abstract class MetropolisHastingsAnnealer extends MetropolisHastings with MPEAlgorithm

Metropolis-Hastings based Annealer.

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Inherited
  1. MetropolisHastingsAnnealer
  2. MPEAlgorithm
  3. MetropolisHastings
  4. BaseUnweightedSampler
  5. Sampler
  6. Algorithm
  7. AnyRef
  8. Any
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Visibility
  1. Public
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Instance Constructors

  1. new MetropolisHastingsAnnealer(universe: Universe, proposalScheme: ProposalScheme, annealSchedule: Schedule, burnIn: Int, interval: Int)

    annealSchedule

    The schedule that determines how to anneal the model

    burnIn

    The number of iterations to run before annealing starts

    interval

    The number of iterations to perform before recording the annealing state .

Type Members

  1. type LastUpdate[T] = (T, Int)
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  2. type Sample = Map[Element[_], Any]

    A sample is a map from elements to their values.

    A sample is a map from elements to their values.

    Definition Classes
    BaseUnweightedSampler
  3. type TimesSeen[T] = Map[T, Int]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler

Abstract Value Members

  1. abstract def doKill(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  2. abstract def doMostLikelyValue[T](target: Element[T]): T
    Attributes
    protected
    Definition Classes
    MPEAlgorithm
  3. abstract def doResume(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  4. abstract def doStart(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm
  5. abstract def doStop(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    Algorithm

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. def accept(state: State): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  5. var acceptProbability: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  6. def acceptRejectRatio: Double

    Get the acceptance ratio for the sampler.

    Get the acceptance ratio for the sampler.

    Definition Classes
    MetropolisHastings
  7. var accepts: Int
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  8. val active: Boolean
    Attributes
    protected
    Definition Classes
    Algorithm
  9. var allLastUpdates: Map[Element[_], LastUpdate[_]]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  10. var allTimesSeen: Map[Element[_], TimesSeen[_]]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  11. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  12. var bestEnergy: Double
    Attributes
    protected
  13. var chainCache: Cache
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  14. def cleanUp(): Unit

    Clean up the sampler, freeing memory.

    Clean up the sampler, freeing memory.

    Definition Classes
    MetropolisHastingsAlgorithm
  15. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  16. def computeScores(): Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  17. var constraintsBound: Boolean

    Set this flag to true when constraints are bound between 0 and 1 to enable early rejection of states with constrained elements.

    Set this flag to true when constraints are bound between 0 and 1 to enable early rejection of states with constrained elements.

    Definition Classes
    MetropolisHastings
  18. var constraintsSum: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  19. val currentConstraintValues: Map[Element[_], Double]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  20. var currentEnergy: Double
    Attributes
    protected
  21. var debug: Boolean

    Set this flag to true to obtain debugging information.

    Set this flag to true to obtain debugging information.

    Definition Classes
    MetropolisHastings
  22. def decideToAccept(newState: State): Boolean
    Attributes
    protected
    Definition Classes
    MetropolisHastingsAnnealerMetropolisHastings
  23. var dissatisfied: Set[Element[_]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  24. def doInitialize(): Unit
  25. def doSample(): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastingsBaseUnweightedSamplerSampler
  26. var elementsUsedBy: Map[Element[_], Set[Element[_]]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  27. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  28. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  29. val fastTargets: Set[Element[_]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  30. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  31. def getBestEnergy: Double

    Return the best energy computed by the annealer.

  32. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  33. def getCurrentEnergy: Double

    Return the current energy of the annealer.

  34. def getDissatisfied: Set[Element[_]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  35. def getSampleCount: Int

    Number of samples taken

    Number of samples taken

    Definition Classes
    BaseUnweightedSampler
  36. def getTemperature: Double

    The current temperature of the model.

  37. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  38. def initConstrainedValues(): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  39. def initUpdates(): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastingsAnnealerBaseUnweightedSampler
  40. 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
  41. def isActive: Boolean
    Definition Classes
    Algorithm
  42. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  43. 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
  44. def lastTransProb: Double

    The last computed transition probability.

  45. def mhStep(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastingsAnnealerMetropolisHastings
  46. def mostLikelyValue[T](target: Element[T]): T

    Returns the most likely value for the target element.

    Returns the most likely value for the target element.

    Definition Classes
    MetropolisHastingsAnnealerMPEAlgorithm
  47. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  48. def newLastUpdate[T](target: Element[T]): LastUpdate[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  49. def newTimesSeen[T](target: Element[T]): TimesSeen[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  50. final def notify(): Unit
    Definition Classes
    AnyRef
  51. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  52. var oldModelProb: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  53. var oldPropProb: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  54. def proposeAndUpdate(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  55. var proposedElementsSortedUpdates: Map[Iterable[Element[_]], List[Element[_]]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  56. lazy val queryTargets: List[Element[_]]
    Definition Classes
    BaseUnweightedSampler
  57. var rejects: Int
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  58. def resetCounts(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSamplerSampler
  59. 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
  60. def runScheme(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  61. def sample(): (Boolean, Sample)

    Produce a single sample.

    Produce a single sample.

    Definition Classes
    MetropolisHastingsAnnealerMetropolisHastingsBaseUnweightedSampler
  62. var sampleCount: Int
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  63. 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
  64. 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
  65. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  66. def test(numSamples: Int, predicates: Seq[Predicate[_]], elementsToTrack: Seq[Element[_]]): (Double, Map[Predicate[_], Double], Map[Element[_], Double])

    Test Metropolis-Hastings by repeatedly running a single step from the same initial state.

    Test Metropolis-Hastings by repeatedly running a single step from the same initial state. For each of a set of predicates, the fraction of times the predicate is satisfied by the resulting state is returned. By the resulting state, we mean the new state if it is accepted and the original state if not.

    Definition Classes
    MetropolisHastings
  67. def toString(): String
    Definition Classes
    AnyRef → Any
  68. def undo(state: State): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  69. val universe: Universe
    Definition Classes
    BaseUnweightedSampler
  70. def update(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSamplerSampler
  71. def updateTimesSeenForTarget[T](elem: Element[T], newValue: T): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastingsAnnealerBaseUnweightedSampler
  72. def updateTimesSeenWithValue[T](value: T, timesSeen: TimesSeen[T], seen: Int): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  73. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  74. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  75. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from MPEAlgorithm

Inherited from MetropolisHastings

Inherited from BaseUnweightedSampler

Inherited from Sampler

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped