UnweightedAnnealer

abstract def doKill(): Unit

abstract def doResume(): Unit

abstract def doStart(): Unit

abstract def doStop(): Unit

abstract def sample(iter: Int): (Boolean, Double)

Anneal the model with the provided iteration count.

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

var active: Boolean

final def asInstanceOf[T0]: T0

var bestEnergy: Double

var bestState: Map[Element[_], Any]

def cleanUp(): Unit

Called when the algorithm is killed.

def clone(): AnyRef

def computeEnergy: Double

val currentConstraintValues: Map[Element[_], Double]

var currentEnergy: Double

def doSample(): Unit

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

def getBestEnergy: Double

Return the best energy computed by the annealer.

final def getClass(): Class[_]

def getCurrentEnergy: Double

Return the current energy of the annealer.

def getSampleCount: Int

Number of samples taken.

def hashCode(): Int

def initialize(): Unit

Called when the algorithm is started before running any steps.

def isActive: Boolean

final def isInstanceOf[T0]: Boolean

def kill(): Unit

Kill the algorithm so that it is inactive.

def mostLikelyValue[T](target: Element[T]): T

Returns the most likely value for the target element.

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def resetCounts(): Unit

def resume(): Unit

Resume the computation of the algorithm, if it has been stopped.

var sampleCount: Int

def start(): Unit

Start the algorithm and make it active.

def stop(): Unit

Stop the algorithm from computing.

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

val universe: Universe

def update(): Unit

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit