c

VEGibbsStrategy 

class VEGibbsStrategy extends RaisingStrategy

A solving strategy that chooses between VE and Gibbs based on a score of the elminiation order

Linear Supertypes
Ordering
1. Alphabetic
2. By Inheritance
Inherited
1. VEGibbsStrategy
2. RaisingStrategy
3. SolvingStrategy
4. AnyRef
5. Any
1. Hide All
2. Show All
Visibility
1. Public
2. All

Instance Constructors

1. new VEGibbsStrategy(problem: Problem, raisingCriteria: RaisingCriteria, scoreThreshold: Double, numSamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator)

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. final def asInstanceOf[T0]: T0
Definition Classes
Any
5. val blockToSampler
6. val burnIn: Int
7. def chainNonConstraintFactors[ParentValue, Value](chainComp: ChainComponent[ParentValue, Value]): List[Factor[Double]]

Get non-constraint factors associated with a single Chain component.

Get non-constraint factors associated with a single Chain component.

chainComp

Chain component to process.

returns

All factors associated with the chain component that are needed for solving. This includes (possibly eliminated) subproblem factors.

Definition Classes
RaisingStrategy
8. def clone(): AnyRef
Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
9. def constraintFactors(bounds: Bounds): List[Factor[Double]]

Get all of the constraint factors needed for solving.

Get all of the constraint factors needed for solving.

bounds

Bounds for the returned constraint factors.

returns

Constraint factors for solving.

Definition Classes
SolvingStrategy
10. def eliminate(toEliminate: Set[Variable[_]], toPreserve: Set[Variable[_]], factors: List[Factor[Double]]): (List[Factor[Double]], Map[Variable[_], Factor[_]])

Solve the problem by eliminating variables, leaving only the ones that belong in the solution.

Solve the problem by eliminating variables, leaving only the ones that belong in the solution.

toEliminate

Variables to eliminate.

toPreserve

Variables to preserve.

factors

Factors over which to perform elimination.

returns

A list of factors over the variables to preserve representing their joint distribution, and a map of recording factors for MPE.

Definition Classes
VEGibbsStrategySolvingStrategy
11. final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
12. def equals(arg0: Any): Boolean
Definition Classes
AnyRef → Any
13. def execute(bounds: Bounds = Lower): Unit

Solve the problem defined by all the components' current factors.

Solve the problem defined by all the components' current factors. This involves solving and incorporating subproblems as well. This will set the globals accordingly. All components in this problem and contained subproblems should be eliminated in the solution.

bounds

Bounds for constraint factors. Defaults to `Lower`. This default is intended for the cases where it does not matter which bounds should be used because both upper and lower bounds would be the same.

Definition Classes
SolvingStrategy
14. def finalize(): Unit
Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
15. final def getClass(): Class[_]
Definition Classes
AnyRef → Any
16. def hashCode(): Int
Definition Classes
AnyRef → Any
17. val interval: Int
18. final def isInstanceOf[T0]: Boolean
Definition Classes
Any
19. final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
20. def nonConstraintFactors(): List[Factor[Double]]

Get all of the non-constraint factors needed for solving.

Get all of the non-constraint factors needed for solving. This includes subproblem factors.

returns

Non-constraint factors for solving.

Definition Classes
RaisingStrategySolvingStrategy
21. final def notify(): Unit
Definition Classes
AnyRef
22. final def notifyAll(): Unit
Definition Classes
AnyRef
23. val numSamples: Int
24. def recurse(subproblem: NestedProblem[_])

Returns a strategy that could be used to solve the nested problem.

Returns a strategy that could be used to solve the nested problem.

subproblem

Unsolved nested problem to recurse on.

returns

A strategy to solve the nested problem.

Definition Classes
VEGibbsStrategyRaisingStrategy
25. val scoreThreshold: Double
26. def subproblemNonConstraintFactors[ParentValue, Value](chainComp: ChainComponent[ParentValue, Value]): Map[ParentValue, List[Factor[Double]]]

Get the non-constraint factors associated with all subproblems of a Chain component.

Get the non-constraint factors associated with all subproblems of a Chain component. This returns the existing solution if there is one. Otherwise, it chooses to solve or raise the subproblem based on the raising criteria.

chainComp

Chain component whose subproblems are to be processed.

returns

All factors associated with subproblems that are needed for solving, grouped by parent value.

Definition Classes
RaisingStrategy
27. final def synchronized[T0](arg0: ⇒ T0): T0
Definition Classes
AnyRef
28. def toString(): String
Definition Classes
AnyRef → Any
29. final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
30. final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
31. final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )