class ParOneTimeParticleFilter extends ParFiltering with ParticleFilter
A parallel onetime particle filter. Distributes the work of generating particles at each time step over a specified number of threads. After generating the particles, they are recombined before resampling occurs. Instead of accepting initial and static universes as input, this method accepts functions that return universes. This is because each thread needs its own set of universes to work on. It is important that any elements created within those functions are explicitly assigned to the returned universe, not the implicit default universe.
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 ParOneTimeParticleFilter
 ParticleFilter
 ParFiltering
 OneTime
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Instance Constructors

new
ParOneTimeParticleFilter(static: () ⇒ Universe, initial: () ⇒ Universe, transition: (Universe, Universe) ⇒ Universe, numParticles: Int, numThreads: Int)
 static
A function that returns a universe of elements whose values do not change over time
 initial
A function that returns a universe describing the distribution over the initial state of the system
 transition
The transition model describing how the current state of the system depends on the static and previous, respectively
 numParticles
Number of particles to use at each time step
 numThreads
The number of threads over which to distribute the work of generating the particles at each step
Value Members

final
def
!=(arg0: Any): Boolean
 Definition Classes
 AnyRef → Any

final
def
##(): Int
 Definition Classes
 AnyRef → Any

final
def
==(arg0: Any): Boolean
 Definition Classes
 AnyRef → Any

val
active: Boolean
 Attributes
 protected
 Definition Classes
 Algorithm

def
addWeightedParticle(evidence: Seq[NamedEvidence[_]], index: Int, universes: UniverseWindow, lw: LikelihoodWeighter): WeightedParticle
 Attributes
 protected
 Definition Classes
 ParticleFilter

def
advanceTime(evidence: Seq[NamedEvidence[_]] = List()): Unit
Advance the filtering one time step, conditioning on the given evidence at the new time point.
Advance the filtering one time step, conditioning on the given evidence at the new time point.
 Definition Classes
 ParOneTimeParticleFilter → ParFiltering

def
advanceUniverse(universes: UniverseWindow, transition: (Universe, Universe) ⇒ Universe): UniverseWindow
 Attributes
 protected
 Definition Classes
 ParticleFilter

final
def
asInstanceOf[T0]: T0
 Definition Classes
 Any

val
beliefState: BeliefState
The belief about the state of the system at the current point in time.
The belief about the state of the system at the current point in time.
 Definition Classes
 ParticleFilter

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

def
clone(): AnyRef
 Attributes
 protected[java.lang]
 Definition Classes
 AnyRef
 Annotations
 @throws( ... )

def
computeCurrentDistribution[T](reference: Reference[T]): Stream[(Double, T)]
Returns the distribution over the element referred to by the reference at the current time point.
Returns the distribution over the element referred to by the reference at the current time point.
 Definition Classes
 ParticleFilter

def
computeCurrentExpectation[T](reference: Reference[T], function: (T) ⇒ Double): Double
Returns the expectation of the element referred to by the reference under the given function at the current time point.
Returns the expectation of the element referred to by the reference under the given function at the current time point.
 Definition Classes
 ParticleFilter

def
computeCurrentProbability[T](reference: Reference[T], predicate: (T) ⇒ Boolean): Double
Returns the probability that the element referred to by the reference satisfies the given predicate at the current time point.
Returns the probability that the element referred to by the reference satisfies the given predicate at the current time point.
 Attributes
 protected
 Definition Classes
 ParFiltering

def
currentDistribution[T](reference: Reference[T]): Stream[(Double, T)]
Returns the distribution over the element referred to by the reference at the current time point.
Returns the distribution over the element referred to by the reference at the current time point.
 Definition Classes
 ParFiltering

def
currentExpectation[T](reference: Reference[T], function: (T) ⇒ Double): Double
Returns the expectation of the element referred to by the reference under the given function at the current time point.
Returns the expectation of the element referred to by the reference under the given function at the current time point.
 Definition Classes
 ParFiltering

def
currentProbability[T](reference: Reference[T], predicate: (T) ⇒ Boolean): Double
Returns the probability that the element referred to by the reference satisfies the given predicate at the current time point.
Returns the probability that the element referred to by the reference satisfies the given predicate at the current time point.
 Definition Classes
 ParFiltering

def
currentProbability[T](reference: Reference[T], value: T): Double
Returns the probability that the element referred to by the reference produces the given value at the current time point.
Returns the probability that the element referred to by the reference produces the given value at the current time point.
 Definition Classes
 ParFiltering

def
doKill(): Unit
 Attributes
 protected[com.cra.figaro.algorithm]
 Definition Classes
 OneTime → Algorithm

def
doResume(): Unit
 Attributes
 protected[com.cra.figaro.algorithm]
 Definition Classes
 OneTime → Algorithm

def
doStart(): Unit
 Attributes
 protected[com.cra.figaro.algorithm]
 Definition Classes
 OneTime → Algorithm

def
doStop(): Unit
 Attributes
 protected[com.cra.figaro.algorithm]
 Definition Classes
 OneTime → Algorithm

final
def
eq(arg0: AnyRef): Boolean
 Definition Classes
 AnyRef

def
equals(arg0: Any): Boolean
 Definition Classes
 AnyRef → Any

def
finalize(): Unit
 Attributes
 protected[java.lang]
 Definition Classes
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 @throws( classOf[java.lang.Throwable] )

final
def
getClass(): Class[_]
 Definition Classes
 AnyRef → Any

def
getlogProbEvidence(): Double
The computed log probability of evidence.
The computed log probability of evidence.
 Definition Classes
 ParticleFilter

def
hashCode(): Int
 Definition Classes
 AnyRef → Any

def
initialWeightedParticle(static: Universe, current: Universe, lw: LikelihoodWeighter): WeightedParticle
 Attributes
 protected
 Definition Classes
 ParticleFilter

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

def
isActive: Boolean
 Definition Classes
 Algorithm

final
def
isInstanceOf[T0]: Boolean
 Definition Classes
 Any

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

val
logProbEvidence: Double
 Attributes
 protected
 Definition Classes
 ParticleFilter

def
makeWeightedParticle(previousState: State, currentUniverse: Universe, lw: LikelihoodWeighter): WeightedParticle
 Attributes
 protected
 Definition Classes
 ParticleFilter

final
def
ne(arg0: AnyRef): Boolean
 Definition Classes
 AnyRef

final
def
notify(): Unit
 Definition Classes
 AnyRef

final
def
notifyAll(): Unit
 Definition Classes
 AnyRef

val
numParticles: Int
 Definition Classes
 ParOneTimeParticleFilter → ParticleFilter

def
probEvidence(): Double
The computed probability of evidence.
The computed probability of evidence.
 Definition Classes
 ParticleFilter

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

def
run(): Unit
Run the algorithm, performing its computation to completion.
Run the algorithm, performing its computation to completion.
 Definition Classes
 ParOneTimeParticleFilter → OneTime

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

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

final
def
synchronized[T0](arg0: ⇒ T0): T0
 Definition Classes
 AnyRef

def
toString(): String
 Definition Classes
 AnyRef → Any

final
def
wait(): Unit
 Definition Classes
 AnyRef
 Annotations
 @throws( ... )

final
def
wait(arg0: Long, arg1: Int): Unit
 Definition Classes
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 @throws( ... )

final
def
wait(arg0: Long): Unit
 Definition Classes
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 @throws( ... )