mgo/mgo.evolution.algorithm/EMPPSE

EMPPSE

object EMPPSE
Companion
class
trait Product
trait Mirror
class Object
trait Matchable
class Any

Type members

Classlikes

case
class EMPPSEState(hitmap: HitMap, gmm: Option[(GMM, State)], probabilityMap: DensityMap)
case
class Individual[P](genome: Genome, phenotype: P)
case
class Result[P](continuous: Vector[Double], pattern: Vector[Int], density: Double, phenotype: Vector[Double], individual: Individual[P])

Types

type DensityMap = Map[Vector[Int], Double]
type Genome = (Array[Double], Double)

Inherited types

type MirroredElemLabels <: Tuple

The names of the product elements

The names of the product elements

Inherited from
Mirror
type MirroredLabel <: String

The name of the type

The name of the type

Inherited from
Mirror

Value members

Concrete methods

def acceptPoint(x: Vector[Double]): Boolean
def breeding[P](continuous: Vector[C], lambda: Int, reject: Option[Vector[Double] => Boolean]): (EvolutionState[EMPPSEState], Individual[P]) => Genome
def buildIndividual[P](g: Genome, f: P): Individual[P]
def elitism[P : CanBeNaN](pattern: P => Vector[Int], continuous: Vector[C], reject: Option[Vector[Double] => Boolean], iterations: Int, tolerance: Double, dilation: Double, warmupSampler: Int, fitOnRarest: Int): EvolutionState[EMPPSEState] => Individual[P]
def expression[P](phenotype: Vector[Double] => P, continuous: Vector[C]): Genome => Individual[P]
def initialGenomes(number: Int, continuous: Vector[C], rng: Random): Vector[Genome]
def result[P](population: Vector[Individual[P]], state: EvolutionState[EMPPSEState], continuous: Vector[C], phenotype: P => Vector[Double], pattern: Vector[Double] => Vector[Int]): Vector[Result[P]]
def result(pse: EMPPSE, population: Vector[Individual[Vector[Double]]], state: EvolutionState[EMPPSEState]): Vector[Result[Vector[Double]]]
def toSampler(gmm: GMM, reject: Option[Vector[Double] => Boolean], continuous: Vector[C], rng: Random): RejectionSampler

Implicits

Implicits