c

com.cra.figaro.algorithm.decision

OneTimeDecisionMetropolisHastings

class OneTimeDecisionMetropolisHastings[T, U] extends DecisionMetropolisHastings[T, U] with UnweightedSampler with OneTimeProbQuerySampler

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Inherited
  1. OneTimeDecisionMetropolisHastings
  2. OneTimeProbQuerySampler
  3. OneTimeProbQuery
  4. OneTimeSampler
  5. OneTime
  6. UnweightedSampler
  7. StreamableProbQueryAlgorithm
  8. ProbQueryAlgorithm
  9. ProbQuerySampler
  10. BaseProbQuerySampler
  11. BaseProbQueryAlgorithm
  12. DecisionMetropolisHastings
  13. DecisionAlgorithm
  14. MetropolisHastings
  15. BaseUnweightedSampler
  16. Sampler
  17. Algorithm
  18. AnyRef
  19. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new OneTimeDecisionMetropolisHastings(universe: Universe, myNumSamples: Int, scheme: ProposalScheme, burnIn: Int, interval: Int, utilityNodes: List[Element[_]], decisionTarget: Decision[T, U])

Type Members

  1. class NotATargetException [T] extends AlgorithmException
    Definition Classes
    BaseProbQueryAlgorithm
  2. type LastUpdate[T] = (T, Int)
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  3. 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
  4. type TimesSeen[T] = Map[T, Int]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  5. type WeightSeen[T] = (Element[T], Map[T, Double])
    Attributes
    protected
    Definition Classes
    DecisionMetropolisHastings

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 chainCache: Cache
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  13. def check[T](target: Element[T]): Unit
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  14. def cleanUp(): Unit

    Clean up the sampler, freeing memory.

    Clean up the sampler, freeing memory.

    Definition Classes
    MetropolisHastingsAlgorithm
  15. def cleanup(): Unit

    Cleans up the temporary elements created during sampling

    Cleans up the temporary elements created during sampling

    Definition Classes
    DecisionMetropolisHastings
  16. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  17. def computeDistribution[T](target: Element[T]): Stream[(Double, T)]

    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
    BaseProbQuerySamplerBaseProbQueryAlgorithm
  18. 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
    BaseProbQuerySamplerBaseProbQueryAlgorithm
  19. 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
  20. def computeProjection[T](target: Element[T]): List[(T, Double)]
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    UnweightedSamplerBaseProbQueryAlgorithm
  21. def computeScores(): Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  22. 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
    DecisionMetropolisHastingsDecisionAlgorithm
  23. 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
  24. var constraintsSum: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  25. val currentConstraintValues: Map[Element[_], Double]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  26. var debug: Boolean

    Set this flag to true to obtain debugging information.

    Set this flag to true to obtain debugging information.

    Definition Classes
    MetropolisHastings
  27. def decideToAccept(newState: State): Boolean
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  28. var dissatisfied: Set[Element[_]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  29. 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
  30. def doDistribution[T](target: Element[T]): Stream[(Double, T)]
    Attributes
    protected
    Definition Classes
    OneTimeProbQueryBaseProbQueryAlgorithm
  31. def doExpectation[T](target: Element[T], function: (T) ⇒ Double): Double
    Attributes
    protected
    Definition Classes
    OneTimeProbQueryBaseProbQueryAlgorithm
  32. def doInitialize(): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  33. def doKill(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  34. def doProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double
    Attributes
    protected
    Definition Classes
    OneTimeProbQueryBaseProbQueryAlgorithm
  35. def doProjection[T](target: Element[T]): List[(T, Double)]
    Attributes
    protected
    Definition Classes
    OneTimeProbQueryBaseProbQueryAlgorithm
  36. def doResume(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  37. final def doSample(): Unit
    Attributes
    protected
    Definition Classes
    DecisionMetropolisHastingsMetropolisHastingsBaseUnweightedSamplerSampler
  38. def doStart(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  39. def doStop(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  40. var elementsUsedBy: Map[Element[_], Set[Element[_]]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  41. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  42. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  43. 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
  44. 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
  45. val fastTargets: Set[Element[_]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  46. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  47. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  48. def getDissatisfied: Set[Element[_]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  49. def getSampleCount: Int

    Number of samples taken

    Number of samples taken

    Definition Classes
    BaseUnweightedSampler
  50. def getTotalWeight: Double

    Total weight of samples taken, in log space

    Total weight of samples taken, in log space

    Definition Classes
    UnweightedSamplerBaseProbQuerySampler
  51. def getUtility(p: T, d: U): DecisionSample

    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
  52. 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
  53. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  54. def initConstrainedValues(): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  55. def initUpdates(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  56. 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
  57. def isActive: Boolean
    Definition Classes
    Algorithm
  58. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  59. 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
  60. 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
  61. def mhStep(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  62. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  63. def newLastUpdate[T](target: Element[T]): LastUpdate[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  64. def newTimesSeen[T](target: Element[T]): TimesSeen[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  65. def newWeightSeen[T](target: Element[T]): WeightSeen[T]
    Attributes
    protected
    Definition Classes
    DecisionMetropolisHastings
  66. final def notify(): Unit
    Definition Classes
    AnyRef
  67. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  68. val numSamples: Int

    Number of samples to take.

    Number of samples to take.

    Definition Classes
    OneTimeDecisionMetropolisHastingsOneTimeSampler
  69. var oldModelProb: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  70. var oldPropProb: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  71. 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
  72. 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
  73. 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
  74. 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
  75. def proposeAndUpdate(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  76. var proposedElementsSortedUpdates: Map[Iterable[Element[_]], List[Element[_]]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  77. lazy val queryTargets: List[Element[_]]
    Definition Classes
    BaseUnweightedSampler
  78. var rejects: Int
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  79. def resetCounts(): Unit
    Attributes
    protected
    Definition Classes
    DecisionMetropolisHastingsBaseUnweightedSamplerSampler
  80. 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
  81. def run(): Unit

    Run the algorithm, performing its computation to completion.

    Run the algorithm, performing its computation to completion.

    Definition Classes
    OneTimeDecisionMetropolisHastingsOneTimeSamplerOneTime
  82. def runScheme(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  83. def sample(): (Boolean, Sample)

    Produce a single sample.

    Produce a single sample. In decision MH, we always update the target (parent and decision) since the utilities mights have changed

    Definition Classes
    DecisionMetropolisHastingsMetropolisHastingsBaseUnweightedSampler
  84. var sampleCount: Int
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  85. def sampleFromPosterior[T](element: Element[T]): Stream[T]

    Sample an value from the posterior of this element

    Sample an value from the posterior of this element

    Definition Classes
    UnweightedSamplerStreamableProbQueryAlgorithm
  86. 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
  87. 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
  88. 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
  89. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  90. 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
  91. def toString(): String
    Definition Classes
    AnyRef → Any
  92. def undo(state: State): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  93. val universe: Universe
    Definition Classes
    BaseUnweightedSampler
  94. def update(): Unit
    Attributes
    protected
    Definition Classes
    DecisionMetropolisHastingsBaseUnweightedSamplerSampler
  95. def updateTimesSeenForTarget[T](elem: Element[T], newValue: T): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  96. def updateTimesSeenWithValue[T](value: T, timesSeen: TimesSeen[T], seen: Int): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  97. def updateWeightSeenForTarget[T](sample: (Double, Map[Element[_], Any]), weightSeen: WeightSeen[T]): Unit
    Attributes
    protected
    Definition Classes
    DecisionMetropolisHastings
  98. def updateWeightSeenWithValue[T](value: T, weight: Double, weightSeen: WeightSeen[T]): Unit
    Attributes
    protected
    Definition Classes
    DecisionMetropolisHastings
  99. 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
  100. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  101. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  102. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from OneTimeProbQuerySampler

Inherited from OneTimeProbQuery

Inherited from OneTimeSampler

Inherited from OneTime

Inherited from UnweightedSampler

Inherited from ProbQueryAlgorithm

Inherited from ProbQuerySampler

Inherited from BaseProbQuerySampler[Element]

Inherited from DecisionMetropolisHastings[T, U]

Inherited from DecisionAlgorithm[T, U]

Inherited from MetropolisHastings

Inherited from BaseUnweightedSampler

Inherited from Sampler

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped