalize(): Unit
Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
19. final def getClass(): Class[_]
Definition Classes
AnyRef → Any
20. def getFactors(allElements: List[Element[_]], targetElements: List[Element[_]], upper: Boolean = false): List[Factor[Double]]

All implementations of factored algorithms must specify a way to get the factors from the given universe and dependent universes.

All implementations of factored algorithms must specify a way to get the factors from the given universe and dependent universes.

Definition Classes
ProbabilisticVariableEliminationFactoredAlgorithm
21. 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
22. def hashCode(): Int
Definition Classes
AnyRef → Any
23. def initialFactorMap(factors: Traversable[Factor[Double]]): FactorMap[Double]
Attributes
protected
Definition Classes
VariableElimination
24. 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
25. def isActive: Boolean
Definition Classes
Algorithm
26. final def isInstanceOf[T0]: Boolean
Definition Classes
Any
27. 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
28. final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
29. final def notify(): Unit
Definition Classes
AnyRef
30. final def notifyAll(): Unit
Definition Classes
AnyRef
31. val recordingFactors: List[Factor[_]]
Attributes
protected
Definition Classes
VariableElimination
32. 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
33. def run(): Unit

Run the algorithm, performing its computation to completion.

Run the algorithm, performing its computation to completion.

Definition Classes
VariableEliminationOneTime
34. 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
35. 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
VariableElimination
36. 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
37. final def synchronized[T0](arg0: ⇒ T0): T0
Definition Classes
AnyRef
38. val targetFactors: Map[Element[_], Factor[Double]]
Attributes
protected[com.cra.figaro]
Definition Classes
VariableElimination
39. def toString(): String
Definition Classes
AnyRef → Any
40. final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
41. final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
42. final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )