EuclideanIndividualDiversity

abstract def clamp(values: Lens[G, Seq[Double]]): Lens[G, Seq[Double]]

abstract def genomeSize: Int

Size of the value part of the genome

abstract def individualPosition(individuals: Individual[G, P, F])(implicit rng: Random): Seq[Double]

abstract def randomGenome(implicit rng: Random): G

abstract def rawValues: Lens[G, Seq[Double]]

final def !=(arg0: Any): Boolean

final def ##(): Int

def +(other: String): String

def ->[B](y: B): (EuclideanIndividualDiversity, B)

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def distance(p1: Seq[Double], p2: Seq[Double]): Double

def ensuring(cond: (EuclideanIndividualDiversity) ⇒ Boolean, msg: ⇒ Any): EuclideanIndividualDiversity

def ensuring(cond: (EuclideanIndividualDiversity) ⇒ Boolean): EuclideanIndividualDiversity

def ensuring(cond: Boolean, msg: ⇒ Any): EuclideanIndividualDiversity

def ensuring(cond: Boolean): EuclideanIndividualDiversity

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

def formatted(fmtstr: String): String

def genomeDiversity(g: Seq[G]): Seq[Lazy[Double]]

def genomesEqualOn(g: G): Any

final def getClass(): Class[_]

def hashCode(): Int

def individualDistance(individuals: Seq[Individual[G, P, F]])(implicit rng: Random): Seq[Lazy[Double]]

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

def toString(): String

def values: Lens[G, Seq[Double]]

The value part of the genome actually used for the optimisation

final def wait(): Unit

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

final def wait(arg0: Long): Unit

def →[B](y: B): (EuclideanIndividualDiversity, B)