c

com.cra.figaro.algorithm.sampling

OneTimeMetropolisHastings

class OneTimeMetropolisHastings extends MetropolisHastings with UnweightedSampler with OneTimeProbQuerySampler

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

  1. new OneTimeMetropolisHastings(universe: Universe, myNumSamples: Int, scheme: ProposalScheme, burnIn: Int, interval: Int, targets: Element[_]*)

    burnIn

    The number of iterations to run before samples are collected

    interval

    The number of iterations to perform between collecting samples

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

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 clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  16. 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
  17. 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
  18. 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
  19. def computeProjection[T](target: Element[T]): List[(T, Double)]
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    UnweightedSamplerBaseProbQueryAlgorithm
  20. def computeScores(): Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  21. 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
  22. var constraintsSum: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  23. val currentConstraintValues: Map[Element[_], Double]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  24. var debug: Boolean

    Set this flag to true to obtain debugging information.

    Set this flag to true to obtain debugging information.

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

    Number of samples taken

    Number of samples taken

    Definition Classes
    BaseUnweightedSampler
  48. def getTotalWeight: Double

    Total weight of samples taken, in log space

    Total weight of samples taken, in log space

    Definition Classes
    UnweightedSamplerBaseProbQuerySampler
  49. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  50. def initConstrainedValues(): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  51. def initUpdates(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  52. 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
  53. def isActive: Boolean
    Definition Classes
    Algorithm
  54. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  55. 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
  56. 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
  57. def mhStep(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  58. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  59. def newLastUpdate[T](target: Element[T]): LastUpdate[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  60. def newTimesSeen[T](target: Element[T]): TimesSeen[T]
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  61. final def notify(): Unit
    Definition Classes
    AnyRef
  62. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  63. val numSamples: Int
  64. var oldModelProb: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  65. var oldPropProb: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  66. 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
  67. 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
  68. 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
  69. 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
  70. def proposeAndUpdate(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  71. var proposedElementsSortedUpdates: Map[Iterable[Element[_]], List[Element[_]]]
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  72. lazy val queryTargets: List[Element[_]]
    Definition Classes
    BaseUnweightedSampler
  73. var rejects: Int
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  74. def resetCounts(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSamplerSampler
  75. 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
  76. def run(): Unit

    Run the algorithm, performing its computation to completion.

    Run the algorithm, performing its computation to completion.

    Definition Classes
    OneTimeMetropolisHastingsOneTimeSamplerOneTime
  77. def runScheme(): State
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  78. def sample(): (Boolean, Sample)

    Produce a single sample.

    Produce a single sample.

    Definition Classes
    MetropolisHastingsBaseUnweightedSampler
  79. var sampleCount: Int
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  80. 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
  81. 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
  82. 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
  83. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  84. 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
  85. def toString(): String
    Definition Classes
    AnyRef → Any
  86. def undo(state: State): Unit
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  87. val universe: Universe
    Definition Classes
    BaseUnweightedSampler
  88. def update(): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSamplerSampler
  89. def updateTimesSeenForTarget[T](elem: Element[T], newValue: T): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  90. def updateTimesSeenWithValue[T](value: T, timesSeen: TimesSeen[T], seen: Int): Unit
    Attributes
    protected
    Definition Classes
    BaseUnweightedSampler
  91. 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
  92. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  93. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  94. 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 MetropolisHastings

Inherited from BaseUnweightedSampler

Inherited from Sampler

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped